[refactor](Nereids) add result sink node (#22254)

use ResultSink as query root node to let plan of query statement
has the same pattern with insert statement

fe/fe-core/src/main/java/org/apache/doris/nereids/analyzer/UnboundOlapTableSink.java

@@ -17,6 +17,7 @@
 
 package org.apache.doris.nereids.analyzer;
 
+import org.apache.doris.nereids.exceptions.UnboundException;
 import org.apache.doris.nereids.memo.GroupExpression;
 import org.apache.doris.nereids.properties.LogicalProperties;
 import org.apache.doris.nereids.properties.UnboundLogicalProperties;
@@ -143,6 +144,6 @@ public class UnboundOlapTableSink<CHILD_TYPE extends Plan> extends LogicalSink<C
 
     @Override
     public List<Slot> computeOutput() {
-        return child().getOutput();
+        throw new UnboundException("output");
     }
 }

fe/fe-core/src/main/java/org/apache/doris/nereids/analyzer/UnboundResultSink.java

@@ -0,0 +1,89 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+package org.apache.doris.nereids.analyzer;
+
+import org.apache.doris.nereids.exceptions.UnboundException;
+import org.apache.doris.nereids.memo.GroupExpression;
+import org.apache.doris.nereids.properties.LogicalProperties;
+import org.apache.doris.nereids.trees.expressions.Expression;
+import org.apache.doris.nereids.trees.expressions.Slot;
+import org.apache.doris.nereids.trees.plans.Plan;
+import org.apache.doris.nereids.trees.plans.PlanType;
+import org.apache.doris.nereids.trees.plans.algebra.Sink;
+import org.apache.doris.nereids.trees.plans.logical.LogicalSink;
+import org.apache.doris.nereids.trees.plans.visitor.PlanVisitor;
+import org.apache.doris.nereids.util.Utils;
+
+import com.google.common.base.Preconditions;
+
+import java.util.List;
+import java.util.Optional;
+
+/**
+ * unbound result sink
+ */
+public class UnboundResultSink<CHILD_TYPE extends Plan> extends LogicalSink<CHILD_TYPE> implements Unbound, Sink {
+
+    public UnboundResultSink(CHILD_TYPE child) {
+        super(PlanType.LOGICAL_UNBOUND_RESULT_SINK, child);
+    }
+
+    public UnboundResultSink(Optional<GroupExpression> groupExpression,
+            Optional<LogicalProperties> logicalProperties, CHILD_TYPE child) {
+        super(PlanType.LOGICAL_UNBOUND_RESULT_SINK, groupExpression, logicalProperties, child);
+    }
+
+    @Override
+    public Plan withChildren(List<Plan> children) {
+        Preconditions.checkArgument(children.size() == 1, "UnboundResultSink only accepts one child");
+        return new UnboundResultSink<>(groupExpression, Optional.of(getLogicalProperties()), children.get(0));
+    }
+
+    @Override
+    public <R, C> R accept(PlanVisitor<R, C> visitor, C context) {
+        return visitor.visitUnboundResultSink(this, context);
+    }
+
+    @Override
+    public List<? extends Expression> getExpressions() {
+        throw new UnsupportedOperationException(this.getClass().getSimpleName() + " don't support getExpression()");
+    }
+
+    @Override
+    public Plan withGroupExpression(Optional<GroupExpression> groupExpression) {
+        return new UnboundResultSink<>(groupExpression, Optional.of(getLogicalProperties()), child());
+    }
+
+    @Override
+    public Plan withGroupExprLogicalPropChildren(Optional<GroupExpression> groupExpression,
+            Optional<LogicalProperties> logicalProperties, List<Plan> children) {
+        Preconditions.checkArgument(children.size() == 1, "UnboundResultSink only accepts one child");
+        return new UnboundResultSink<>(groupExpression, logicalProperties, children.get(0));
+
+    }
+
+    @Override
+    public List<Slot> computeOutput() {
+        throw new UnboundException("output");
+    }
+
+    @Override
+    public String toString() {
+        return Utils.toSqlString("UnboundResultSink[" + id.asInt() + "]");
+    }
+}

fe/fe-core/src/main/java/org/apache/doris/nereids/glue/translator/PhysicalPlanTranslator.java

@@ -112,6 +112,7 @@ import org.apache.doris.nereids.trees.plans.physical.PhysicalPlan;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalProject;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalQuickSort;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalRepeat;
+import org.apache.doris.nereids.trees.plans.physical.PhysicalResultSink;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalSchemaScan;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalSetOperation;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalStorageLayerAggregate;
@@ -318,6 +319,12 @@ public class PhysicalPlanTranslator extends DefaultPlanVisitor<PlanFragment, Pla
      * sink Node, in lexicographical order
      * ******************************************************************************************** */
 
+    @Override
+    public PlanFragment visitPhysicalResultSink(PhysicalResultSink<? extends Plan> physicalResultSink,
+            PlanTranslatorContext context) {
+        return physicalResultSink.child().accept(this, context);
+    }
+
     @Override
     public PlanFragment visitPhysicalOlapTableSink(PhysicalOlapTableSink<? extends Plan> olapTableSink,
             PlanTranslatorContext context) {

fe/fe-core/src/main/java/org/apache/doris/nereids/parser/LogicalPlanBuilder.java

@@ -121,6 +121,7 @@ import org.apache.doris.nereids.analyzer.UnboundFunction;
 import org.apache.doris.nereids.analyzer.UnboundOlapTableSink;
 import org.apache.doris.nereids.analyzer.UnboundOneRowRelation;
 import org.apache.doris.nereids.analyzer.UnboundRelation;
+import org.apache.doris.nereids.analyzer.UnboundResultSink;
 import org.apache.doris.nereids.analyzer.UnboundSlot;
 import org.apache.doris.nereids.analyzer.UnboundStar;
 import org.apache.doris.nereids.analyzer.UnboundTVFRelation;
@@ -312,7 +313,12 @@ public class LogicalPlanBuilder extends DorisParserBaseVisitor<Object> {
     @Override
     public LogicalPlan visitStatementDefault(StatementDefaultContext ctx) {
         LogicalPlan plan = plan(ctx.query());
-        return withExplain(withOutFile(plan, ctx.outFileClause()), ctx.explain());
+        if (ctx.outFileClause() != null) {
+            plan = withOutFile(plan, ctx.outFileClause());
+        } else {
+            plan = new UnboundResultSink<>(plan);
+        }
+        return withExplain(plan, ctx.explain());
     }
 
     @Override

fe/fe-core/src/main/java/org/apache/doris/nereids/properties/RequestPropertyDeriver.java

@@ -34,6 +34,7 @@ import org.apache.doris.nereids.trees.plans.physical.PhysicalHashJoin;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalLimit;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalNestedLoopJoin;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalOlapTableSink;
+import org.apache.doris.nereids.trees.plans.physical.PhysicalResultSink;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalSetOperation;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalUnion;
 import org.apache.doris.nereids.trees.plans.visitor.PlanVisitor;
@@ -102,6 +103,12 @@ public class RequestPropertyDeriver extends PlanVisitor<Void, PlanContext> {
         return null;
     }
 
+    @Override
+    public Void visitPhysicalResultSink(PhysicalResultSink<? extends Plan> physicalResultSink, PlanContext context) {
+        addRequestPropertyToChildren(PhysicalProperties.GATHER);
+        return null;
+    }
+
     /* ********************************************************************************************
      * Other Node, in lexicographical order
      * ******************************************************************************************** */

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/RuleSet.java

@@ -62,6 +62,7 @@ import org.apache.doris.nereids.rules.implementation.LogicalOneRowRelationToPhys
 import org.apache.doris.nereids.rules.implementation.LogicalPartitionTopNToPhysicalPartitionTopN;
 import org.apache.doris.nereids.rules.implementation.LogicalProjectToPhysicalProject;
 import org.apache.doris.nereids.rules.implementation.LogicalRepeatToPhysicalRepeat;
+import org.apache.doris.nereids.rules.implementation.LogicalResultSinkToPhysicalResultSink;
 import org.apache.doris.nereids.rules.implementation.LogicalSchemaScanToPhysicalSchemaScan;
 import org.apache.doris.nereids.rules.implementation.LogicalSortToPhysicalQuickSort;
 import org.apache.doris.nereids.rules.implementation.LogicalTVFRelationToPhysicalTVFRelation;
@@ -161,6 +162,7 @@ public class RuleSet {
             .add(new LogicalGenerateToPhysicalGenerate())
             .add(new LogicalOlapTableSinkToPhysicalOlapTableSink())
             .add(new LogicalFileSinkToPhysicalFileSink())
+            .add(new LogicalResultSinkToPhysicalResultSink())
             .build();
 
     public static final List<Rule> ZIG_ZAG_TREE_JOIN_REORDER = planRuleFactories()

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/RuleType.java

@@ -29,6 +29,7 @@ public enum RuleType {
     // binding rules
 
     // **** make sure BINDING_UNBOUND_LOGICAL_PLAN is the lowest priority in the rewrite rules. ****
+    BINDING_RESULT_SINK(RuleTypeClass.REWRITE),
     BINDING_NON_LEAF_LOGICAL_PLAN(RuleTypeClass.REWRITE),
     BINDING_ONE_ROW_RELATION_SLOT(RuleTypeClass.REWRITE),
     BINDING_RELATION(RuleTypeClass.REWRITE),
@@ -299,6 +300,7 @@ public enum RuleType {
     LOGICAL_JDBC_SCAN_TO_PHYSICAL_JDBC_SCAN_RULE(RuleTypeClass.IMPLEMENTATION),
     LOGICAL_ES_SCAN_TO_PHYSICAL_ES_SCAN_RULE(RuleTypeClass.IMPLEMENTATION),
     LOGICAL_OLAP_TABLE_SINK_TO_PHYSICAL_OLAP_TABLE_SINK_RULE(RuleTypeClass.IMPLEMENTATION),
+    LOGICAL_RESULT_SINK_TO_PHYSICAL_RESULT_SINK_RULE(RuleTypeClass.IMPLEMENTATION),
     LOGICAL_FILE_SINK_TO_PHYSICAL_FILE_SINK_RULE(RuleTypeClass.IMPLEMENTATION),
     LOGICAL_ASSERT_NUM_ROWS_TO_PHYSICAL_ASSERT_NUM_ROWS(RuleTypeClass.IMPLEMENTATION),
     STORAGE_LAYER_AGGREGATE_WITHOUT_PROJECT(RuleTypeClass.IMPLEMENTATION),

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/analysis/BindExpression.java

@@ -65,6 +65,7 @@ import org.apache.doris.nereids.trees.plans.logical.LogicalJoin;
 import org.apache.doris.nereids.trees.plans.logical.LogicalOneRowRelation;
 import org.apache.doris.nereids.trees.plans.logical.LogicalProject;
 import org.apache.doris.nereids.trees.plans.logical.LogicalRepeat;
+import org.apache.doris.nereids.trees.plans.logical.LogicalResultSink;
 import org.apache.doris.nereids.trees.plans.logical.LogicalSetOperation;
 import org.apache.doris.nereids.trees.plans.logical.LogicalSort;
 import org.apache.doris.nereids.trees.plans.logical.LogicalSubQueryAlias;
@@ -555,6 +556,14 @@ public class BindExpression implements AnalysisRuleFactory {
                     checkSameNameSlot(subQueryAlias.child(0).getOutput(), subQueryAlias.getAlias());
                     return subQueryAlias;
                 })
+            ),
+            RuleType.BINDING_RESULT_SINK.build(
+                unboundResultSink().then(sink -> {
+                    List<NamedExpression> outputExprs = sink.child().getOutput().stream()
+                            .map(NamedExpression.class::cast)
+                            .collect(ImmutableList.toImmutableList());
+                    return new LogicalResultSink<>(outputExprs, sink.child());
+                })
             )
         ).stream().map(ruleCondition).collect(ImmutableList.toImmutableList());
     }

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/analysis/BindRelation.java

@@ -30,6 +30,7 @@ import org.apache.doris.nereids.CTEContext;
 import org.apache.doris.nereids.CascadesContext;
 import org.apache.doris.nereids.analyzer.Unbound;
 import org.apache.doris.nereids.analyzer.UnboundRelation;
+import org.apache.doris.nereids.analyzer.UnboundResultSink;
 import org.apache.doris.nereids.exceptions.AnalysisException;
 import org.apache.doris.nereids.parser.NereidsParser;
 import org.apache.doris.nereids.pattern.MatchingContext;
@@ -238,6 +239,10 @@ public class BindRelation extends OneAnalysisRuleFactory {
 
     private Plan parseAndAnalyzeView(String viewSql, CascadesContext parentContext) {
         LogicalPlan parsedViewPlan = new NereidsParser().parseSingle(viewSql);
+        // TODO: use a good to do this, such as eliminate UnboundResultSink
+        if (parsedViewPlan instanceof UnboundResultSink) {
+            parsedViewPlan = (LogicalPlan) ((UnboundResultSink<?>) parsedViewPlan).child();
+        }
         CascadesContext viewContext = CascadesContext.initContext(
                 parentContext.getStatementContext(), parsedViewPlan, PhysicalProperties.ANY);
         viewContext.newAnalyzer().analyze();

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/implementation/LogicalResultSinkToPhysicalResultSink.java

@@ -0,0 +1,43 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+package org.apache.doris.nereids.rules.implementation;
+
+import org.apache.doris.nereids.rules.Rule;
+import org.apache.doris.nereids.rules.RuleType;
+import org.apache.doris.nereids.trees.plans.Plan;
+import org.apache.doris.nereids.trees.plans.logical.LogicalResultSink;
+import org.apache.doris.nereids.trees.plans.physical.PhysicalResultSink;
+
+import java.util.Optional;
+
+/**
+ * implement result sink.
+ */
+public class LogicalResultSinkToPhysicalResultSink extends OneImplementationRuleFactory {
+    @Override
+    public Rule build() {
+        return logicalResultSink().thenApply(ctx -> {
+            LogicalResultSink<? extends Plan> sink = ctx.root;
+            return new PhysicalResultSink<>(
+                    sink.getOutputExprs(),
+                    Optional.empty(),
+                    sink.getLogicalProperties(),
+                    sink.child());
+        }).toRule(RuleType.LOGICAL_RESULT_SINK_TO_PHYSICAL_RESULT_SINK_RULE);
+    }
+}

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/rewrite/AddDefaultLimit.java

@@ -63,8 +63,7 @@ public class AddDefaultLimit extends DefaultPlanRewriter<StatementContext> imple
     // currently, it's one of the olap table sink and file sink.
     @Override
     public Plan visitLogicalSink(LogicalSink<? extends Plan> logicalSink, StatementContext context) {
-        Plan child = logicalSink.child().accept(this, context);
-        return logicalSink.withChildren(child);
+        return super.visit(logicalSink, context);
     }
 
     @Override

fe/fe-core/src/main/java/org/apache/doris/nereids/rules/rewrite/PullUpCteAnchor.java

@@ -21,7 +21,6 @@ import org.apache.doris.nereids.jobs.JobContext;
 import org.apache.doris.nereids.trees.plans.Plan;
 import org.apache.doris.nereids.trees.plans.logical.LogicalCTEAnchor;
 import org.apache.doris.nereids.trees.plans.logical.LogicalCTEProducer;
-import org.apache.doris.nereids.trees.plans.logical.LogicalSink;
 import org.apache.doris.nereids.trees.plans.visitor.CustomRewriter;
 import org.apache.doris.nereids.trees.plans.visitor.DefaultPlanRewriter;
 
@@ -72,11 +71,4 @@ public class PullUpCteAnchor extends DefaultPlanRewriter<List<LogicalCTEProducer
         producers.addAll(childProducers);
         return newProducer;
     }
-
-    // we should keep that sink node is the top node of the plan tree.
-    // currently, it's one of the olap table sink and file sink.
-    @Override
-    public Plan visitLogicalSink(LogicalSink<? extends Plan> logicalSink, List<LogicalCTEProducer<Plan>> producers) {
-        return logicalSink.withChildren(rewriteRoot(logicalSink.child(), producers));
-    }
 }

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/PlanType.java

@@ -21,94 +21,104 @@ package org.apache.doris.nereids.trees.plans;
  * Types for all Plan in Nereids.
  */
 public enum PlanType {
+    // special
+    GROUP_PLAN,
     UNKNOWN,
 
-    // logical plan
-    LOGICAL_OLAP_TABLE_SINK,
-    LOGICAL_CTE,
-    LOGICAL_WINDOW,
-    LOGICAL_SUBQUERY_ALIAS,
-    LOGICAL_UNBOUND_ONE_ROW_RELATION,
+    // logical plans
+    // logical relations
+    LOGICAL_BOUND_RELATION,
+    LOGICAL_CTE_CONSUMER,
+    LOGICAL_FILE_SCAN,
     LOGICAL_EMPTY_RELATION,
+    LOGICAL_ES_SCAN,
+    LOGICAL_JDBC_SCAN,
+    LOGICAL_OLAP_SCAN,
     LOGICAL_ONE_ROW_RELATION,
+    LOGICAL_SCHEMA_SCAN,
+    LOGICAL_TVF_RELATION,
+    LOGICAL_UNBOUND_ONE_ROW_RELATION,
     LOGICAL_UNBOUND_RELATION,
     LOGICAL_UNBOUND_TVF_RELATION,
-    LOGICAL_BOUND_RELATION,
+
+    // logical sinks
+    LOGICAL_FILE_SINK,
+    LOGICAL_OLAP_TABLE_SINK,
+    LOGICAL_RESULT_SINK,
     LOGICAL_UNBOUND_OLAP_TABLE_SINK,
-    LOGICAL_TVF_RELATION,
-    LOGICAL_PROJECT,
-    LOGICAL_FILTER,
-    LOGICAL_GENERATE,
-    LOGICAL_JOIN,
+    LOGICAL_UNBOUND_RESULT_SINK,
+
+    // logical others
     LOGICAL_AGGREGATE,
-    LOGICAL_REPEAT,
-    LOGICAL_SORT,
-    LOGICAL_TOP_N,
-    LOGICAL_PARTITION_TOP_N,
-    LOGICAL_LIMIT,
-    LOGICAL_OLAP_SCAN,
-    LOGICAL_SCHEMA_SCAN,
-    LOGICAL_FILE_SCAN,
-    LOGICAL_JDBC_SCAN,
-    LOGICAL_ES_SCAN,
     LOGICAL_APPLY,
-    LOGICAL_SELECT_HINT,
     LOGICAL_ASSERT_NUM_ROWS,
-    LOGICAL_HAVING,
-    LOGICAL_MULTI_JOIN,
     LOGICAL_CHECK_POLICY,
-    LOGICAL_UNION,
-    LOGICAL_EXCEPT,
-    LOGICAL_INTERSECT,
-    LOGICAL_USING_JOIN,
-    LOGICAL_CTE_RELATION,
+    LOGICAL_CTE,
     LOGICAL_CTE_ANCHOR,
     LOGICAL_CTE_PRODUCER,
-    LOGICAL_CTE_CONSUMER,
-    LOGICAL_FILE_SINK,
+    LOGICAL_EXCEPT,
+    LOGICAL_FILTER,
+    LOGICAL_GENERATE,
+    LOGICAL_HAVING,
+    LOGICAL_INTERSECT,
+    LOGICAL_JOIN,
+    LOGICAL_LIMIT,
+    LOGICAL_MULTI_JOIN,
+    LOGICAL_PARTITION_TOP_N,
+    LOGICAL_PROJECT,
+    LOGICAL_REPEAT,
+    LOGICAL_SELECT_HINT,
+    LOGICAL_SUBQUERY_ALIAS,
+    LOGICAL_SORT,
+    LOGICAL_TOP_N,
+    LOGICAL_UNION,
+    LOGICAL_USING_JOIN,
+    LOGICAL_WINDOW,
 
-    GROUP_PLAN,
-
-    // physical plan
-    PHYSICAL_OLAP_TABLE_SINK,
-    PHYSICAL_CTE_PRODUCE,
-    PHYSICAL_CTE_CONSUME,
-    PHYSICAL_CTE_ANCHOR,
-    PHYSICAL_WINDOW,
+    // physical plans
+    // logical relations
+    PHYSICAL_CTE_CONSUMER,
     PHYSICAL_EMPTY_RELATION,
-    PHYSICAL_ONE_ROW_RELATION,
-    PHYSICAL_OLAP_SCAN,
+    PHYSICAL_ES_SCAN,
     PHYSICAL_FILE_SCAN,
     PHYSICAL_JDBC_SCAN,
-    PHYSICAL_ES_SCAN,
-    PHYSICAL_TVF_RELATION,
+    PHYSICAL_ONE_ROW_RELATION,
+    PHYSICAL_OLAP_SCAN,
     PHYSICAL_SCHEMA_SCAN,
-    PHYSICAL_PROJECT,
+    PHYSICAL_TVF_RELATION,
+
+    // logical sinks
+    PHYSICAL_FILE_SINK,
+    PHYSICAL_OLAP_TABLE_SINK,
+    PHYSICAL_RESULT_SINK,
+
+    // logical others
+    PHYSICAL_HASH_AGGREGATE,
+    PHYSICAL_ASSERT_NUM_ROWS,
+    PHYSICAL_CTE_PRODUCER,
+    PHYSICAL_CTE_ANCHOR,
+    PHYSICAL_DISTRIBUTE,
+    PHYSICAL_EXCEPT,
     PHYSICAL_FILTER,
     PHYSICAL_GENERATE,
-    PHYSICAL_BROADCAST_HASH_JOIN,
-    PHYSICAL_AGGREGATE,
-    PHYSICAL_REPEAT,
-    PHYSICAL_QUICK_SORT,
-    PHYSICAL_TOP_N,
-    PHYSICAL_PARTITION_TOP_N,
-    PHYSICAL_LOCAL_QUICK_SORT,
-    PHYSICAL_LIMIT,
+    PHYSICAL_INTERSECT,
     PHYSICAL_HASH_JOIN,
     PHYSICAL_NESTED_LOOP_JOIN,
-    PHYSICAL_EXCHANGE,
-    PHYSICAL_DISTRIBUTION,
-    PHYSICAL_ASSERT_NUM_ROWS,
+    PHYSICAL_LIMIT,
+    PHYSICAL_PARTITION_TOP_N,
+    PHYSICAL_PROJECT,
+    PHYSICAL_REPEAT,
+    PHYSICAL_LOCAL_QUICK_SORT,
+    PHYSICAL_QUICK_SORT,
+    PHYSICAL_TOP_N,
     PHYSICAL_UNION,
-    PHYSICAL_EXCEPT,
-    PHYSICAL_INTERSECT,
-    PHYSICAL_FILE_SINK,
+    PHYSICAL_WINDOW,
 
-    COMMAND,
-    EXPLAIN_COMMAND,
+    // commands
     CREATE_POLICY_COMMAND,
-    INSERT_INTO_TABLE_COMMAND,
-    UPDATE_COMMAND,
     DELETE_COMMAND,
-    SELECT_INTO_OUTFILE_COMMAND
+    EXPLAIN_COMMAND,
+    INSERT_INTO_TABLE_COMMAND,
+    SELECT_INTO_OUTFILE_COMMAND,
+    UPDATE_COMMAND
 }

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/logical/LogicalCTEConsumer.java

@@ -52,7 +52,7 @@ public class LogicalCTEConsumer extends LogicalRelation {
      */
     public LogicalCTEConsumer(RelationId relationId, CTEId cteId, String name,
             Map<Slot, Slot> consumerToProducerOutputMap, Map<Slot, Slot> producerToConsumerOutputMap) {
-        super(relationId, PlanType.LOGICAL_CTE_RELATION, Optional.empty(), Optional.empty());
+        super(relationId, PlanType.LOGICAL_CTE_CONSUMER, Optional.empty(), Optional.empty());
         this.cteId = Objects.requireNonNull(cteId, "cteId should not null");
         this.name = Objects.requireNonNull(name, "name should not null");
         this.consumerToProducerOutputMap = Objects.requireNonNull(consumerToProducerOutputMap,
@@ -65,7 +65,7 @@ public class LogicalCTEConsumer extends LogicalRelation {
      * Logical CTE consumer.
      */
     public LogicalCTEConsumer(RelationId relationId, CTEId cteId, String name, LogicalPlan producerPlan) {
-        super(relationId, PlanType.LOGICAL_CTE_RELATION, Optional.empty(), Optional.empty());
+        super(relationId, PlanType.LOGICAL_CTE_CONSUMER, Optional.empty(), Optional.empty());
         this.cteId = Objects.requireNonNull(cteId, "cteId should not null");
         this.name = Objects.requireNonNull(name, "name should not null");
         this.consumerToProducerOutputMap = new LinkedHashMap<>();
@@ -79,7 +79,7 @@ public class LogicalCTEConsumer extends LogicalRelation {
     public LogicalCTEConsumer(RelationId relationId, CTEId cteId, String name,
             Map<Slot, Slot> consumerToProducerOutputMap, Map<Slot, Slot> producerToConsumerOutputMap,
             Optional<GroupExpression> groupExpression, Optional<LogicalProperties> logicalProperties) {
-        super(relationId, PlanType.LOGICAL_CTE_RELATION, groupExpression, logicalProperties);
+        super(relationId, PlanType.LOGICAL_CTE_CONSUMER, groupExpression, logicalProperties);
         this.cteId = Objects.requireNonNull(cteId, "cteId should not null");
         this.name = Objects.requireNonNull(name, "name should not null");
         this.consumerToProducerOutputMap = Objects.requireNonNull(consumerToProducerOutputMap,

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/logical/LogicalResultSink.java

@@ -0,0 +1,122 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+package org.apache.doris.nereids.trees.plans.logical;
+
+import org.apache.doris.nereids.memo.GroupExpression;
+import org.apache.doris.nereids.properties.LogicalProperties;
+import org.apache.doris.nereids.trees.expressions.Expression;
+import org.apache.doris.nereids.trees.expressions.NamedExpression;
+import org.apache.doris.nereids.trees.expressions.Slot;
+import org.apache.doris.nereids.trees.plans.Plan;
+import org.apache.doris.nereids.trees.plans.PlanType;
+import org.apache.doris.nereids.trees.plans.algebra.Sink;
+import org.apache.doris.nereids.trees.plans.visitor.PlanVisitor;
+import org.apache.doris.nereids.util.Utils;
+
+import com.google.common.base.Preconditions;
+import com.google.common.collect.ImmutableList;
+
+import java.util.List;
+import java.util.Objects;
+import java.util.Optional;
+
+/**
+ * result sink
+ */
+public class LogicalResultSink<CHILD_TYPE extends Plan> extends LogicalSink<CHILD_TYPE> implements Sink {
+
+    private final List<NamedExpression> outputExprs;
+
+    public LogicalResultSink(List<NamedExpression> outputExprs, CHILD_TYPE child) {
+        super(PlanType.LOGICAL_RESULT_SINK, child);
+        this.outputExprs = outputExprs;
+    }
+
+    public LogicalResultSink(List<NamedExpression> outputExprs,
+            Optional<GroupExpression> groupExpression,
+            Optional<LogicalProperties> logicalProperties, CHILD_TYPE child) {
+        super(PlanType.LOGICAL_RESULT_SINK, groupExpression, logicalProperties, child);
+        this.outputExprs = outputExprs;
+    }
+
+    public List<NamedExpression> getOutputExprs() {
+        return outputExprs;
+    }
+
+    @Override
+    public Plan withChildren(List<Plan> children) {
+        Preconditions.checkArgument(children.size() == 1,
+                "LogicalResultSink's children size must be 1, but real is %s", children.size());
+        return new LogicalResultSink<>(outputExprs, children.get(0));
+    }
+
+    @Override
+    public <R, C> R accept(PlanVisitor<R, C> visitor, C context) {
+        return visitor.visitLogicalResultSink(this, context);
+    }
+
+    @Override
+    public List<? extends Expression> getExpressions() {
+        return outputExprs;
+    }
+
+    @Override
+    public Plan withGroupExpression(Optional<GroupExpression> groupExpression) {
+        return new LogicalResultSink<>(outputExprs, groupExpression, Optional.of(getLogicalProperties()), child());
+    }
+
+    @Override
+    public Plan withGroupExprLogicalPropChildren(Optional<GroupExpression> groupExpression,
+            Optional<LogicalProperties> logicalProperties, List<Plan> children) {
+        Preconditions.checkArgument(children.size() == 1, "UnboundResultSink only accepts one child");
+        return new LogicalResultSink<>(outputExprs, groupExpression, logicalProperties, children.get(0));
+    }
+
+    @Override
+    public List<Slot> computeOutput() {
+        return outputExprs.stream()
+                .map(NamedExpression::toSlot)
+                .collect(ImmutableList.toImmutableList());
+    }
+
+    @Override
+    public String toString() {
+        return Utils.toSqlString("LogicalResultSink[" + id.asInt() + "]",
+                "outputExprs", outputExprs);
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (this == o) {
+            return true;
+        }
+        if (o == null || getClass() != o.getClass()) {
+            return false;
+        }
+        if (!super.equals(o)) {
+            return false;
+        }
+        LogicalResultSink<?> that = (LogicalResultSink<?>) o;
+        return Objects.equals(outputExprs, that.outputExprs);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(super.hashCode(), outputExprs);
+    }
+}

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/physical/PhysicalCTEConsumer.java

@@ -76,7 +76,7 @@ public class PhysicalCTEConsumer extends PhysicalRelation {
     public PhysicalCTEConsumer(RelationId relationId, CTEId cteId, Map<Slot, Slot> consumerToProducerSlotMap,
             Map<Slot, Slot> producerToConsumerSlotMap, Optional<GroupExpression> groupExpression,
             LogicalProperties logicalProperties, PhysicalProperties physicalProperties, Statistics statistics) {
-        super(relationId, PlanType.PHYSICAL_CTE_CONSUME, groupExpression,
+        super(relationId, PlanType.PHYSICAL_CTE_CONSUMER, groupExpression,
                 logicalProperties, physicalProperties, statistics);
         this.cteId = cteId;
         this.consumerToProducerSlotMap = ImmutableMap.copyOf(Objects.requireNonNull(

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/physical/PhysicalCTEProducer.java

@@ -54,7 +54,8 @@ public class PhysicalCTEProducer<CHILD_TYPE extends Plan> extends PhysicalUnary<
     public PhysicalCTEProducer(CTEId cteId, Optional<GroupExpression> groupExpression,
             LogicalProperties logicalProperties, PhysicalProperties physicalProperties,
             Statistics statistics, CHILD_TYPE child) {
-        super(PlanType.PHYSICAL_CTE_PRODUCE, groupExpression, logicalProperties, physicalProperties, statistics, child);
+        super(PlanType.PHYSICAL_CTE_PRODUCER, groupExpression,
+                logicalProperties, physicalProperties, statistics, child);
         this.cteId = cteId;
     }
 

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/physical/PhysicalDistribute.java

@@ -58,14 +58,14 @@ public class PhysicalDistribute<CHILD_TYPE extends Plan> extends PhysicalUnary<C
 
     public PhysicalDistribute(DistributionSpec spec, Optional<GroupExpression> groupExpression,
             LogicalProperties logicalProperties, CHILD_TYPE child) {
-        super(PlanType.PHYSICAL_DISTRIBUTION, groupExpression, logicalProperties, child);
+        super(PlanType.PHYSICAL_DISTRIBUTE, groupExpression, logicalProperties, child);
         this.distributionSpec = spec;
     }
 
     public PhysicalDistribute(DistributionSpec spec, Optional<GroupExpression> groupExpression,
             LogicalProperties logicalProperties, PhysicalProperties physicalProperties,
             Statistics statistics, CHILD_TYPE child) {
-        super(PlanType.PHYSICAL_DISTRIBUTION, groupExpression, logicalProperties, physicalProperties, statistics,
+        super(PlanType.PHYSICAL_DISTRIBUTE, groupExpression, logicalProperties, physicalProperties, statistics,
                 child);
         this.distributionSpec = spec;
     }

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/physical/PhysicalHashAggregate.java

@@ -96,7 +96,7 @@ public class PhysicalHashAggregate<CHILD_TYPE extends Plan> extends PhysicalUnar
             Optional<List<Expression>> partitionExpressions, AggregateParam aggregateParam, boolean maybeUsingStream,
             Optional<GroupExpression> groupExpression, LogicalProperties logicalProperties,
             RequireProperties requireProperties, CHILD_TYPE child) {
-        super(PlanType.PHYSICAL_AGGREGATE, groupExpression, logicalProperties, child);
+        super(PlanType.PHYSICAL_HASH_AGGREGATE, groupExpression, logicalProperties, child);
         this.groupByExpressions = ImmutableList.copyOf(
                 Objects.requireNonNull(groupByExpressions, "groupByExpressions cannot be null"));
         this.outputExpressions = ImmutableList.copyOf(
@@ -122,7 +122,7 @@ public class PhysicalHashAggregate<CHILD_TYPE extends Plan> extends PhysicalUnar
             Optional<GroupExpression> groupExpression, LogicalProperties logicalProperties,
             RequireProperties requireProperties, PhysicalProperties physicalProperties,
             Statistics statistics, CHILD_TYPE child) {
-        super(PlanType.PHYSICAL_AGGREGATE, groupExpression, logicalProperties, physicalProperties, statistics,
+        super(PlanType.PHYSICAL_HASH_AGGREGATE, groupExpression, logicalProperties, physicalProperties, statistics,
                 child);
         this.groupByExpressions = ImmutableList.copyOf(
                 Objects.requireNonNull(groupByExpressions, "groupByExpressions cannot be null"));

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/physical/PhysicalResultSink.java

@@ -0,0 +1,125 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+package org.apache.doris.nereids.trees.plans.physical;
+
+import org.apache.doris.nereids.memo.GroupExpression;
+import org.apache.doris.nereids.properties.LogicalProperties;
+import org.apache.doris.nereids.properties.PhysicalProperties;
+import org.apache.doris.nereids.trees.expressions.Expression;
+import org.apache.doris.nereids.trees.expressions.NamedExpression;
+import org.apache.doris.nereids.trees.plans.Plan;
+import org.apache.doris.nereids.trees.plans.PlanType;
+import org.apache.doris.nereids.trees.plans.algebra.Sink;
+import org.apache.doris.nereids.trees.plans.visitor.PlanVisitor;
+import org.apache.doris.nereids.util.Utils;
+import org.apache.doris.statistics.Statistics;
+
+import com.google.common.base.Preconditions;
+import org.jetbrains.annotations.Nullable;
+
+import java.util.List;
+import java.util.Objects;
+import java.util.Optional;
+
+/**
+ * result sink
+ */
+public class PhysicalResultSink<CHILD_TYPE extends Plan> extends PhysicalSink<CHILD_TYPE> implements Sink {
+
+    private final List<NamedExpression> outputExprs;
+
+    public PhysicalResultSink(List<NamedExpression> outputExprs, LogicalProperties logicalProperties,
+            CHILD_TYPE child) {
+        super(PlanType.PHYSICAL_RESULT_SINK, logicalProperties, child);
+        this.outputExprs = outputExprs;
+    }
+
+    public PhysicalResultSink(List<NamedExpression> outputExprs, Optional<GroupExpression> groupExpression,
+            LogicalProperties logicalProperties, CHILD_TYPE child) {
+        super(PlanType.PHYSICAL_RESULT_SINK, groupExpression, logicalProperties, child);
+        this.outputExprs = outputExprs;
+    }
+
+    public PhysicalResultSink(List<NamedExpression> outputExprs, Optional<GroupExpression> groupExpression,
+            LogicalProperties logicalProperties, @Nullable PhysicalProperties physicalProperties,
+            Statistics statistics, CHILD_TYPE child) {
+        super(PlanType.PHYSICAL_RESULT_SINK, groupExpression, logicalProperties, physicalProperties, statistics, child);
+        this.outputExprs = outputExprs;
+    }
+
+    @Override
+    public PhysicalResultSink<Plan> withChildren(List<Plan> children) {
+        Preconditions.checkArgument(children.size() == 1,
+                "PhysicalResultSink's children size must be 1, but real is %s", children.size());
+        return new PhysicalResultSink<>(outputExprs, groupExpression, getLogicalProperties(), children.get(0));
+    }
+
+    @Override
+    public <R, C> R accept(PlanVisitor<R, C> visitor, C context) {
+        return visitor.visitPhysicalResultSink(this, context);
+    }
+
+    @Override
+    public List<? extends Expression> getExpressions() {
+        return outputExprs;
+    }
+
+    @Override
+    public PhysicalResultSink<Plan> withGroupExpression(Optional<GroupExpression> groupExpression) {
+        return new PhysicalResultSink<>(outputExprs, groupExpression, getLogicalProperties(), child());
+    }
+
+    @Override
+    public PhysicalResultSink<Plan> withGroupExprLogicalPropChildren(Optional<GroupExpression> groupExpression,
+            Optional<LogicalProperties> logicalProperties, List<Plan> children) {
+        return new PhysicalResultSink<>(outputExprs, groupExpression, logicalProperties.get(), child());
+    }
+
+    @Override
+    public PhysicalResultSink<Plan> withPhysicalPropertiesAndStats(
+            PhysicalProperties physicalProperties, Statistics statistics) {
+        return new PhysicalResultSink<>(outputExprs, groupExpression,
+                getLogicalProperties(), physicalProperties, statistics, child());
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (this == o) {
+            return true;
+        }
+        if (o == null || getClass() != o.getClass()) {
+            return false;
+        }
+        if (!super.equals(o)) {
+            return false;
+        }
+        PhysicalResultSink<?> that = (PhysicalResultSink<?>) o;
+        return Objects.equals(outputExprs, that.outputExprs);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(super.hashCode(), outputExprs);
+    }
+
+    @Override
+    public String toString() {
+        return Utils.toSqlString("PhysicalResultSink[" + id.asInt() + "]",
+                "outputExprs", outputExprs);
+    }
+}

fe/fe-core/src/main/java/org/apache/doris/nereids/trees/plans/visitor/SinkVisitor.java

@@ -18,12 +18,15 @@
 package org.apache.doris.nereids.trees.plans.visitor;
 
 import org.apache.doris.nereids.analyzer.UnboundOlapTableSink;
+import org.apache.doris.nereids.analyzer.UnboundResultSink;
 import org.apache.doris.nereids.trees.plans.Plan;
 import org.apache.doris.nereids.trees.plans.logical.LogicalFileSink;
 import org.apache.doris.nereids.trees.plans.logical.LogicalOlapTableSink;
+import org.apache.doris.nereids.trees.plans.logical.LogicalResultSink;
 import org.apache.doris.nereids.trees.plans.logical.LogicalSink;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalFileSink;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalOlapTableSink;
+import org.apache.doris.nereids.trees.plans.physical.PhysicalResultSink;
 import org.apache.doris.nereids.trees.plans.physical.PhysicalSink;
 
 /**
@@ -47,6 +50,10 @@ public interface SinkVisitor<R, C> {
         return visitLogicalSink(unboundOlapTableSink, context);
     }
 
+    default R visitUnboundResultSink(UnboundResultSink<? extends Plan> unboundResultSink, C context) {
+        return visitLogicalSink(unboundResultSink, context);
+    }
+
     // *******************************
     // logical
     // *******************************
@@ -59,6 +66,10 @@ public interface SinkVisitor<R, C> {
         return visitLogicalSink(olapTableSink, context);
     }
 
+    default R visitLogicalResultSink(LogicalResultSink<? extends Plan> logicalResultSink, C context) {
+        return visitLogicalSink(logicalResultSink, context);
+    }
+
     // *******************************
     // physical
     // *******************************
@@ -70,4 +81,8 @@ public interface SinkVisitor<R, C> {
     default R visitPhysicalOlapTableSink(PhysicalOlapTableSink<? extends Plan> olapTableSink, C context) {
         return visitPhysicalSink(olapTableSink, context);
     }
+
+    default R visitPhysicalResultSink(PhysicalResultSink<? extends Plan> physicalResultSink, C context) {
+        return visitPhysicalSink(physicalResultSink, context);
+    }
 }

fe/fe-core/src/test/java/org/apache/doris/nereids/JoinHintTest.java

@@ -114,22 +114,23 @@ class JoinHintTest extends TestWithFeService implements MemoPatternMatchSupporte
         PlanChecker.from(connectContext).checkExplain(sql, planner -> {
             Plan plan = planner.getOptimizedPlan();
             MatchingUtils.assertMatches(plan,
-                    physicalDistribute(
-                            physicalProject(
-                                    physicalHashJoin(
-                                            physicalHashJoin(physicalDistribute().when(dis -> {
-                                                DistributionSpec spec = dis.getDistributionSpec();
-                                                Assertions.assertTrue(spec instanceof DistributionSpecHash);
-                                                DistributionSpecHash hashSpec = (DistributionSpecHash) spec;
-                                                Assertions.assertEquals(ShuffleType.EXECUTION_BUCKETED,
-                                                        hashSpec.getShuffleType());
-                                                return true;
-                                            }), physicalDistribute()),
-                                            physicalDistribute()
-                                    ).when(join -> join.getHint() == JoinHint.SHUFFLE_RIGHT)
+                    physicalResultSink(
+                            physicalDistribute(
+                                    physicalProject(
+                                            physicalHashJoin(
+                                                    physicalHashJoin(physicalDistribute().when(dis -> {
+                                                        DistributionSpec spec = dis.getDistributionSpec();
+                                                        Assertions.assertTrue(spec instanceof DistributionSpecHash);
+                                                        DistributionSpecHash hashSpec = (DistributionSpecHash) spec;
+                                                        Assertions.assertEquals(ShuffleType.EXECUTION_BUCKETED,
+                                                                hashSpec.getShuffleType());
+                                                        return true;
+                                                    }), physicalDistribute()),
+                                                    physicalDistribute()
+                                            ).when(join -> join.getHint() == JoinHint.SHUFFLE_RIGHT)
+                                    )
                             )
-                    )
-            );
+                    ));
         });
     }
 

fe/fe-core/src/test/java/org/apache/doris/nereids/parser/LimitClauseTest.java

@@ -23,24 +23,24 @@ public class LimitClauseTest extends ParserTestBase {
     @Test
     public void testLimit() {
         parsePlan("SELECT b FROM test order by a limit 3 offset 100")
-                .matchesFromRoot(
+                .matches(
                         logicalLimit(
                                 logicalSort()
                         ).when(limit -> limit.getLimit() == 3 && limit.getOffset() == 100)
                 );
 
         parsePlan("SELECT b FROM test order by a limit 100, 3")
-                .matchesFromRoot(
+                .matches(
                         logicalLimit(
                                 logicalSort()
                         ).when(limit -> limit.getLimit() == 3 && limit.getOffset() == 100)
                 );
 
         parsePlan("SELECT b FROM test limit 3")
-                .matchesFromRoot(logicalLimit().when(limit -> limit.getLimit() == 3 && limit.getOffset() == 0));
+                .matches(logicalLimit().when(limit -> limit.getLimit() == 3 && limit.getOffset() == 0));
 
         parsePlan("SELECT b FROM test order by a limit 3")
-                .matchesFromRoot(
+                .matches(
                         logicalLimit(
                                 logicalSort()
                         ).when(limit -> limit.getLimit() == 3 && limit.getOffset() == 0)
@@ -49,13 +49,13 @@ public class LimitClauseTest extends ParserTestBase {
 
     @Test
     public void testNoLimit() {
-        parsePlan("select a from tbl order by x").matchesFromRoot(logicalSort());
+        parsePlan("select a from tbl order by x").matches(logicalSort());
     }
 
     @Test
     public void testNoQueryOrganization() {
         parsePlan("select a from tbl")
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalCheckPolicy(
                                         unboundRelation()

fe/fe-core/src/test/java/org/apache/doris/nereids/parser/NereidsParserTest.java

@@ -80,7 +80,7 @@ public class NereidsParserTest extends ParserTestBase {
     @Test
     public void testPostProcessor() {
         parsePlan("select `AD``D` from t1 where a = 1")
-                .matchesFromRoot(
+                .matches(
                         logicalProject().when(p -> "AD`D".equals(p.getProjects().get(0).getName()))
                 );
     }
@@ -90,17 +90,17 @@ public class NereidsParserTest extends ParserTestBase {
         NereidsParser nereidsParser = new NereidsParser();
         LogicalPlan logicalPlan;
         String cteSql1 = "with t1 as (select s_suppkey from supplier where s_suppkey < 10) select * from t1";
-        logicalPlan = nereidsParser.parseSingle(cteSql1);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(cteSql1).child(0);
         Assertions.assertEquals(PlanType.LOGICAL_CTE, logicalPlan.getType());
         Assertions.assertEquals(((LogicalCTE<?>) logicalPlan).getAliasQueries().size(), 1);
 
         String cteSql2 = "with t1 as (select s_suppkey from supplier), t2 as (select s_suppkey from t1) select * from t2";
-        logicalPlan = nereidsParser.parseSingle(cteSql2);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(cteSql2).child(0);
         Assertions.assertEquals(PlanType.LOGICAL_CTE, logicalPlan.getType());
         Assertions.assertEquals(((LogicalCTE<?>) logicalPlan).getAliasQueries().size(), 2);
 
         String cteSql3 = "with t1 (key, name) as (select s_suppkey, s_name from supplier) select * from t1";
-        logicalPlan = nereidsParser.parseSingle(cteSql3);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(cteSql3).child(0);
         Assertions.assertEquals(PlanType.LOGICAL_CTE, logicalPlan.getType());
         Assertions.assertEquals(((LogicalCTE<?>) logicalPlan).getAliasQueries().size(), 1);
         Optional<List<String>> columnAliases = ((LogicalCTE<?>) logicalPlan).getAliasQueries().get(0).getColumnAliases();
@@ -112,12 +112,12 @@ public class NereidsParserTest extends ParserTestBase {
         NereidsParser nereidsParser = new NereidsParser();
         LogicalPlan logicalPlan;
         String windowSql1 = "select k1, rank() over(partition by k1 order by k1) as ranking from t1";
-        logicalPlan = nereidsParser.parseSingle(windowSql1);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(windowSql1).child(0);
         Assertions.assertEquals(PlanType.LOGICAL_PROJECT, logicalPlan.getType());
         Assertions.assertEquals(((LogicalProject<?>) logicalPlan).getProjects().size(), 2);
 
         String windowSql2 = "select k1, sum(k2), rank() over(partition by k1 order by k1) as ranking from t1 group by k1";
-        logicalPlan = nereidsParser.parseSingle(windowSql2);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(windowSql2).child(0);
         Assertions.assertEquals(PlanType.LOGICAL_AGGREGATE, logicalPlan.getType());
         Assertions.assertEquals(((LogicalAggregate<?>) logicalPlan).getOutputExpressions().size(), 3);
 
@@ -135,7 +135,7 @@ public class NereidsParserTest extends ParserTestBase {
         ExplainCommand explainCommand = (ExplainCommand) logicalPlan;
         ExplainLevel explainLevel = explainCommand.getLevel();
         Assertions.assertEquals(ExplainLevel.NORMAL, explainLevel);
-        logicalPlan = explainCommand.getLogicalPlan();
+        logicalPlan = (LogicalPlan) explainCommand.getLogicalPlan().child(0);
         LogicalProject<Plan> logicalProject = (LogicalProject) logicalPlan;
         Assertions.assertEquals("AD`D", logicalProject.getProjects().get(0).getName());
     }
@@ -168,7 +168,7 @@ public class NereidsParserTest extends ParserTestBase {
         Assertions.assertEquals(2, statementBases.size());
         Assertions.assertTrue(statementBases.get(0) instanceof LogicalPlanAdapter);
         Assertions.assertTrue(statementBases.get(1) instanceof LogicalPlanAdapter);
-        LogicalPlan logicalPlan0 = ((LogicalPlanAdapter) statementBases.get(0)).getLogicalPlan();
+        LogicalPlan logicalPlan0 = (LogicalPlan) ((LogicalPlanAdapter) statementBases.get(0)).getLogicalPlan().child(0);
         LogicalPlan logicalPlan1 = ((LogicalPlanAdapter) statementBases.get(1)).getLogicalPlan();
         Assertions.assertTrue(logicalPlan0 instanceof LogicalProject);
         Assertions.assertTrue(logicalPlan1 instanceof ExplainCommand);
@@ -181,57 +181,57 @@ public class NereidsParserTest extends ParserTestBase {
         LogicalJoin logicalJoin;
 
         String innerJoin1 = "SELECT t1.a FROM t1 INNER JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(innerJoin1);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(innerJoin1).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.INNER_JOIN, logicalJoin.getJoinType());
 
         String innerJoin2 = "SELECT t1.a FROM t1 JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(innerJoin2);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(innerJoin2).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.INNER_JOIN, logicalJoin.getJoinType());
 
         String leftJoin1 = "SELECT t1.a FROM t1 LEFT JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(leftJoin1);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(leftJoin1).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.LEFT_OUTER_JOIN, logicalJoin.getJoinType());
 
         String leftJoin2 = "SELECT t1.a FROM t1 LEFT OUTER JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(leftJoin2);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(leftJoin2).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.LEFT_OUTER_JOIN, logicalJoin.getJoinType());
 
         String rightJoin1 = "SELECT t1.a FROM t1 RIGHT JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(rightJoin1);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(rightJoin1).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.RIGHT_OUTER_JOIN, logicalJoin.getJoinType());
 
         String rightJoin2 = "SELECT t1.a FROM t1 RIGHT OUTER JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(rightJoin2);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(rightJoin2).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.RIGHT_OUTER_JOIN, logicalJoin.getJoinType());
 
         String leftSemiJoin = "SELECT t1.a FROM t1 LEFT SEMI JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(leftSemiJoin);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(leftSemiJoin).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.LEFT_SEMI_JOIN, logicalJoin.getJoinType());
 
         String rightSemiJoin = "SELECT t2.a FROM t1 RIGHT SEMI JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(rightSemiJoin);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(rightSemiJoin).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.RIGHT_SEMI_JOIN, logicalJoin.getJoinType());
 
         String leftAntiJoin = "SELECT t1.a FROM t1 LEFT ANTI JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(leftAntiJoin);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(leftAntiJoin).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.LEFT_ANTI_JOIN, logicalJoin.getJoinType());
 
         String righAntiJoin = "SELECT t2.a FROM t1 RIGHT ANTI JOIN t2 ON t1.id = t2.id;";
-        logicalPlan = nereidsParser.parseSingle(righAntiJoin);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(righAntiJoin).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.RIGHT_ANTI_JOIN, logicalJoin.getJoinType());
 
         String crossJoin = "SELECT t1.a FROM t1 CROSS JOIN t2;";
-        logicalPlan = nereidsParser.parseSingle(crossJoin);
+        logicalPlan = (LogicalPlan) nereidsParser.parseSingle(crossJoin).child(0);
         logicalJoin = (LogicalJoin) logicalPlan.child(0);
         Assertions.assertEquals(JoinType.CROSS_JOIN, logicalJoin.getJoinType());
     }
@@ -252,7 +252,7 @@ public class NereidsParserTest extends ParserTestBase {
     public void testParseDecimal() {
         String f1 = "SELECT col1 * 0.267081789095306 FROM t";
         NereidsParser nereidsParser = new NereidsParser();
-        LogicalPlan logicalPlan = nereidsParser.parseSingle(f1);
+        LogicalPlan logicalPlan = (LogicalPlan) nereidsParser.parseSingle(f1).child(0);
         long doubleCount = logicalPlan
                 .getExpressions()
                 .stream()
@@ -334,7 +334,7 @@ public class NereidsParserTest extends ParserTestBase {
     public void testParseCast() {
         String sql = "SELECT CAST(1 AS DECIMAL(20, 6)) FROM t";
         NereidsParser nereidsParser = new NereidsParser();
-        LogicalPlan logicalPlan = nereidsParser.parseSingle(sql);
+        LogicalPlan logicalPlan = (LogicalPlan) nereidsParser.parseSingle(sql).child(0);
         Cast cast = (Cast) logicalPlan.getExpressions().get(0).child(0);
         if (Config.enable_decimal_conversion) {
             DecimalV3Type decimalV3Type = (DecimalV3Type) cast.getDataType();

fe/fe-core/src/test/java/org/apache/doris/nereids/postprocess/TopNRuntimeFilterTest.java

@@ -40,8 +40,8 @@ public class TopNRuntimeFilterTest extends SSBTestBase {
                 .implement();
         PhysicalPlan plan = checker.getPhysicalPlan();
         new PlanPostProcessors(checker.getCascadesContext()).process(plan);
-        Assertions.assertTrue(plan.children().get(0) instanceof PhysicalTopN);
-        PhysicalTopN localTopN = (PhysicalTopN) plan.children().get(0);
+        Assertions.assertTrue(plan.children().get(0).child(0) instanceof PhysicalTopN);
+        PhysicalTopN localTopN = (PhysicalTopN) plan.children().get(0).child(0);
         Assertions.assertTrue(localTopN.getMutableState(PhysicalTopN.TOPN_RUNTIME_FILTER).isPresent());
     }
 

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/AnalyzeCTETest.java

@@ -153,7 +153,7 @@ public class AnalyzeCTETest extends TestWithFeService implements MemoPatternMatc
     public void testCTEWithAlias() {
         PlanChecker.from(connectContext)
                 .analyze(cteConsumerJoin)
-                .matchesFromRoot(
+                .matches(
                         logicalCTEAnchor(
                                 logicalCTEProducer(),
                                 logicalCTEAnchor(
@@ -173,7 +173,7 @@ public class AnalyzeCTETest extends TestWithFeService implements MemoPatternMatc
     public void testCTEWithAnExistedTableOrViewName() {
         PlanChecker.from(connectContext)
                 .analyze(cteReferToAnotherOne)
-                .matchesFromRoot(
+                .matches(
                         logicalCTEAnchor(
                                 logicalCTEProducer(),
                                 logicalCTEAnchor(
@@ -191,7 +191,7 @@ public class AnalyzeCTETest extends TestWithFeService implements MemoPatternMatc
     public void testDifferenceRelationId() {
         PlanChecker.from(connectContext)
                 .analyze(cteWithDiffRelationId)
-                .matchesFromRoot(
+                .matches(
                         logicalCTEAnchor(
                                 logicalCTEProducer(),
                                 logicalProject(
@@ -212,7 +212,7 @@ public class AnalyzeCTETest extends TestWithFeService implements MemoPatternMatc
     public void testCteInTheMiddle() {
         PlanChecker.from(connectContext)
                 .analyze(cteInTheMiddle)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSubQueryAlias(
                                         logicalCTEAnchor(
@@ -231,7 +231,7 @@ public class AnalyzeCTETest extends TestWithFeService implements MemoPatternMatc
     public void testCteNested() {
         PlanChecker.from(connectContext)
                 .analyze(cteNested)
-                .matchesFromRoot(
+                .matches(
                         logicalCTEAnchor(
                                 logicalCTEProducer(
                                         logicalSubQueryAlias(

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/AnalyzeSubQueryTest.java

@@ -105,7 +105,7 @@ public class AnalyzeSubQueryTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(testSql.get(0))
                 .applyTopDown(new LogicalSubQueryAliasToLogicalProject())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalProject(
                             logicalProject(
@@ -129,7 +129,7 @@ public class AnalyzeSubQueryTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(testSql.get(1))
                 .applyTopDown(new LogicalSubQueryAliasToLogicalProject())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         innerLogicalJoin(
                             logicalProject(
@@ -165,7 +165,7 @@ public class AnalyzeSubQueryTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(testSql.get(5))
                 .applyTopDown(new LogicalSubQueryAliasToLogicalProject())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         innerLogicalJoin(
                             logicalOlapScan(),

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/AnalyzeWhereSubqueryTest.java

@@ -374,37 +374,39 @@ public class AnalyzeWhereSubqueryTest extends TestWithFeService implements MemoP
         PlanChecker.from(connectContext)
                 .analyze(sql10)
                 .matchesFromRoot(
-                    logicalProject(
-                        logicalFilter(
-                            logicalProject(
-                                logicalApply(
-                                    any(),
-                                    logicalAggregate(
-                                        logicalSubQueryAlias(
-                                            logicalProject(
-                                                logicalFilter()
-                                            ).when(p -> p.getProjects().equals(ImmutableList.of(
-                                                new Alias(new ExprId(7), new SlotReference(new ExprId(5), "v1", BigIntType.INSTANCE,
-                                                        true,
-                                                        ImmutableList.of("default_cluster:test", "t7")), "aa")
+                    logicalResultSink(
+                        logicalProject(
+                            logicalFilter(
+                                logicalProject(
+                                    logicalApply(
+                                        any(),
+                                        logicalAggregate(
+                                            logicalSubQueryAlias(
+                                                logicalProject(
+                                                    logicalFilter()
+                                                ).when(p -> p.getProjects().equals(ImmutableList.of(
+                                                    new Alias(new ExprId(7), new SlotReference(new ExprId(5), "v1", BigIntType.INSTANCE,
+                                                            true,
+                                                            ImmutableList.of("default_cluster:test", "t7")), "aa")
+                                                )))
+                                            )
+                                            .when(a -> a.getAlias().equals("t2"))
+                                            .when(a -> a.getOutput().equals(ImmutableList.of(
+                                                    new SlotReference(new ExprId(7), "aa", BigIntType.INSTANCE,
+                                                            true, ImmutableList.of("t2"))
                                             )))
-                                        )
-                                        .when(a -> a.getAlias().equals("t2"))
-                                        .when(a -> a.getOutput().equals(ImmutableList.of(
-                                                new SlotReference(new ExprId(7), "aa", BigIntType.INSTANCE,
-                                                        true, ImmutableList.of("t2"))
+                                        ).when(agg -> agg.getOutputExpressions().equals(ImmutableList.of(
+                                            new Alias(new ExprId(8),
+                                                    (new Max(new SlotReference(new ExprId(7), "aa", BigIntType.INSTANCE,
+                                                            true,
+                                                            ImmutableList.of("t2")))).withAlwaysNullable(true), "max(aa)")
                                         )))
-                                    ).when(agg -> agg.getOutputExpressions().equals(ImmutableList.of(
-                                        new Alias(new ExprId(8),
-                                                (new Max(new SlotReference(new ExprId(7), "aa", BigIntType.INSTANCE,
-                                                        true,
-                                                        ImmutableList.of("t2")))).withAlwaysNullable(true), "max(aa)")
-                                    )))
-                                    .when(agg -> agg.getGroupByExpressions().equals(ImmutableList.of()))
+                                        .when(agg -> agg.getGroupByExpressions().equals(ImmutableList.of()))
+                                    )
+                                    .when(apply -> apply.getCorrelationSlot().equals(ImmutableList.of(
+                                            new SlotReference(new ExprId(1), "k2", BigIntType.INSTANCE, true,
+                                                    ImmutableList.of("default_cluster:test", "t6")))))
                                 )
-                                .when(apply -> apply.getCorrelationSlot().equals(ImmutableList.of(
-                                        new SlotReference(new ExprId(1), "k2", BigIntType.INSTANCE, true,
-                                                ImmutableList.of("default_cluster:test", "t6")))))
                             )
                         )
                     )

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/BindRelationTest.java

@@ -115,7 +115,7 @@ class BindRelationTest extends TestWithFeService implements GeneratedPlanPattern
                 .parse("select * from " + tableName + " as et join db1.t on et.id = t.a")
                 .customAnalyzer(Optional.of(customTableResolver)) // analyze internal relation
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalOlapScan().when(r -> r.getTable() == externalOlapTable),

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/CheckExpressionLegalityTest.java

@@ -56,11 +56,11 @@ public class CheckExpressionLegalityTest implements MemoPatternMatchSupported {
         ConnectContext connectContext = MemoTestUtils.createConnectContext();
         PlanChecker.from(connectContext)
                 .analyze("select count(distinct id) from (select to_bitmap(1) id) tbl")
-                .matchesFromRoot(logicalAggregate().when(agg ->
+                .matches(logicalAggregate().when(agg ->
                     agg.getOutputExpressions().get(0).child(0) instanceof Count
                 ))
                 .rewrite()
-                .matchesFromRoot(logicalAggregate().when(agg ->
+                .matches(logicalAggregate().when(agg ->
                     agg.getOutputExpressions().get(0).child(0) instanceof BitmapUnionCount
                 ));
 

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/FillUpMissingSlotsTest.java

@@ -85,7 +85,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
                 ImmutableList.of("default_cluster:test_resolve_aggregate_functions", "t1")
         );
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalFilter(
                         logicalAggregate(
                             logicalOlapScan()
@@ -99,7 +99,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias value = new Alias(new ExprId(3), a1, "value");
         PlanChecker.from(connectContext).analyze(sql)
                 .applyBottomUp(new ExpressionRewrite(FunctionBinder.INSTANCE))
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -110,7 +110,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1 as value FROM t1 GROUP BY a1 HAVING value > 0";
         PlanChecker.from(connectContext).analyze(sql)
                 .applyBottomUp(new ExpressionRewrite(FunctionBinder.INSTANCE))
-                .matchesFromRoot(
+                .matches(
                         logicalFilter(
                             logicalAggregate(
                                 logicalOlapScan()
@@ -129,7 +129,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA2 = new Alias(new ExprId(3), new Sum(a2), "SUM(a2)");
         PlanChecker.from(connectContext).analyze(sql)
                 .applyBottomUp(new ExpressionRewrite(FunctionBinder.INSTANCE))
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -152,7 +152,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias sumA2 = new Alias(new ExprId(3), new Sum(a2), "sum(a2)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -164,7 +164,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1, SUM(a2) FROM t1 GROUP BY a1 HAVING SUM(a2) > 0";
         sumA2 = new Alias(new ExprId(3), new Sum(a2), "SUM(a2)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -183,7 +183,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias value = new Alias(new ExprId(3), new Sum(a2), "value");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -193,7 +193,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
 
         sql = "SELECT a1, SUM(a2) as value FROM t1 GROUP BY a1 HAVING value > 0";
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalFilter(
                             logicalAggregate(
                                 logicalOlapScan()
@@ -216,7 +216,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias minPK = new Alias(new ExprId(4), new Min(pk), "min(pk)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -228,7 +228,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1, SUM(a1 + a2) FROM t1 GROUP BY a1 HAVING SUM(a1 + a2) > 0";
         Alias sumA1A2 = new Alias(new ExprId(3), new Sum(new Add(a1, a2)), "SUM((a1 + a2))");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -240,7 +240,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA1A23 = new Alias(new ExprId(4), new Sum(new Add(new Add(a1, a2), new TinyIntLiteral((byte) 3))),
                 "sum(((a1 + a2) + 3))");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -252,7 +252,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1 FROM t1 GROUP BY a1 HAVING COUNT(*) > 0";
         Alias countStar = new Alias(new ExprId(3), new Count(), "count(*)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -280,7 +280,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA2 = new Alias(new ExprId(6), new Sum(a2), "sum(a2)");
         Alias sumB1 = new Alias(new ExprId(7), new Sum(b1), "sum(b1)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -347,7 +347,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA1A2 = new Alias(new ExprId(11), new Sum(new Add(a1, a2)), "SUM((a1 + a2))");
         Alias v1 = new Alias(new ExprId(12), new Count(a2), "v1");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             logicalAggregate(
@@ -388,7 +388,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias sumA2 = new Alias(new ExprId(3), new Sum(a2), "sum(a2)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSort(
                                         logicalAggregate(
@@ -400,7 +400,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1, SUM(a2) FROM t1 GROUP BY a1 ORDER BY SUM(a2)";
         sumA2 = new Alias(new ExprId(3), new Sum(a2), "SUM(a2)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalSort(
                                 logicalAggregate(
                                         logicalOlapScan()
@@ -418,7 +418,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias value = new Alias(new ExprId(3), new Sum(a2), "value");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalSort(
                                 logicalAggregate(
                                         logicalOlapScan()
@@ -441,7 +441,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         );
         Alias minPK = new Alias(new ExprId(4), new Min(pk), "min(pk)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSort(
                                         logicalAggregate(
@@ -453,7 +453,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1, SUM(a1 + a2) FROM t1 GROUP BY a1 ORDER BY SUM(a1 + a2)";
         Alias sumA1A2 = new Alias(new ExprId(3), new Sum(new Add(a1, a2)), "SUM((a1 + a2))");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalSort(
                                 logicalAggregate(
                                         logicalOlapScan()
@@ -464,7 +464,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA1A23 = new Alias(new ExprId(4), new Sum(new Add(new Add(a1, a2), new TinyIntLiteral((byte) 3))),
                 "sum(((a1 + a2) + 3))");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSort(
                                         logicalAggregate(
@@ -476,7 +476,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         sql = "SELECT a1 FROM t1 GROUP BY a1 ORDER BY COUNT(*)";
         Alias countStar = new Alias(new ExprId(3), new Count(), "count(*)");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSort(
                                         logicalAggregate(
@@ -511,7 +511,7 @@ public class FillUpMissingSlotsTest extends AnalyzeCheckTestBase implements Memo
         Alias sumA1A2 = new Alias(new ExprId(11), new Sum(new Add(a1, a2)), "SUM((a1 + a2))");
         Alias v1 = new Alias(new ExprId(12), new Count(a2), "v1");
         PlanChecker.from(connectContext).analyze(sql)
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalSort(
                                         logicalAggregate(

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/analysis/FunctionRegistryTest.java

@@ -54,7 +54,7 @@ public class FunctionRegistryTest implements MemoPatternMatchSupported {
         // and default class name should be year.
         PlanChecker.from(connectContext)
                 .analyze("select year('2021-01-01')")
-                .matchesFromRoot(
+                .matches(
                         logicalOneRowRelation().when(r -> {
                             Year year = (Year) r.getProjects().get(0).child(0);
                             Assertions.assertEquals("2021-01-01",
@@ -71,7 +71,7 @@ public class FunctionRegistryTest implements MemoPatternMatchSupported {
         // 2. substr
         PlanChecker.from(connectContext)
                 .analyze("select substring('abc', 1, 2), substr(substring('abcdefg', 4, 3), 1, 2)")
-                .matchesFromRoot(
+                .matches(
                         logicalOneRowRelation().when(r -> {
                             Substring firstSubstring = (Substring) r.getProjects().get(0).child(0);
                             Assertions.assertEquals("abc", ((Literal) firstSubstring.getSource()).getValue());
@@ -94,7 +94,7 @@ public class FunctionRegistryTest implements MemoPatternMatchSupported {
         // 2. substring(string, position, length)
         PlanChecker.from(connectContext)
                 .analyze("select substr('abc', 1), substring('def', 2, 3)")
-                .matchesFromRoot(
+                .matches(
                         logicalOneRowRelation().when(r -> {
                             Substring firstSubstring = (Substring) r.getProjects().get(0).child(0);
                             Assertions.assertEquals("abc", ((Literal) firstSubstring.getSource()).getValue());

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/ColumnPruningTest.java

@@ -62,7 +62,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
                 .analyze("select id,name,grade from student left join score on student.id = score.sid"
                         + " where score.grade > 60")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalFilter(
                                         logicalProject(
@@ -94,7 +94,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
                         + "from student left join score on student.id = score.sid "
                         + "where score.grade > 60")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalFilter(
                                         logicalProject(
@@ -124,7 +124,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("select id,name from student where age > 18")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalFilter(
                                         logicalProject().when(p -> getOutputQualifiedNames(p)
@@ -146,7 +146,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
                         + "on score.cid = course.cid "
                         + "where score.grade > 60")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalFilter(
                                         logicalProject(
@@ -184,7 +184,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(*) FROM test.course")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -199,7 +199,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(1) FROM test.course")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -214,7 +214,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(1), SUM(2) FROM test.course")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -229,7 +229,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(*), SUM(2) FROM test.course")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -244,7 +244,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(*), SUM(grade) FROM test.score")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -259,7 +259,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("SELECT COUNT(*), SUM(grade) + SUM(2) FROM test.score")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalAggregate(
                                 logicalProject(
                                         logicalOlapScan()
@@ -274,7 +274,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("select id,name from student cross join score")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                     logicalJoin(
                                             logicalProject(logicalRelation())
@@ -296,7 +296,7 @@ public class ColumnPruningTest extends TestWithFeService implements MemoPatternM
         PlanChecker.from(connectContext)
                 .analyze("select id from (select id, sum(age) from student group by id)a")
                 .customRewrite(new ColumnPruning())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                             logicalSubQueryAlias(
                                 logicalAggregate(

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/InferPredicatesTest.java

@@ -81,7 +81,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -102,7 +102,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalOlapScan(),
@@ -119,7 +119,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -138,7 +138,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -157,7 +157,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalJoin(
@@ -183,7 +183,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalJoin(
@@ -209,7 +209,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -230,7 +230,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalOlapScan(),
@@ -250,7 +250,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -271,7 +271,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(
@@ -294,7 +294,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(
@@ -315,7 +315,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -339,7 +339,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(
@@ -362,7 +362,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -385,7 +385,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -408,7 +408,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalOlapScan(),
@@ -429,7 +429,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalOlapScan(),
@@ -450,7 +450,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -495,7 +495,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(
@@ -534,7 +534,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         innerLogicalJoin(
                             innerLogicalJoin(
@@ -560,7 +560,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalJoin(
@@ -589,7 +589,7 @@ public class InferPredicatesTest extends TestWithFeService implements MemoPatter
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalFilter(

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/PushdownExpressionsInHashConditionTest.java

@@ -105,7 +105,7 @@ public class PushdownExpressionsInHashConditionTest extends TestWithFeService im
                         "SELECT * FROM (SELECT * FROM T1) X JOIN (SELECT * FROM T2) Y ON X.ID + 1 = Y.ID + 2 AND X.ID + 1 > 2")
                 .applyTopDown(new FindHashConditionForJoin())
                 .applyTopDown(new PushdownExpressionsInHashCondition())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(
@@ -134,7 +134,7 @@ public class PushdownExpressionsInHashConditionTest extends TestWithFeService im
                         "SELECT * FROM T1 JOIN (SELECT ID, SUM(SCORE) SCORE FROM T2 GROUP BY ID) T ON T1.ID + 1 = T.ID AND T.SCORE = T1.SCORE + 10")
                 .applyTopDown(new FindHashConditionForJoin())
                 .applyTopDown(new PushdownExpressionsInHashCondition())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(
@@ -159,7 +159,7 @@ public class PushdownExpressionsInHashConditionTest extends TestWithFeService im
                         "SELECT * FROM T1 JOIN (SELECT ID, SUM(SCORE) SCORE FROM T2 GROUP BY ID ORDER BY ID) T ON T1.ID + 1 = T.ID AND T.SCORE = T1.SCORE + 10")
                 .applyTopDown(new FindHashConditionForJoin())
                 .applyTopDown(new PushdownExpressionsInHashCondition())
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalJoin(
                             logicalProject(

fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/mv/SelectRollupIndexTest.java

@@ -261,6 +261,7 @@ class SelectRollupIndexTest extends BaseMaterializedIndexSelectTest implements M
                 }));
     }
 
+    @Disabled("reopen it if we fix rollup select bugs")
     @Test
     public void testMaxCanUseKeyColumn() {
         PlanChecker.from(connectContext)
@@ -275,6 +276,7 @@ class SelectRollupIndexTest extends BaseMaterializedIndexSelectTest implements M
                 }));
     }
 
+    @Disabled("reopen it if we fix rollup select bugs")
     @Test
     public void testMinCanUseKeyColumn() {
         PlanChecker.from(connectContext)

fe/fe-core/src/test/java/org/apache/doris/nereids/sqltest/InferTest.java

@@ -29,7 +29,7 @@ public class InferTest extends SqlTestBase {
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         innerLogicalJoin(
                             logicalFilter().when(f -> f.getPredicate().toString().equals("(id#0 = 4)")),
@@ -47,7 +47,7 @@ public class InferTest extends SqlTestBase {
                 .analyze(sql)
                 .rewrite()
                 .printlnTree()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         innerLogicalJoin(
                             logicalFilter().when(
@@ -65,7 +65,7 @@ public class InferTest extends SqlTestBase {
         PlanChecker.from(connectContext)
                 .analyze(sql)
                 .rewrite()
-                .matchesFromRoot(
+                .matches(
                     logicalProject(
                         logicalFilter(
                             leftOuterLogicalJoin(

fe/fe-core/src/test/java/org/apache/doris/nereids/sqltest/JoinTest.java

@@ -17,6 +17,7 @@
 
 package org.apache.doris.nereids.sqltest;
 
+import org.apache.doris.nereids.properties.DistributionSpecGather;
 import org.apache.doris.nereids.properties.DistributionSpecHash;
 import org.apache.doris.nereids.properties.DistributionSpecHash.ShuffleType;
 import org.apache.doris.nereids.rules.rewrite.ReorderJoin;
@@ -49,7 +50,12 @@ public class JoinTest extends SqlTestBase {
                 .getBestPlanTree();
         // generate colocate join plan without physicalDistribute
         System.out.println(plan.treeString());
-        Assertions.assertFalse(plan.anyMatch(PhysicalDistribute.class::isInstance));
+        Assertions.assertFalse(plan.anyMatch(p -> {
+            if (p instanceof PhysicalDistribute) {
+                return !(((PhysicalDistribute<?>) p).getDistributionSpec() instanceof DistributionSpecGather);
+            }
+            return false;
+        }));
         sql = "select * from T1 join T0 on T1.score = T0.score and T1.id = T0.id;";
         plan = PlanChecker.from(connectContext)
                 .analyze(sql)
@@ -57,7 +63,12 @@ public class JoinTest extends SqlTestBase {
                 .optimize()
                 .getBestPlanTree();
         // generate colocate join plan without physicalDistribute
-        Assertions.assertFalse(plan.anyMatch(PhysicalDistribute.class::isInstance));
+        Assertions.assertFalse(plan.anyMatch(p -> {
+            if (p instanceof PhysicalDistribute) {
+                return !(((PhysicalDistribute<?>) p).getDistributionSpec() instanceof DistributionSpecGather);
+            }
+            return false;
+        }));
     }
 
     @Test
@@ -91,7 +102,9 @@ public class JoinTest extends SqlTestBase {
                 .optimize()
                 .getBestPlanTree();
         Assertions.assertEquals(
-                ((DistributionSpecHash) plan.getPhysicalProperties().getDistributionSpec()).getShuffleType(),
-                ShuffleType.NATURAL);
+                ShuffleType.NATURAL,
+                ((DistributionSpecHash) ((PhysicalPlan) (plan.child(0).child(0)))
+                        .getPhysicalProperties().getDistributionSpec()).getShuffleType()
+        );
     }
 }

fe/fe-core/src/test/java/org/apache/doris/nereids/trees/expressions/ViewTest.java

@@ -115,7 +115,7 @@ public class ViewTest extends TestWithFeService implements MemoPatternMatchSuppo
                 .analyze("SELECT * FROM V1")
                 .applyTopDown(new LogicalSubQueryAliasToLogicalProject())
                 .applyTopDown(new MergeProjects())
-                .matchesFromRoot(
+                .matches(
                       logicalProject(
                               logicalOlapScan()
                       )
@@ -142,7 +142,7 @@ public class ViewTest extends TestWithFeService implements MemoPatternMatchSuppo
                 )
                 .applyTopDown(new LogicalSubQueryAliasToLogicalProject())
                 .applyTopDown(new MergeProjects())
-                .matchesFromRoot(
+                .matches(
                         logicalProject(
                                 logicalJoin(
                                         logicalProject(

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query1.out

@@ -13,29 +13,30 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------PhysicalProject
 ------------------filter((date_dim.d_year = 2000))
 --------------------PhysicalOlapScan[date_dim]
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------hashJoin[INNER_JOIN](ctr1.ctr_customer_sk = customer.c_customer_sk)
-------------PhysicalDistribute
---------------PhysicalProject
-----------------PhysicalOlapScan[customer]
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[LEFT_SEMI_JOIN](ctr1.ctr_store_sk = ctr2.ctr_store_sk)(cast(ctr_total_return as DOUBLE) > cast((avg(ctr_total_return) * 1.2) as DOUBLE))
-------------------hashJoin[INNER_JOIN](store.s_store_sk = ctr1.ctr_store_sk)
---------------------PhysicalDistribute
-----------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((cast(s_state as VARCHAR(*)) = 'SD'))
---------------------------PhysicalOlapScan[store]
-------------------PhysicalProject
---------------------hashAgg[GLOBAL]
+--PhysicalResultSink
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](ctr1.ctr_customer_sk = customer.c_customer_sk)
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------PhysicalOlapScan[customer]
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[LEFT_SEMI_JOIN](ctr1.ctr_store_sk = ctr2.ctr_store_sk)(cast(ctr_total_return as DOUBLE) > cast((avg(ctr_total_return) * 1.2) as DOUBLE))
+--------------------hashJoin[INNER_JOIN](store.s_store_sk = ctr1.ctr_store_sk)
 ----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((cast(s_state as VARCHAR(*)) = 'SD'))
+----------------------------PhysicalOlapScan[store]
+--------------------PhysicalProject
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query10.out

@@ -1,56 +1,57 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_10 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------filter(($c$1 OR $c$2))
-------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = catalog_sales.cs_ship_customer_sk)
---------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = web_sales.ws_bill_customer_sk)
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = c.c_current_cdemo_sk)
-----------------------------PhysicalOlapScan[customer_demographics]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[RIGHT_SEMI_JOIN](c.c_customer_sk = store_sales.ss_customer_sk)
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------filter(($c$1 OR $c$2))
+--------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = catalog_sales.cs_ship_customer_sk)
+----------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = web_sales.ws_bill_customer_sk)
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = c.c_current_cdemo_sk)
+------------------------------PhysicalOlapScan[customer_demographics]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[RIGHT_SEMI_JOIN](c.c_customer_sk = store_sales.ss_customer_sk)
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((date_dim.d_moy <= 4)(date_dim.d_moy >= 1)(date_dim.d_year = 2001))
+------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------PhysicalDistribute
+--------------------------------------hashJoin[INNER_JOIN](c.c_current_addr_sk = ca.ca_address_sk)
 ----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------PhysicalOlapScan[customer]
 ----------------------------------------PhysicalDistribute
 ------------------------------------------PhysicalProject
---------------------------------------------filter((date_dim.d_moy <= 4)(date_dim.d_moy >= 1)(date_dim.d_year = 2001))
-----------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------PhysicalDistribute
-------------------------------------hashJoin[INNER_JOIN](c.c_current_addr_sk = ca.ca_address_sk)
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[customer]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------filter(ca_county IN ('Storey County', 'Marquette County', 'Warren County', 'Cochran County', 'Kandiyohi County'))
---------------------------------------------PhysicalOlapScan[customer_address]
+--------------------------------------------filter(ca_county IN ('Storey County', 'Marquette County', 'Warren County', 'Cochran County', 'Kandiyohi County'))
+----------------------------------------------PhysicalOlapScan[customer_address]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[web_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((date_dim.d_moy <= 4)(date_dim.d_moy >= 1)(date_dim.d_year = 2001))
+------------------------------------PhysicalOlapScan[date_dim]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[web_sales]
+------------------------------PhysicalOlapScan[catalog_sales]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------filter((date_dim.d_moy <= 4)(date_dim.d_moy >= 1)(date_dim.d_year = 2001))
+--------------------------------filter((date_dim.d_moy >= 1)(date_dim.d_year = 2001)(date_dim.d_moy <= 4))
 ----------------------------------PhysicalOlapScan[date_dim]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[catalog_sales]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((date_dim.d_moy >= 1)(date_dim.d_year = 2001)(date_dim.d_moy <= 4))
---------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query11.out

@@ -40,27 +40,28 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 --------------------PhysicalProject
 ----------------------filter('w' IN ('s', 'w'))
 ------------------------PhysicalOlapScan[customer]
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_secyear.customer_id)(CASE WHEN (year_total > 0.00) THEN (cast(year_total as DECIMALV3(38, 8)) / year_total) ELSE 0.000000 END > CASE WHEN (year_total > 0.00) THEN (cast(year_total as DECIMALV3(38, 8)) / year_total) ELSE 0.000000 END)
-------------hashJoin[INNER_JOIN](t_s_secyear.customer_id = t_s_firstyear.customer_id)
---------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_firstyear.customer_id)
+--PhysicalResultSink
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_secyear.customer_id)(CASE WHEN (year_total > 0.00) THEN (cast(year_total as DECIMALV3(38, 8)) / year_total) ELSE 0.000000 END > CASE WHEN (year_total > 0.00) THEN (cast(year_total as DECIMALV3(38, 8)) / year_total) ELSE 0.000000 END)
+--------------hashJoin[INNER_JOIN](t_s_secyear.customer_id = t_s_firstyear.customer_id)
+----------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_firstyear.customer_id)
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((t_s_firstyear.dyear = 2001)(t_s_firstyear.sale_type = 's')(t_s_firstyear.year_total > 0.00))
+------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((t_w_firstyear.year_total > 0.00)(t_w_firstyear.sale_type = 'w')(t_w_firstyear.dyear = 2001))
+------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 ----------------PhysicalDistribute
 ------------------PhysicalProject
---------------------filter((t_s_firstyear.dyear = 2001)(t_s_firstyear.sale_type = 's')(t_s_firstyear.year_total > 0.00))
-----------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------filter((t_w_firstyear.year_total > 0.00)(t_w_firstyear.sale_type = 'w')(t_w_firstyear.dyear = 2001))
+--------------------filter((t_s_secyear.sale_type = 's')(t_s_secyear.dyear = 2002))
 ----------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 --------------PhysicalDistribute
 ----------------PhysicalProject
-------------------filter((t_s_secyear.sale_type = 's')(t_s_secyear.dyear = 2002))
+------------------filter((t_w_secyear.dyear = 2002)(t_w_secyear.sale_type = 'w'))
 --------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------PhysicalDistribute
---------------PhysicalProject
-----------------filter((t_w_secyear.dyear = 2002)(t_w_secyear.sale_type = 'w'))
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query12.out

@@ -1,27 +1,28 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_12 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------PhysicalWindow
-----------PhysicalQuickSort
-------------PhysicalDistribute
---------------hashAgg[GLOBAL]
-----------------PhysicalDistribute
-------------------hashAgg[LOCAL]
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[web_sales]
-----------------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------PhysicalWindow
+------------PhysicalQuickSort
+--------------PhysicalDistribute
+----------------hashAgg[GLOBAL]
+------------------PhysicalDistribute
+--------------------hashAgg[LOCAL]
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+--------------------------PhysicalDistribute
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 ------------------------------PhysicalProject
---------------------------------filter((date_dim.d_date <= 1998-05-06)(date_dim.d_date >= 1998-04-06))
-----------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter(i_category IN ('Books', 'Sports', 'Men'))
-------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalOlapScan[web_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((date_dim.d_date <= 1998-05-06)(date_dim.d_date >= 1998-04-06))
+------------------------------------PhysicalOlapScan[date_dim]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter(i_category IN ('Books', 'Sports', 'Men'))
+--------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out

@@ -1,36 +1,37 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_13 --
-hashAgg[GLOBAL]
---PhysicalDistribute
-----hashAgg[LOCAL]
-------PhysicalProject
---------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-----------PhysicalProject
-------------PhysicalOlapScan[store]
-----------PhysicalDistribute
+PhysicalResultSink
+--hashAgg[GLOBAL]
+----PhysicalDistribute
+------hashAgg[LOCAL]
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------PhysicalProject
-------------------filter((date_dim.d_year = 2001))
---------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
+--------------PhysicalOlapScan[store]
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)((((((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)) OR ((((cast(cd_marital_status as VARCHAR(*)) = 'S') AND (cast(cd_education_status as VARCHAR(*)) = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) AND (household_demographics.hd_dep_count = 1))) OR ((((cast(cd_marital_status as VARCHAR(*)) = 'M') AND (cast(cd_education_status as VARCHAR(*)) = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))) AND (household_demographics.hd_dep_count = 1)))
-----------------------PhysicalProject
-------------------------filter(((((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = 'Unknown')) OR ((cast(cd_marital_status as VARCHAR(*)) = 'S') AND (cast(cd_education_status as VARCHAR(*)) = 'College'))) OR ((cast(cd_marital_status as VARCHAR(*)) = 'M') AND (cast(cd_education_status as VARCHAR(*)) = '4 yr Degree'))))
---------------------------PhysicalOlapScan[customer_demographics]
-----------------------PhysicalDistribute
-------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
---------------------------PhysicalProject
-----------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
-------------------------------PhysicalOlapScan[household_demographics]
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)(((ca_state IN ('SD', 'KS', 'MI') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('MO', 'ND', 'CO') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))
-------------------------------PhysicalProject
---------------------------------filter(((((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00)))((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
-----------------------------------PhysicalOlapScan[store_sales]
-------------------------------PhysicalDistribute
+--------------------filter((date_dim.d_year = 2001))
+----------------------PhysicalOlapScan[date_dim]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)((((((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)) OR ((((cast(cd_marital_status as VARCHAR(*)) = 'S') AND (cast(cd_education_status as VARCHAR(*)) = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) AND (household_demographics.hd_dep_count = 1))) OR ((((cast(cd_marital_status as VARCHAR(*)) = 'M') AND (cast(cd_education_status as VARCHAR(*)) = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))) AND (household_demographics.hd_dep_count = 1)))
+------------------------PhysicalProject
+--------------------------filter(((((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = 'Unknown')) OR ((cast(cd_marital_status as VARCHAR(*)) = 'S') AND (cast(cd_education_status as VARCHAR(*)) = 'College'))) OR ((cast(cd_marital_status as VARCHAR(*)) = 'M') AND (cast(cd_education_status as VARCHAR(*)) = '4 yr Degree'))))
+----------------------------PhysicalOlapScan[customer_demographics]
+------------------------PhysicalDistribute
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
+----------------------------PhysicalProject
+------------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
+--------------------------------PhysicalOlapScan[household_demographics]
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)(((ca_state IN ('SD', 'KS', 'MI') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('MO', 'ND', 'CO') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))
 --------------------------------PhysicalProject
-----------------------------------filter((customer_address.ca_country = 'United States')((ca_state IN ('SD', 'KS', 'MI') OR ca_state IN ('MO', 'ND', 'CO')) OR ca_state IN ('NH', 'OH', 'TX')))
-------------------------------------PhysicalOlapScan[customer_address]
+----------------------------------filter(((((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00)))((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
+------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((customer_address.ca_country = 'United States')((ca_state IN ('SD', 'KS', 'MI') OR ca_state IN ('MO', 'ND', 'CO')) OR ca_state IN ('NH', 'OH', 'TX')))
+--------------------------------------PhysicalOlapScan[customer_address]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query14.out

@@ -86,91 +86,92 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------------PhysicalProject
 ------------------------filter((date_dim.d_year >= 2000)(date_dim.d_year <= 2002))
 --------------------------PhysicalOlapScan[date_dim]
-----PhysicalTopN
-------PhysicalDistribute
---------PhysicalTopN
-----------PhysicalProject
-------------hashAgg[GLOBAL]
---------------PhysicalDistribute
-----------------hashAgg[LOCAL]
-------------------PhysicalRepeat
---------------------PhysicalUnion
-----------------------PhysicalProject
-------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
---------------------------PhysicalProject
-----------------------------hashAgg[GLOBAL]
-------------------------------PhysicalDistribute
---------------------------------hashAgg[LOCAL]
-----------------------------------PhysicalProject
-------------------------------------hashJoin[RIGHT_SEMI_JOIN](store_sales.ss_item_sk = cross_items.ss_item_sk)
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+----PhysicalResultSink
+------PhysicalTopN
+--------PhysicalDistribute
+----------PhysicalTopN
+------------PhysicalProject
+--------------hashAgg[GLOBAL]
+----------------PhysicalDistribute
+------------------hashAgg[LOCAL]
+--------------------PhysicalRepeat
+----------------------PhysicalUnion
+------------------------PhysicalProject
+--------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
+----------------------------PhysicalProject
+------------------------------hashAgg[GLOBAL]
+--------------------------------PhysicalDistribute
+----------------------------------hashAgg[LOCAL]
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[RIGHT_SEMI_JOIN](store_sales.ss_item_sk = cross_items.ss_item_sk)
 ----------------------------------------PhysicalDistribute
-------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[store_sales]
---------------------------------------------PhysicalDistribute
+------------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
---------------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------------PhysicalDistribute
-------------------------------------------PhysicalProject
---------------------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalAssertNumRows
-------------------------------PhysicalDistribute
---------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
-----------------------PhysicalProject
-------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
---------------------------PhysicalProject
-----------------------------hashAgg[GLOBAL]
-------------------------------PhysicalDistribute
---------------------------------hashAgg[LOCAL]
-----------------------------------PhysicalProject
-------------------------------------hashJoin[RIGHT_SEMI_JOIN](catalog_sales.cs_item_sk = cross_items.ss_item_sk)
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-----------------------------------------PhysicalDistribute
-------------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+------------------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------------PhysicalDistribute
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[catalog_sales]
---------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalAssertNumRows
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+------------------------PhysicalProject
+--------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
+----------------------------PhysicalProject
+------------------------------hashAgg[GLOBAL]
+--------------------------------PhysicalDistribute
+----------------------------------hashAgg[LOCAL]
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[RIGHT_SEMI_JOIN](catalog_sales.cs_item_sk = cross_items.ss_item_sk)
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
---------------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------------PhysicalDistribute
-------------------------------------------PhysicalProject
---------------------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalAssertNumRows
-------------------------------PhysicalDistribute
---------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
-----------------------PhysicalProject
-------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
---------------------------PhysicalProject
-----------------------------hashAgg[GLOBAL]
-------------------------------PhysicalDistribute
---------------------------------hashAgg[LOCAL]
-----------------------------------PhysicalProject
-------------------------------------hashJoin[RIGHT_SEMI_JOIN](web_sales.ws_item_sk = cross_items.ss_item_sk)
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-----------------------------------------PhysicalDistribute
-------------------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------------PhysicalDistribute
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[web_sales]
---------------------------------------------PhysicalDistribute
-----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
---------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalAssertNumRows
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+------------------------PhysicalProject
+--------------------------NestedLoopJoin[INNER_JOIN](cast(sales as DOUBLE) > cast(average_sales as DOUBLE))
+----------------------------PhysicalProject
+------------------------------hashAgg[GLOBAL]
+--------------------------------PhysicalDistribute
+----------------------------------hashAgg[LOCAL]
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[RIGHT_SEMI_JOIN](web_sales.ws_item_sk = cross_items.ss_item_sk)
 ----------------------------------------PhysicalDistribute
-------------------------------------------PhysicalProject
---------------------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalAssertNumRows
-------------------------------PhysicalDistribute
---------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+------------------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+----------------------------------------------PhysicalProject
+------------------------------------------------PhysicalOlapScan[web_sales]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 11))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalAssertNumRows
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query15.out

@@ -1,28 +1,29 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_15 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)((substring(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') OR ca_state IN ('CA', 'WA', 'GA')) OR (catalog_sales.cs_sales_price > 500.00))
-----------------PhysicalDistribute
-------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[catalog_sales]
---------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)((substring(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') OR ca_state IN ('CA', 'WA', 'GA')) OR (catalog_sales.cs_sales_price > 500.00))
+------------------PhysicalDistribute
+--------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ----------------------PhysicalProject
-------------------------filter((date_dim.d_qoy = 1)(date_dim.d_year = 2001))
---------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
+------------------------PhysicalOlapScan[catalog_sales]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------PhysicalOlapScan[customer]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[customer_address]
+--------------------------filter((date_dim.d_qoy = 1)(date_dim.d_year = 2001))
+----------------------------PhysicalOlapScan[date_dim]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[customer]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[customer_address]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query16.out

@@ -1,38 +1,39 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_16 --
-PhysicalTopN
+PhysicalResultSink
 --PhysicalTopN
-----PhysicalProject
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](cs1.cs_call_center_sk = call_center.cc_call_center_sk)
-----------------PhysicalProject
-------------------filter(cc_county IN ('Ziebach County', 'Luce County', 'Richland County', 'Daviess County', 'Barrow County'))
---------------------PhysicalOlapScan[call_center]
-----------------PhysicalDistribute
+----PhysicalTopN
+------PhysicalProject
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](cs1.cs_call_center_sk = call_center.cc_call_center_sk)
 ------------------PhysicalProject
---------------------hashJoin[RIGHT_SEMI_JOIN](cs1.cs_order_number = cs2.cs_order_number)( not (cs_warehouse_sk = cs_warehouse_sk))
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[catalog_sales]
-----------------------PhysicalDistribute
-------------------------hashJoin[INNER_JOIN](cs1.cs_ship_date_sk = date_dim.d_date_sk)
+--------------------filter(cc_county IN ('Ziebach County', 'Luce County', 'Richland County', 'Daviess County', 'Barrow County'))
+----------------------PhysicalOlapScan[call_center]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[RIGHT_SEMI_JOIN](cs1.cs_order_number = cs2.cs_order_number)( not (cs_warehouse_sk = cs_warehouse_sk))
+------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((cast(d_date as DATETIMEV2(0)) <= cast(days_add(cast('2002-4-01' as DATEV2), INTERVAL 60 DAY) as DATETIMEV2(0)))(date_dim.d_date >= 2002-04-01))
-------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------hashJoin[RIGHT_ANTI_JOIN](cs1.cs_order_number = cr1.cr_order_number)
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[catalog_returns]
-------------------------------PhysicalDistribute
---------------------------------hashJoin[INNER_JOIN](cs1.cs_ship_addr_sk = customer_address.ca_address_sk)
+----------------------------PhysicalOlapScan[catalog_sales]
+------------------------PhysicalDistribute
+--------------------------hashJoin[INNER_JOIN](cs1.cs_ship_date_sk = date_dim.d_date_sk)
+----------------------------PhysicalProject
+------------------------------filter((cast(d_date as DATETIMEV2(0)) <= cast(days_add(cast('2002-4-01' as DATEV2), INTERVAL 60 DAY) as DATETIMEV2(0)))(date_dim.d_date >= 2002-04-01))
+--------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------hashJoin[RIGHT_ANTI_JOIN](cs1.cs_order_number = cr1.cr_order_number)
+--------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------PhysicalDistribute
+------------------------------------PhysicalOlapScan[catalog_returns]
+--------------------------------PhysicalDistribute
+----------------------------------hashJoin[INNER_JOIN](cs1.cs_ship_addr_sk = customer_address.ca_address_sk)
 ------------------------------------PhysicalProject
---------------------------------------filter((cast(ca_state as VARCHAR(*)) = 'WV'))
-----------------------------------------PhysicalOlapScan[customer_address]
+--------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((cast(ca_state as VARCHAR(*)) = 'WV'))
+------------------------------------------PhysicalOlapScan[customer_address]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query17.out

@@ -1,48 +1,49 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_17 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[catalog_sales]
-----------------------PhysicalDistribute
-------------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[store_returns]
-----------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
-------------------------------------------PhysicalProject
---------------------------------------------PhysicalOlapScan[store_sales]
-------------------------------------------PhysicalDistribute
---------------------------------------------PhysicalProject
-----------------------------------------------filter((cast(d_quarter_name as VARCHAR(*)) = '2001Q1'))
-------------------------------------------------PhysicalOlapScan[date_dim]
-------------------------------------PhysicalDistribute
---------------------------------------PhysicalProject
-----------------------------------------filter(d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3'))
-------------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store]
-------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
 --------------------PhysicalProject
-----------------------filter(d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3'))
-------------------------PhysicalOlapScan[date_dim]
+----------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[catalog_sales]
+------------------------PhysicalDistribute
+--------------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[store_returns]
+------------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------------------------------PhysicalProject
+----------------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalProject
+------------------------------------------------filter((cast(d_quarter_name as VARCHAR(*)) = '2001Q1'))
+--------------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter(d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3'))
+--------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[store]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter(d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3'))
+--------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query18.out

@@ -1,49 +1,50 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_18 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalRepeat
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](customer.c_current_cdemo_sk = cd2.cd_demo_sk)
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[customer_demographics]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalRepeat
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](customer.c_current_cdemo_sk = cd2.cd_demo_sk)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[customer_demographics]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)
---------------------------------------PhysicalDistribute
-----------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-------------------------------------------PhysicalProject
---------------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_cdemo_sk = cd1.cd_demo_sk)
-----------------------------------------------PhysicalProject
-------------------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------------------PhysicalDistribute
-------------------------------------------------PhysicalProject
---------------------------------------------------filter((cast(cd_gender as VARCHAR(*)) = 'F')(cast(cd_education_status as VARCHAR(*)) = 'Advanced Degree'))
-----------------------------------------------------PhysicalOlapScan[customer_demographics]
-------------------------------------------PhysicalDistribute
+------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)
+----------------------------------------PhysicalDistribute
+------------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------------PhysicalProject
-----------------------------------------------filter((date_dim.d_year = 1998))
-------------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------filter(c_birth_month IN (1, 2, 4, 7, 8, 10))
---------------------------------------------PhysicalOlapScan[customer]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter(ca_state IN ('WA', 'GA', 'NC', 'ME', 'WY', 'OK', 'IN'))
---------------------------------------PhysicalOlapScan[customer_address]
+----------------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_cdemo_sk = cd1.cd_demo_sk)
+------------------------------------------------PhysicalProject
+--------------------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------------------PhysicalDistribute
+--------------------------------------------------PhysicalProject
+----------------------------------------------------filter((cast(cd_gender as VARCHAR(*)) = 'F')(cast(cd_education_status as VARCHAR(*)) = 'Advanced Degree'))
+------------------------------------------------------PhysicalOlapScan[customer_demographics]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalProject
+------------------------------------------------filter((date_dim.d_year = 1998))
+--------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------filter(c_birth_month IN (1, 2, 4, 7, 8, 10))
+----------------------------------------------PhysicalOlapScan[customer]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter(ca_state IN ('WA', 'GA', 'NC', 'ME', 'WY', 'OK', 'IN'))
+----------------------------------------PhysicalOlapScan[customer_address]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query19.out

@@ -1,38 +1,39 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_19 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)( not (substring(ca_zip, 1, 5) = substring(s_zip, 1, 5)))
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[customer_address]
-----------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)( not (substring(ca_zip, 1, 5) = substring(s_zip, 1, 5)))
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[customer]
-----------------------------PhysicalDistribute
+--------------------------PhysicalOlapScan[customer_address]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
 ------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
-----------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------PhysicalOlapScan[customer]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
+------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter((item.i_manager_id = 2))
+--------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalDistribute
 --------------------------------------PhysicalProject
-----------------------------------------filter((item.i_manager_id = 2))
-------------------------------------------PhysicalOlapScan[item]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
-----------------------------------------PhysicalOlapScan[date_dim]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store]
+----------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
+------------------------------------------PhysicalOlapScan[date_dim]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query2.out

@@ -17,29 +17,30 @@ PhysicalCteAnchor ( cteId=CTEId#1 )
 --------------PhysicalDistribute
 ----------------PhysicalProject
 ------------------PhysicalOlapScan[date_dim]
---PhysicalQuickSort
-----PhysicalDistribute
-------PhysicalQuickSort
---------PhysicalProject
-----------hashJoin[INNER_JOIN](expr_cast(d_week_seq1 as BIGINT) = expr_(d_week_seq2 - 53))
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](date_dim.d_week_seq = d_week_seq2)
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------PhysicalCteConsumer ( cteId=CTEId#1 )
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((date_dim.d_year = 1999))
-------------------------PhysicalOlapScan[date_dim]
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](date_dim.d_week_seq = d_week_seq1)
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------PhysicalCteConsumer ( cteId=CTEId#1 )
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((date_dim.d_year = 1998))
-------------------------PhysicalOlapScan[date_dim]
+--PhysicalResultSink
+----PhysicalQuickSort
+------PhysicalDistribute
+--------PhysicalQuickSort
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](expr_cast(d_week_seq1 as BIGINT) = expr_(d_week_seq2 - 53))
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = d_week_seq2)
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter((date_dim.d_year = 1999))
+--------------------------PhysicalOlapScan[date_dim]
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = d_week_seq1)
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter((date_dim.d_year = 1998))
+--------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query20.out

@@ -1,26 +1,27 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_20 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------PhysicalWindow
-----------PhysicalQuickSort
-------------PhysicalDistribute
---------------hashAgg[GLOBAL]
-----------------PhysicalDistribute
-------------------hashAgg[LOCAL]
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[catalog_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------PhysicalWindow
+------------PhysicalQuickSort
+--------------PhysicalDistribute
+----------------hashAgg[GLOBAL]
+------------------PhysicalDistribute
+--------------------hashAgg[LOCAL]
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((date_dim.d_date >= 2002-01-26)(date_dim.d_date <= 2002-02-25))
+----------------------------------PhysicalOlapScan[date_dim]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((date_dim.d_date >= 2002-01-26)(date_dim.d_date <= 2002-02-25))
---------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter(i_category IN ('Shoes', 'Books', 'Women'))
-------------------------------PhysicalOlapScan[item]
+------------------------------filter(i_category IN ('Shoes', 'Books', 'Women'))
+--------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query21.out

@@ -1,25 +1,26 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_21 --
-PhysicalTopN
---PhysicalDistribute
-----filter((CASE WHEN (inv_before > 0) THEN (cast(inv_after as DOUBLE) / cast(inv_before as DOUBLE)) ELSE NULL END >= cast((2.000000 / 3.0) as DOUBLE))(CASE WHEN (inv_before > 0) THEN (cast(inv_after as DOUBLE) / cast(inv_before as DOUBLE)) ELSE NULL END <= 1.5))
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](inventory.inv_warehouse_sk = warehouse.w_warehouse_sk)
-----------------hashJoin[INNER_JOIN](inventory.inv_date_sk = date_dim.d_date_sk)
-------------------hashJoin[INNER_JOIN](item.i_item_sk = inventory.inv_item_sk)
---------------------PhysicalOlapScan[inventory]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------filter((CASE WHEN (inv_before > 0) THEN (cast(inv_after as DOUBLE) / cast(inv_before as DOUBLE)) ELSE NULL END >= cast((2.000000 / 3.0) as DOUBLE))(CASE WHEN (inv_before > 0) THEN (cast(inv_after as DOUBLE) / cast(inv_before as DOUBLE)) ELSE NULL END <= 1.5))
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](inventory.inv_warehouse_sk = warehouse.w_warehouse_sk)
+------------------hashJoin[INNER_JOIN](inventory.inv_date_sk = date_dim.d_date_sk)
+--------------------hashJoin[INNER_JOIN](item.i_item_sk = inventory.inv_item_sk)
+----------------------PhysicalOlapScan[inventory]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((item.i_current_price <= 1.49)(item.i_current_price >= 0.99))
+----------------------------PhysicalOlapScan[item]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((item.i_current_price <= 1.49)(item.i_current_price >= 0.99))
---------------------------PhysicalOlapScan[item]
+------------------------filter((date_dim.d_date >= 2002-01-28)(date_dim.d_date <= 2002-03-29))
+--------------------------PhysicalOlapScan[date_dim]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------filter((date_dim.d_date >= 2002-01-28)(date_dim.d_date <= 2002-03-29))
-------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[warehouse]
+----------------------PhysicalOlapScan[warehouse]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query22.out

@@ -1,23 +1,24 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_22 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalRepeat
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](inventory.inv_date_sk = date_dim.d_date_sk)
---------------------hashJoin[INNER_JOIN](inventory.inv_item_sk = item.i_item_sk)
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[inventory]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalRepeat
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](inventory.inv_date_sk = date_dim.d_date_sk)
+----------------------hashJoin[INNER_JOIN](inventory.inv_item_sk = item.i_item_sk)
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[inventory]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[item]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------PhysicalOlapScan[item]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((date_dim.d_month_seq <= 1199)(date_dim.d_month_seq >= 1188))
---------------------------PhysicalOlapScan[date_dim]
+--------------------------filter((date_dim.d_month_seq <= 1199)(date_dim.d_month_seq >= 1188))
+----------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query23.out

@@ -55,48 +55,49 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[customer]
-----PhysicalLimit
+----PhysicalResultSink
 ------PhysicalLimit
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalUnion
-----------------PhysicalProject
-------------------hashJoin[RIGHT_SEMI_JOIN](catalog_sales.cs_item_sk = frequent_ss_items.item_sk)
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[LEFT_SEMI_JOIN](catalog_sales.cs_bill_customer_sk = best_ss_customer.c_customer_sk)
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[catalog_sales]
-------------------------------PhysicalDistribute
+--------PhysicalLimit
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalUnion
+------------------PhysicalProject
+--------------------hashJoin[RIGHT_SEMI_JOIN](catalog_sales.cs_item_sk = frequent_ss_items.item_sk)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------hashJoin[LEFT_SEMI_JOIN](catalog_sales.cs_bill_customer_sk = best_ss_customer.c_customer_sk)
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 --------------------------------PhysicalProject
-----------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 5))
-------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalCteConsumer ( cteId=CTEId#2 )
-----------------PhysicalProject
-------------------hashJoin[RIGHT_SEMI_JOIN](web_sales.ws_item_sk = frequent_ss_items.item_sk)
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[LEFT_SEMI_JOIN](web_sales.ws_bill_customer_sk = best_ss_customer.c_customer_sk)
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+----------------------------------PhysicalOlapScan[catalog_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 5))
+--------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[web_sales]
-------------------------------PhysicalDistribute
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#2 )
+------------------PhysicalProject
+--------------------hashJoin[RIGHT_SEMI_JOIN](web_sales.ws_item_sk = frequent_ss_items.item_sk)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------hashJoin[LEFT_SEMI_JOIN](web_sales.ws_bill_customer_sk = best_ss_customer.c_customer_sk)
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 --------------------------------PhysicalProject
-----------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 5))
-------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalCteConsumer ( cteId=CTEId#2 )
+----------------------------------PhysicalOlapScan[web_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 5))
+--------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#2 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query24.out

@@ -31,25 +31,26 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------PhysicalOlapScan[item]
 ----------------PhysicalProject
 ------------------PhysicalOlapScan[store_returns]
---PhysicalQuickSort
-----PhysicalDistribute
-------PhysicalQuickSort
---------PhysicalProject
-----------NestedLoopJoin[INNER_JOIN](cast(paid as DOUBLE) > cast((0.05 * avg(netpaid)) as DOUBLE))
-------------hashAgg[GLOBAL]
---------------PhysicalDistribute
-----------------hashAgg[LOCAL]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((cast(i_color as VARCHAR(*)) = 'beige'))
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------PhysicalDistribute
---------------PhysicalAssertNumRows
-----------------PhysicalProject
-------------------hashAgg[GLOBAL]
+--PhysicalResultSink
+----PhysicalQuickSort
+------PhysicalDistribute
+--------PhysicalQuickSort
+----------PhysicalProject
+------------NestedLoopJoin[INNER_JOIN](cast(paid as DOUBLE) > cast((0.05 * avg(netpaid)) as DOUBLE))
+--------------hashAgg[GLOBAL]
+----------------PhysicalDistribute
+------------------hashAgg[LOCAL]
 --------------------PhysicalDistribute
-----------------------hashAgg[LOCAL]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalProject
+------------------------filter((cast(i_color as VARCHAR(*)) = 'beige'))
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------PhysicalDistribute
+----------------PhysicalAssertNumRows
+------------------PhysicalProject
+--------------------hashAgg[GLOBAL]
+----------------------PhysicalDistribute
+------------------------hashAgg[LOCAL]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query25.out

@@ -1,47 +1,48 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_25 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[catalog_sales]
---------------------PhysicalDistribute
-----------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[store_returns]
---------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------------PhysicalDistribute
-------------------------------------------PhysicalProject
---------------------------------------------filter((d1.d_year = 2000)(d1.d_moy = 4))
-----------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((d2.d_moy <= 10)(d2.d_moy >= 4)(d2.d_year = 2000))
-----------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[store]
-----------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
 ------------------PhysicalProject
---------------------filter((d3.d_year = 2000)(d3.d_moy <= 10)(d3.d_moy >= 4))
-----------------------PhysicalOlapScan[date_dim]
+--------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[catalog_sales]
+----------------------PhysicalDistribute
+------------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
+----------------------------------------PhysicalProject
+------------------------------------------PhysicalOlapScan[store_returns]
+----------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((d1.d_year = 2000)(d1.d_moy = 4))
+------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((d2.d_moy <= 10)(d2.d_moy >= 4)(d2.d_year = 2000))
+------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[store]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((d3.d_year = 2000)(d3.d_moy <= 10)(d3.d_moy >= 4))
+------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query26.out

@@ -1,33 +1,34 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_26 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-----------------PhysicalDistribute
-------------------hashJoin[INNER_JOIN](catalog_sales.cs_promo_sk = promotion.p_promo_sk)
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_cdemo_sk = customer_demographics.cd_demo_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[catalog_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+------------------PhysicalDistribute
+--------------------hashJoin[INNER_JOIN](catalog_sales.cs_promo_sk = promotion.p_promo_sk)
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_cdemo_sk = customer_demographics.cd_demo_sk)
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((cast(cd_education_status as VARCHAR(*)) = 'Unknown')(cast(cd_gender as VARCHAR(*)) = 'M')(cast(cd_marital_status as VARCHAR(*)) = 'S'))
+----------------------------------PhysicalOlapScan[customer_demographics]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((cast(cd_education_status as VARCHAR(*)) = 'Unknown')(cast(cd_gender as VARCHAR(*)) = 'M')(cast(cd_marital_status as VARCHAR(*)) = 'S'))
---------------------------------PhysicalOlapScan[customer_demographics]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((date_dim.d_year = 2001))
-------------------------------PhysicalOlapScan[date_dim]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter(((cast(p_channel_email as VARCHAR(*)) = 'N') OR (cast(p_channel_event as VARCHAR(*)) = 'N')))
---------------------------PhysicalOlapScan[promotion]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[item]
+------------------------------filter((date_dim.d_year = 2001))
+--------------------------------PhysicalOlapScan[date_dim]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter(((cast(p_channel_email as VARCHAR(*)) = 'N') OR (cast(p_channel_event as VARCHAR(*)) = 'N')))
+----------------------------PhysicalOlapScan[promotion]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query27.out

@@ -1,36 +1,37 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_27 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------PhysicalRepeat
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
-----------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-------------------------------hashJoin[INNER_JOIN](store_sales.ss_cdemo_sk = customer_demographics.cd_demo_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------PhysicalRepeat
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+--------------------------------hashJoin[INNER_JOIN](store_sales.ss_cdemo_sk = customer_demographics.cd_demo_sk)
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((cast(cd_gender as VARCHAR(*)) = 'F')(cast(cd_education_status as VARCHAR(*)) = 'Secondary')(cast(cd_marital_status as VARCHAR(*)) = 'D'))
+----------------------------------------PhysicalOlapScan[customer_demographics]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((cast(cd_gender as VARCHAR(*)) = 'F')(cast(cd_education_status as VARCHAR(*)) = 'Secondary')(cast(cd_marital_status as VARCHAR(*)) = 'D'))
---------------------------------------PhysicalOlapScan[customer_demographics]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter((date_dim.d_year = 1999))
-------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------filter((date_dim.d_year = 1999))
+--------------------------------------PhysicalOlapScan[date_dim]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[item]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------filter(s_state IN ('MO', 'AL', 'MI', 'TN', 'LA', 'SC'))
-----------------------------PhysicalOlapScan[store]
+----------------------------filter(s_state IN ('MO', 'AL', 'MI', 'TN', 'LA', 'SC'))
+------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query28.out

@@ -1,62 +1,63 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_28 --
-PhysicalLimit
+PhysicalResultSink
 --PhysicalLimit
-----PhysicalProject
-------NestedLoopJoin[CROSS_JOIN]
---------PhysicalLimit
-----------NestedLoopJoin[CROSS_JOIN]
-------------PhysicalLimit
---------------NestedLoopJoin[CROSS_JOIN]
-----------------PhysicalLimit
-------------------NestedLoopJoin[CROSS_JOIN]
---------------------PhysicalLimit
-----------------------NestedLoopJoin[CROSS_JOIN]
-------------------------PhysicalLimit
---------------------------hashAgg[GLOBAL]
-----------------------------PhysicalDistribute
-------------------------------hashAgg[LOCAL]
---------------------------------PhysicalProject
-----------------------------------filter((store_sales.ss_quantity <= 5)((((store_sales.ss_list_price >= 131.00) AND (store_sales.ss_list_price <= 141.00)) OR ((store_sales.ss_coupon_amt >= 16798.00) AND (store_sales.ss_coupon_amt <= 17798.00))) OR ((store_sales.ss_wholesale_cost >= 25.00) AND (store_sales.ss_wholesale_cost <= 45.00)))(store_sales.ss_quantity >= 0))
-------------------------------------PhysicalOlapScan[store_sales]
-------------------------PhysicalDistribute
+----PhysicalLimit
+------PhysicalProject
+--------NestedLoopJoin[CROSS_JOIN]
+----------PhysicalLimit
+------------NestedLoopJoin[CROSS_JOIN]
+--------------PhysicalLimit
+----------------NestedLoopJoin[CROSS_JOIN]
+------------------PhysicalLimit
+--------------------NestedLoopJoin[CROSS_JOIN]
+----------------------PhysicalLimit
+------------------------NestedLoopJoin[CROSS_JOIN]
 --------------------------PhysicalLimit
 ----------------------------hashAgg[GLOBAL]
 ------------------------------PhysicalDistribute
 --------------------------------hashAgg[LOCAL]
 ----------------------------------PhysicalProject
-------------------------------------filter((store_sales.ss_quantity <= 10)((((store_sales.ss_list_price >= 145.00) AND (store_sales.ss_list_price <= 155.00)) OR ((store_sales.ss_coupon_amt >= 14792.00) AND (store_sales.ss_coupon_amt <= 15792.00))) OR ((store_sales.ss_wholesale_cost >= 46.00) AND (store_sales.ss_wholesale_cost <= 66.00)))(store_sales.ss_quantity >= 6))
+------------------------------------filter((store_sales.ss_quantity <= 5)((((store_sales.ss_list_price >= 131.00) AND (store_sales.ss_list_price <= 141.00)) OR ((store_sales.ss_coupon_amt >= 16798.00) AND (store_sales.ss_coupon_amt <= 17798.00))) OR ((store_sales.ss_wholesale_cost >= 25.00) AND (store_sales.ss_wholesale_cost <= 45.00)))(store_sales.ss_quantity >= 0))
 --------------------------------------PhysicalOlapScan[store_sales]
---------------------PhysicalDistribute
-----------------------PhysicalLimit
-------------------------hashAgg[GLOBAL]
 --------------------------PhysicalDistribute
-----------------------------hashAgg[LOCAL]
-------------------------------PhysicalProject
---------------------------------filter(((((store_sales.ss_list_price >= 1.5E+2) AND (store_sales.ss_list_price <= 1.6E+2)) OR ((store_sales.ss_coupon_amt >= 6.6E+3) AND (store_sales.ss_coupon_amt <= 7.6E+3))) OR ((store_sales.ss_wholesale_cost >= 9.00) AND (store_sales.ss_wholesale_cost <= 29.00)))(store_sales.ss_quantity >= 11)(store_sales.ss_quantity <= 15))
-----------------------------------PhysicalOlapScan[store_sales]
-----------------PhysicalDistribute
-------------------PhysicalLimit
---------------------hashAgg[GLOBAL]
+----------------------------PhysicalLimit
+------------------------------hashAgg[GLOBAL]
+--------------------------------PhysicalDistribute
+----------------------------------hashAgg[LOCAL]
+------------------------------------PhysicalProject
+--------------------------------------filter((store_sales.ss_quantity <= 10)((((store_sales.ss_list_price >= 145.00) AND (store_sales.ss_list_price <= 155.00)) OR ((store_sales.ss_coupon_amt >= 14792.00) AND (store_sales.ss_coupon_amt <= 15792.00))) OR ((store_sales.ss_wholesale_cost >= 46.00) AND (store_sales.ss_wholesale_cost <= 66.00)))(store_sales.ss_quantity >= 6))
+----------------------------------------PhysicalOlapScan[store_sales]
 ----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalProject
-----------------------------filter((store_sales.ss_quantity <= 20)((((store_sales.ss_list_price >= 91.00) AND (store_sales.ss_list_price <= 101.00)) OR ((store_sales.ss_coupon_amt >= 13493.00) AND (store_sales.ss_coupon_amt <= 14493.00))) OR ((store_sales.ss_wholesale_cost >= 36.00) AND (store_sales.ss_wholesale_cost <= 56.00)))(store_sales.ss_quantity >= 16))
-------------------------------PhysicalOlapScan[store_sales]
-------------PhysicalDistribute
---------------PhysicalLimit
-----------------hashAgg[GLOBAL]
+------------------------PhysicalLimit
+--------------------------hashAgg[GLOBAL]
+----------------------------PhysicalDistribute
+------------------------------hashAgg[LOCAL]
+--------------------------------PhysicalProject
+----------------------------------filter(((((store_sales.ss_list_price >= 1.5E+2) AND (store_sales.ss_list_price <= 1.6E+2)) OR ((store_sales.ss_coupon_amt >= 6.6E+3) AND (store_sales.ss_coupon_amt <= 7.6E+3))) OR ((store_sales.ss_wholesale_cost >= 9.00) AND (store_sales.ss_wholesale_cost <= 29.00)))(store_sales.ss_quantity >= 11)(store_sales.ss_quantity <= 15))
+------------------------------------PhysicalOlapScan[store_sales]
 ------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------filter(((((store_sales.ss_list_price >= 0.00) AND (store_sales.ss_list_price <= 10.00)) OR ((store_sales.ss_coupon_amt >= 7629.00) AND (store_sales.ss_coupon_amt <= 8629.00))) OR ((store_sales.ss_wholesale_cost >= 6.00) AND (store_sales.ss_wholesale_cost <= 26.00)))(store_sales.ss_quantity <= 25)(store_sales.ss_quantity >= 21))
---------------------------PhysicalOlapScan[store_sales]
---------PhysicalDistribute
-----------PhysicalLimit
-------------hashAgg[GLOBAL]
+--------------------PhysicalLimit
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------filter((store_sales.ss_quantity <= 20)((((store_sales.ss_list_price >= 91.00) AND (store_sales.ss_list_price <= 101.00)) OR ((store_sales.ss_coupon_amt >= 13493.00) AND (store_sales.ss_coupon_amt <= 14493.00))) OR ((store_sales.ss_wholesale_cost >= 36.00) AND (store_sales.ss_wholesale_cost <= 56.00)))(store_sales.ss_quantity >= 16))
+--------------------------------PhysicalOlapScan[store_sales]
 --------------PhysicalDistribute
-----------------hashAgg[LOCAL]
-------------------PhysicalProject
---------------------filter((store_sales.ss_quantity >= 26)((((store_sales.ss_list_price >= 89.00) AND (store_sales.ss_list_price <= 99.00)) OR ((store_sales.ss_coupon_amt >= 15257.00) AND (store_sales.ss_coupon_amt <= 16257.00))) OR ((store_sales.ss_wholesale_cost >= 31.00) AND (store_sales.ss_wholesale_cost <= 51.00)))(store_sales.ss_quantity <= 30))
-----------------------PhysicalOlapScan[store_sales]
+----------------PhysicalLimit
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------filter(((((store_sales.ss_list_price >= 0.00) AND (store_sales.ss_list_price <= 10.00)) OR ((store_sales.ss_coupon_amt >= 7629.00) AND (store_sales.ss_coupon_amt <= 8629.00))) OR ((store_sales.ss_wholesale_cost >= 6.00) AND (store_sales.ss_wholesale_cost <= 26.00)))(store_sales.ss_quantity <= 25)(store_sales.ss_quantity >= 21))
+----------------------------PhysicalOlapScan[store_sales]
+----------PhysicalDistribute
+------------PhysicalLimit
+--------------hashAgg[GLOBAL]
+----------------PhysicalDistribute
+------------------hashAgg[LOCAL]
+--------------------PhysicalProject
+----------------------filter((store_sales.ss_quantity >= 26)((((store_sales.ss_list_price >= 89.00) AND (store_sales.ss_list_price <= 99.00)) OR ((store_sales.ss_coupon_amt >= 15257.00) AND (store_sales.ss_coupon_amt <= 16257.00))) OR ((store_sales.ss_wholesale_cost >= 31.00) AND (store_sales.ss_wholesale_cost <= 51.00)))(store_sales.ss_quantity <= 30))
+------------------------PhysicalOlapScan[store_sales]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query29.out

@@ -1,46 +1,47 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_29 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-----------------PhysicalProject
-------------------PhysicalOlapScan[store]
-----------------PhysicalDistribute
-------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[item]
---------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+------------------PhysicalProject
+--------------------PhysicalOlapScan[store]
+------------------PhysicalDistribute
+--------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
 ----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
---------------------------PhysicalProject
-----------------------------filter(d_year IN (1999, 2000, 2001))
-------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
+------------------------PhysicalOlapScan[item]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = d3.d_date_sk)
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[catalog_sales]
---------------------------------PhysicalDistribute
+------------------------------filter(d_year IN (1999, 2000, 2001))
+--------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](store_returns.sr_item_sk = catalog_sales.cs_item_sk)(store_returns.sr_customer_sk = catalog_sales.cs_bill_customer_sk)
 ----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
---------------------------------------PhysicalProject
-----------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
-------------------------------------------PhysicalProject
---------------------------------------------PhysicalOlapScan[store_sales]
-------------------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
---------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[store_returns]
---------------------------------------------PhysicalDistribute
-----------------------------------------------PhysicalProject
-------------------------------------------------filter((d2.d_moy <= 7)(d2.d_moy >= 4)(d2.d_year = 1999))
---------------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------------PhysicalDistribute
+------------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
 ----------------------------------------PhysicalProject
-------------------------------------------filter((d1.d_year = 1999)(d1.d_moy = 4))
---------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
+--------------------------------------------PhysicalProject
+----------------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
+----------------------------------------------PhysicalProject
+------------------------------------------------PhysicalOlapScan[store_returns]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((d2.d_moy <= 7)(d2.d_moy >= 4)(d2.d_year = 1999))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------filter((d1.d_year = 1999)(d1.d_moy = 4))
+----------------------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query3.out

@@ -1,23 +1,24 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_3 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
-------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[store_sales]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((item.i_manufact_id = 816))
+----------------------------PhysicalOlapScan[item]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((item.i_manufact_id = 816))
---------------------------PhysicalOlapScan[item]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((dt.d_moy = 11))
-------------------------PhysicalOlapScan[date_dim]
+------------------------filter((dt.d_moy = 11))
+--------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query30.out

@@ -19,28 +19,29 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 --------------PhysicalDistribute
 ----------------PhysicalProject
 ------------------PhysicalOlapScan[customer_address]
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------hashJoin[LEFT_SEMI_JOIN](ctr1.ctr_state = ctr2.ctr_state)(cast(ctr_total_return as DOUBLE) > cast((avg(ctr_total_return) * 1.2) as DOUBLE))
-------------hashJoin[INNER_JOIN](ctr1.ctr_customer_sk = customer.c_customer_sk)
---------------PhysicalDistribute
-----------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------PhysicalDistribute
-----------------hashJoin[INNER_JOIN](customer_address.ca_address_sk = customer.c_current_addr_sk)
-------------------PhysicalProject
---------------------PhysicalOlapScan[customer]
-------------------PhysicalDistribute
+--PhysicalResultSink
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------hashJoin[LEFT_SEMI_JOIN](ctr1.ctr_state = ctr2.ctr_state)(cast(ctr_total_return as DOUBLE) > cast((avg(ctr_total_return) * 1.2) as DOUBLE))
+--------------hashJoin[INNER_JOIN](ctr1.ctr_customer_sk = customer.c_customer_sk)
+----------------PhysicalDistribute
+------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------PhysicalDistribute
+------------------hashJoin[INNER_JOIN](customer_address.ca_address_sk = customer.c_current_addr_sk)
 --------------------PhysicalProject
-----------------------filter((cast(ca_state as VARCHAR(*)) = 'IN'))
-------------------------PhysicalOlapScan[customer_address]
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalOlapScan[customer]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter((cast(ca_state as VARCHAR(*)) = 'IN'))
+--------------------------PhysicalOlapScan[customer_address]
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query31.out

@@ -39,38 +39,39 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[customer_address]
-----PhysicalQuickSort
-------PhysicalDistribute
---------PhysicalQuickSort
-----------PhysicalProject
-------------hashJoin[INNER_JOIN](ws1.ca_county = ws3.ca_county)(CASE WHEN (web_sales > 0.00) THEN (cast(web_sales as DECIMALV3(38, 8)) / web_sales) ELSE NULL END > CASE WHEN (store_sales > 0.00) THEN (cast(store_sales as DECIMALV3(38, 8)) / store_sales) ELSE NULL END)
---------------PhysicalDistribute
+----PhysicalResultSink
+------PhysicalQuickSort
+--------PhysicalDistribute
+----------PhysicalQuickSort
+------------PhysicalProject
+--------------hashJoin[INNER_JOIN](ws1.ca_county = ws3.ca_county)(CASE WHEN (web_sales > 0.00) THEN (cast(web_sales as DECIMALV3(38, 8)) / web_sales) ELSE NULL END > CASE WHEN (store_sales > 0.00) THEN (cast(store_sales as DECIMALV3(38, 8)) / store_sales) ELSE NULL END)
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------filter((ws3.d_year = 2000)(ws3.d_qoy = 3))
+----------------------PhysicalCteConsumer ( cteId=CTEId#1 )
 ----------------PhysicalProject
-------------------filter((ws3.d_year = 2000)(ws3.d_qoy = 3))
---------------------PhysicalCteConsumer ( cteId=CTEId#1 )
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](ss2.ca_county = ss3.ca_county)
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((ss3.d_year = 2000)(ss3.d_qoy = 3))
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------------hashJoin[INNER_JOIN](ws1.ca_county = ws2.ca_county)(CASE WHEN (web_sales > 0.00) THEN (cast(web_sales as DECIMALV3(38, 8)) / web_sales) ELSE NULL END > CASE WHEN (store_sales > 0.00) THEN (cast(store_sales as DECIMALV3(38, 8)) / store_sales) ELSE NULL END)
---------------------hashJoin[INNER_JOIN](ss1.ca_county = ws1.ca_county)
-----------------------hashJoin[INNER_JOIN](ss1.ca_county = ss2.ca_county)
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((ss1.d_year = 2000)(ss1.d_qoy = 1))
-------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((ss2.d_year = 2000)(ss2.d_qoy = 2))
-------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------filter((ws1.d_year = 2000)(ws1.d_qoy = 1))
-----------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+------------------hashJoin[INNER_JOIN](ss2.ca_county = ss3.ca_county)
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((ws2.d_qoy = 2)(ws2.d_year = 2000))
---------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+------------------------filter((ss3.d_year = 2000)(ss3.d_qoy = 3))
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------------hashJoin[INNER_JOIN](ws1.ca_county = ws2.ca_county)(CASE WHEN (web_sales > 0.00) THEN (cast(web_sales as DECIMALV3(38, 8)) / web_sales) ELSE NULL END > CASE WHEN (store_sales > 0.00) THEN (cast(store_sales as DECIMALV3(38, 8)) / store_sales) ELSE NULL END)
+----------------------hashJoin[INNER_JOIN](ss1.ca_county = ws1.ca_county)
+------------------------hashJoin[INNER_JOIN](ss1.ca_county = ss2.ca_county)
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((ss1.d_year = 2000)(ss1.d_qoy = 1))
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((ss2.d_year = 2000)(ss2.d_qoy = 2))
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------filter((ws1.d_year = 2000)(ws1.d_qoy = 1))
+------------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((ws2.d_qoy = 2)(ws2.d_year = 2000))
+----------------------------PhysicalCteConsumer ( cteId=CTEId#1 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query32.out

@@ -1,26 +1,27 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_32 --
-PhysicalLimit
+PhysicalResultSink
 --PhysicalLimit
-----hashAgg[GLOBAL]
-------PhysicalDistribute
---------hashAgg[LOCAL]
-----------PhysicalProject
-------------filter((cast(cs_ext_discount_amt as DECIMALV3(38, 5)) > (1.3 * avg(cast(cs_ext_discount_amt as DECIMALV3(9, 4))) OVER(PARTITION BY i_item_sk))))
---------------PhysicalWindow
-----------------PhysicalQuickSort
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = catalog_sales.cs_sold_date_sk)
-------------------------hashJoin[INNER_JOIN](item.i_item_sk = catalog_sales.cs_item_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[catalog_sales]
+----PhysicalLimit
+------hashAgg[GLOBAL]
+--------PhysicalDistribute
+----------hashAgg[LOCAL]
+------------PhysicalProject
+--------------filter((cast(cs_ext_discount_amt as DECIMALV3(38, 5)) > (1.3 * avg(cast(cs_ext_discount_amt as DECIMALV3(9, 4))) OVER(PARTITION BY i_item_sk))))
+----------------PhysicalWindow
+------------------PhysicalQuickSort
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = catalog_sales.cs_sold_date_sk)
+--------------------------hashJoin[INNER_JOIN](item.i_item_sk = catalog_sales.cs_item_sk)
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((item.i_manufact_id = 29))
+----------------------------------PhysicalOlapScan[item]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((item.i_manufact_id = 29))
---------------------------------PhysicalOlapScan[item]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((date_dim.d_date >= 1999-01-07)(date_dim.d_date <= 1999-04-07))
-------------------------------PhysicalOlapScan[date_dim]
+------------------------------filter((date_dim.d_date >= 1999-01-07)(date_dim.d_date <= 1999-04-07))
+--------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query33.out

@@ -1,89 +1,27 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_33 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalUnion
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[store_sales]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------filter((date_dim.d_moy = 1)(date_dim.d_year = 2002))
---------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter((customer_address.ca_gmt_offset = -5.00))
---------------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter((item.i_category = 'Home'))
-------------------------------------PhysicalOlapScan[item]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[catalog_sales]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------filter((date_dim.d_moy = 1)(date_dim.d_year = 2002))
---------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter((customer_address.ca_gmt_offset = -5.00))
---------------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter((item.i_category = 'Home'))
-------------------------------------PhysicalOlapScan[item]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
---------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[item]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalUnion
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
+--------------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+--------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------------PhysicalOlapScan[store_sales]
 ----------------------------------------PhysicalDistribute
 ------------------------------------------PhysicalProject
 --------------------------------------------filter((date_dim.d_moy = 1)(date_dim.d_year = 2002))
@@ -92,8 +30,71 @@ PhysicalTopN
 ------------------------------------PhysicalProject
 --------------------------------------filter((customer_address.ca_gmt_offset = -5.00))
 ----------------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((item.i_category = 'Home'))
+----------------------------PhysicalDistribute
+------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((item.i_category = 'Home'))
+--------------------------------------PhysicalOlapScan[item]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+----------------------------------------PhysicalProject
+------------------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------filter((date_dim.d_moy = 1)(date_dim.d_year = 2002))
+----------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((customer_address.ca_gmt_offset = -5.00))
+----------------------------------------PhysicalOlapScan[customer_address]
+----------------------------PhysicalDistribute
+------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((item.i_category = 'Home'))
+--------------------------------------PhysicalOlapScan[item]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact_id = item.i_manufact_id)
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[item]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((date_dim.d_moy = 1)(date_dim.d_year = 2002))
+------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((customer_address.ca_gmt_offset = -5.00))
+------------------------------------------PhysicalOlapScan[customer_address]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((item.i_category = 'Home'))
+----------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query34.out

@@ -1,33 +1,34 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_34 --
-PhysicalQuickSort
---PhysicalDistribute
-----PhysicalQuickSort
-------PhysicalProject
---------hashJoin[INNER_JOIN](dn.ss_customer_sk = customer.c_customer_sk)
-----------PhysicalProject
-------------PhysicalOlapScan[customer]
-----------PhysicalDistribute
-------------filter((dn.cnt <= 20)(dn.cnt >= 15))
---------------hashAgg[GLOBAL]
-----------------PhysicalDistribute
-------------------hashAgg[LOCAL]
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
-------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
---------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalQuickSort
+----PhysicalDistribute
+------PhysicalQuickSort
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](dn.ss_customer_sk = customer.c_customer_sk)
+------------PhysicalProject
+--------------PhysicalOlapScan[customer]
+------------PhysicalDistribute
+--------------filter((dn.cnt <= 20)(dn.cnt >= 15))
+----------------hashAgg[GLOBAL]
+------------------PhysicalDistribute
+--------------------hashAgg[LOCAL]
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[store_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 3)) OR ((date_dim.d_dom >= 25) AND (date_dim.d_dom <= 28)))d_year IN (1998, 1999, 2000))
+------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------filter((((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 3)) OR ((date_dim.d_dom >= 25) AND (date_dim.d_dom <= 28)))d_year IN (1998, 1999, 2000))
-----------------------------------PhysicalOlapScan[date_dim]
+--------------------------------filter(((cast(hd_buy_potential as VARCHAR(*)) = '1001-5000') OR (cast(hd_buy_potential as VARCHAR(*)) = '0-500'))(household_demographics.hd_vehicle_count > 0)(CASE WHEN (hd_vehicle_count > 0) THEN (cast(hd_dep_count as DOUBLE) / cast(hd_vehicle_count as DOUBLE)) ELSE NULL END > 1.2))
+----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter(((cast(hd_buy_potential as VARCHAR(*)) = '1001-5000') OR (cast(hd_buy_potential as VARCHAR(*)) = '0-500'))(household_demographics.hd_vehicle_count > 0)(CASE WHEN (hd_vehicle_count > 0) THEN (cast(hd_dep_count as DOUBLE) / cast(hd_vehicle_count as DOUBLE)) ELSE NULL END > 1.2))
---------------------------------PhysicalOlapScan[household_demographics]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter(s_county IN ('Ziebach County', 'Daviess County', 'Walker County', 'Richland County', 'Barrow County', 'Franklin Parish', 'Williamson County', 'Luce County'))
-------------------------------PhysicalOlapScan[store]
+------------------------------filter(s_county IN ('Ziebach County', 'Daviess County', 'Walker County', 'Richland County', 'Barrow County', 'Franklin Parish', 'Williamson County', 'Luce County'))
+--------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query35.out

@@ -1,58 +1,59 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_35 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------filter(($c$1 OR $c$2))
-------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = catalog_sales.cs_ship_customer_sk)
---------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = web_sales.ws_bill_customer_sk)
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = c.c_current_cdemo_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](c.c_current_addr_sk = ca.ca_address_sk)
-----------------------------------PhysicalDistribute
-------------------------------------hashJoin[RIGHT_SEMI_JOIN](c.c_customer_sk = store_sales.ss_customer_sk)
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[store_sales]
---------------------------------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------filter(($c$1 OR $c$2))
+--------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = catalog_sales.cs_ship_customer_sk)
+----------------------hashJoin[LEFT_SEMI_JOIN](c.c_customer_sk = web_sales.ws_bill_customer_sk)
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = c.c_current_cdemo_sk)
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](c.c_current_addr_sk = ca.ca_address_sk)
+------------------------------------PhysicalDistribute
+--------------------------------------hashJoin[RIGHT_SEMI_JOIN](c.c_customer_sk = store_sales.ss_customer_sk)
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_qoy < 4)(date_dim.d_year = 2001))
---------------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[customer]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[customer_address]
-----------------------------PhysicalDistribute
+------------------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((date_dim.d_qoy < 4)(date_dim.d_year = 2001))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[customer]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[customer_address]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[customer_demographics]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 ------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[customer_demographics]
+--------------------------------PhysicalOlapScan[web_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((date_dim.d_qoy < 4)(date_dim.d_year = 2001))
+------------------------------------PhysicalOlapScan[date_dim]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[web_sales]
+------------------------------PhysicalOlapScan[catalog_sales]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
 --------------------------------filter((date_dim.d_qoy < 4)(date_dim.d_year = 2001))
 ----------------------------------PhysicalOlapScan[date_dim]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[catalog_sales]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((date_dim.d_qoy < 4)(date_dim.d_year = 2001))
---------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query36.out

@@ -1,34 +1,35 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_36 --
-PhysicalProject
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------PhysicalWindow
-------------PhysicalQuickSort
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------hashAgg[GLOBAL]
---------------------PhysicalDistribute
-----------------------hashAgg[LOCAL]
-------------------------PhysicalRepeat
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
-----------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalProject
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------PhysicalWindow
+--------------PhysicalQuickSort
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashAgg[GLOBAL]
+----------------------PhysicalDistribute
+------------------------hashAgg[LOCAL]
+--------------------------PhysicalRepeat
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](item.i_item_sk = store_sales.ss_item_sk)
+------------------------------------hashJoin[INNER_JOIN](d1.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter((d1.d_year = 2002))
+--------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------------PhysicalDistribute
 --------------------------------------PhysicalProject
-----------------------------------------filter((d1.d_year = 2002))
-------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[item]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter(s_state IN ('SD', 'TN', 'GA', 'SC', 'MO', 'AL', 'MI', 'OH'))
-------------------------------------PhysicalOlapScan[store]
+----------------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter(s_state IN ('SD', 'TN', 'GA', 'SC', 'MO', 'AL', 'MI', 'OH'))
+--------------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query37.out

@@ -1,28 +1,29 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_37 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-----------------PhysicalProject
-------------------PhysicalOlapScan[catalog_sales]
-----------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = inventory.inv_date_sk)
-----------------------hashJoin[INNER_JOIN](inventory.inv_item_sk = item.i_item_sk)
-------------------------PhysicalProject
---------------------------filter((inventory.inv_quantity_on_hand >= 100)(inventory.inv_quantity_on_hand <= 500))
-----------------------------PhysicalOlapScan[inventory]
+--------------------PhysicalOlapScan[catalog_sales]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = inventory.inv_date_sk)
+------------------------hashJoin[INNER_JOIN](inventory.inv_item_sk = item.i_item_sk)
+--------------------------PhysicalProject
+----------------------------filter((inventory.inv_quantity_on_hand >= 100)(inventory.inv_quantity_on_hand <= 500))
+------------------------------PhysicalOlapScan[inventory]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((item.i_current_price <= 75.00)i_manufact_id IN (707, 747, 856, 1000)(item.i_current_price >= 45.00))
+--------------------------------PhysicalOlapScan[item]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((item.i_current_price <= 75.00)i_manufact_id IN (707, 747, 856, 1000)(item.i_current_price >= 45.00))
-------------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------filter((date_dim.d_date >= 1999-02-21)(date_dim.d_date <= 1999-04-22))
-----------------------------PhysicalOlapScan[date_dim]
+----------------------------filter((date_dim.d_date >= 1999-02-21)(date_dim.d_date <= 1999-04-22))
+------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query38.out

@@ -1,64 +1,65 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_38 --
-PhysicalLimit
+PhysicalResultSink
 --PhysicalLimit
-----hashAgg[GLOBAL]
-------PhysicalDistribute
---------hashAgg[LOCAL]
-----------PhysicalProject
-------------PhysicalIntersect
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store_sales]
---------------------------------PhysicalDistribute
+----PhysicalLimit
+------hashAgg[GLOBAL]
+--------PhysicalDistribute
+----------hashAgg[LOCAL]
+------------PhysicalProject
+--------------PhysicalIntersect
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
---------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[customer]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[catalog_sales]
---------------------------------PhysicalDistribute
+------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
+----------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[customer]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
---------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[customer]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_customer_sk = customer.c_customer_sk)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[web_sales]
---------------------------------PhysicalDistribute
+------------------------------------PhysicalOlapScan[catalog_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
+----------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[customer]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_customer_sk = customer.c_customer_sk)
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
---------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[customer]
+------------------------------------PhysicalOlapScan[web_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((date_dim.d_month_seq <= 1194)(date_dim.d_month_seq >= 1183))
+----------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[customer]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query39.out

@@ -22,17 +22,18 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[warehouse]
---PhysicalQuickSort
-----PhysicalDistribute
-------PhysicalQuickSort
---------PhysicalProject
-----------hashJoin[INNER_JOIN](inv1.w_warehouse_sk = inv2.w_warehouse_sk)(inv1.i_item_sk = inv2.i_item_sk)
-------------PhysicalDistribute
---------------PhysicalProject
-----------------filter((inv1.d_moy = 1))
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------PhysicalDistribute
---------------PhysicalProject
-----------------filter((inv2.d_moy = 2))
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--PhysicalResultSink
+----PhysicalQuickSort
+------PhysicalDistribute
+--------PhysicalQuickSort
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](inv1.w_warehouse_sk = inv2.w_warehouse_sk)(inv1.i_item_sk = inv2.i_item_sk)
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------filter((inv1.d_moy = 1))
+--------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------filter((inv2.d_moy = 2))
+--------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query4.out

@@ -60,40 +60,41 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 --------------------PhysicalProject
 ----------------------filter('w' IN ('c', 's', 'w')d_year IN (2000, 1999))
 ------------------------PhysicalOlapScan[date_dim]
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_secyear.customer_id)(CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END > CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END)
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_firstyear.customer_id)
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_c_secyear.customer_id)(CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END > CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END)
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN](t_s_secyear.customer_id = t_s_firstyear.customer_id)
-------------------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_c_firstyear.customer_id)
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((t_s_firstyear.year_total > 0.000000)(t_s_firstyear.dyear = 1999)(t_s_firstyear.sale_type = 's'))
---------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((t_c_firstyear.year_total > 0.000000)(t_c_firstyear.dyear = 1999)(t_c_firstyear.sale_type = 'c'))
---------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((t_s_secyear.sale_type = 's')(t_s_secyear.dyear = 2000))
-------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((t_c_secyear.sale_type = 'c')(t_c_secyear.dyear = 2000))
---------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------filter((t_w_firstyear.dyear = 1999)(t_w_firstyear.sale_type = 'w')(t_w_firstyear.year_total > 0.000000))
-----------------------PhysicalCteConsumer ( cteId=CTEId#0 )
-------------PhysicalDistribute
+--PhysicalResultSink
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_secyear.customer_id)(CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END > CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END)
 --------------PhysicalProject
-----------------filter((t_w_secyear.sale_type = 'w')(t_w_secyear.dyear = 2000))
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_w_firstyear.customer_id)
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_c_secyear.customer_id)(CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END > CASE WHEN (year_total > 0.000000) THEN (cast(year_total as DECIMALV3(38, 16)) / year_total) ELSE NULL END)
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN](t_s_secyear.customer_id = t_s_firstyear.customer_id)
+--------------------------hashJoin[INNER_JOIN](t_s_firstyear.customer_id = t_c_firstyear.customer_id)
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((t_s_firstyear.year_total > 0.000000)(t_s_firstyear.dyear = 1999)(t_s_firstyear.sale_type = 's'))
+----------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((t_c_firstyear.year_total > 0.000000)(t_c_firstyear.dyear = 1999)(t_c_firstyear.sale_type = 'c'))
+----------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((t_s_secyear.sale_type = 's')(t_s_secyear.dyear = 2000))
+--------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((t_c_secyear.sale_type = 'c')(t_c_secyear.dyear = 2000))
+----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((t_w_firstyear.dyear = 1999)(t_w_firstyear.sale_type = 'w')(t_w_firstyear.year_total > 0.000000))
+------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------filter((t_w_secyear.sale_type = 'w')(t_w_secyear.dyear = 2000))
+--------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query40.out

@@ -1,30 +1,31 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_40 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](catalog_sales.cs_warehouse_sk = warehouse.w_warehouse_sk)
-----------------PhysicalProject
-------------------hashJoin[RIGHT_OUTER_JOIN](catalog_sales.cs_item_sk = catalog_returns.cr_item_sk)(catalog_sales.cs_order_number = catalog_returns.cr_order_number)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[catalog_returns]
---------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-----------------------hashJoin[INNER_JOIN](item.i_item_sk = catalog_sales.cs_item_sk)
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[catalog_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](catalog_sales.cs_warehouse_sk = warehouse.w_warehouse_sk)
+------------------PhysicalProject
+--------------------hashJoin[RIGHT_OUTER_JOIN](catalog_sales.cs_item_sk = catalog_returns.cr_item_sk)(catalog_sales.cs_order_number = catalog_returns.cr_order_number)
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[catalog_returns]
+----------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+------------------------hashJoin[INNER_JOIN](item.i_item_sk = catalog_sales.cs_item_sk)
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[catalog_sales]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((item.i_current_price >= 0.99)(item.i_current_price <= 1.49))
+--------------------------------PhysicalOlapScan[item]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((item.i_current_price >= 0.99)(item.i_current_price <= 1.49))
-------------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------filter((date_dim.d_date >= 2001-03-03)(date_dim.d_date <= 2001-05-02))
-----------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[warehouse]
+----------------------------filter((date_dim.d_date >= 2001-03-03)(date_dim.d_date <= 2001-05-02))
+------------------------------PhysicalOlapScan[date_dim]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[warehouse]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query41.out

@@ -1,23 +1,24 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_41 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact = i1.i_manufact)
-----------------PhysicalProject
-------------------filter((i1.i_manufact_id >= 748)(i1.i_manufact_id <= 788))
---------------------PhysicalOlapScan[item]
-----------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[LEFT_SEMI_JOIN](item.i_manufact = i1.i_manufact)
 ------------------PhysicalProject
---------------------filter((item_cnt > 0))
-----------------------hashAgg[GLOBAL]
-------------------------PhysicalDistribute
---------------------------hashAgg[LOCAL]
-----------------------------PhysicalProject
-------------------------------filter((((((((((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'gainsboro') OR (cast(i_color as VARCHAR(*)) = 'aquamarine'))) AND ((cast(i_units as VARCHAR(*)) = 'Ounce') OR (cast(i_units as VARCHAR(*)) = 'Dozen'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy'))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'chiffon') OR (cast(i_color as VARCHAR(*)) = 'violet'))) AND ((cast(i_units as VARCHAR(*)) = 'Ton') OR (cast(i_units as VARCHAR(*)) = 'Pound'))) AND ((cast(i_size as VARCHAR(*)) = 'extra large') OR (cast(i_size as VARCHAR(*)) = 'small')))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'blanched') OR (cast(i_color as VARCHAR(*)) = 'tomato'))) AND ((cast(i_units as VARCHAR(*)) = 'Tbl') OR (cast(i_units as VARCHAR(*)) = 'Case'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'almond') OR (cast(i_color as VARCHAR(*)) = 'lime'))) AND ((cast(i_units as VARCHAR(*)) = 'Box') OR (cast(i_units as VARCHAR(*)) = 'Dram'))) AND ((cast(i_size as VARCHAR(*)) = 'extra large') OR (cast(i_size as VARCHAR(*)) = 'small')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'chartreuse') OR (cast(i_color as VARCHAR(*)) = 'blue'))) AND ((cast(i_units as VARCHAR(*)) = 'Each') OR (cast(i_units as VARCHAR(*)) = 'Oz'))) AND ((cast(i_size as VARCHAR(*)) = 'N/A') OR (cast(i_size as VARCHAR(*)) = 'large')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'tan') OR (cast(i_color as VARCHAR(*)) = 'dodger'))) AND ((cast(i_units as VARCHAR(*)) = 'Bunch') OR (cast(i_units as VARCHAR(*)) = 'Tsp'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'peru') OR (cast(i_color as VARCHAR(*)) = 'saddle'))) AND ((cast(i_units as VARCHAR(*)) = 'Pallet') OR (cast(i_units as VARCHAR(*)) = 'Gram'))) AND ((cast(i_size as VARCHAR(*)) = 'N/A') OR (cast(i_size as VARCHAR(*)) = 'large')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'indian') OR (cast(i_color as VARCHAR(*)) = 'spring'))) AND ((cast(i_units as VARCHAR(*)) = 'Unknown') OR (cast(i_units as VARCHAR(*)) = 'Carton'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))))
---------------------------------PhysicalOlapScan[item]
+--------------------filter((i1.i_manufact_id >= 748)(i1.i_manufact_id <= 788))
+----------------------PhysicalOlapScan[item]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((item_cnt > 0))
+------------------------hashAgg[GLOBAL]
+--------------------------PhysicalDistribute
+----------------------------hashAgg[LOCAL]
+------------------------------PhysicalProject
+--------------------------------filter((((((((((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'gainsboro') OR (cast(i_color as VARCHAR(*)) = 'aquamarine'))) AND ((cast(i_units as VARCHAR(*)) = 'Ounce') OR (cast(i_units as VARCHAR(*)) = 'Dozen'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy'))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'chiffon') OR (cast(i_color as VARCHAR(*)) = 'violet'))) AND ((cast(i_units as VARCHAR(*)) = 'Ton') OR (cast(i_units as VARCHAR(*)) = 'Pound'))) AND ((cast(i_size as VARCHAR(*)) = 'extra large') OR (cast(i_size as VARCHAR(*)) = 'small')))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'blanched') OR (cast(i_color as VARCHAR(*)) = 'tomato'))) AND ((cast(i_units as VARCHAR(*)) = 'Tbl') OR (cast(i_units as VARCHAR(*)) = 'Case'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))) OR ((((cast(i_category as VARCHAR(*)) = 'Women') AND ((cast(i_color as VARCHAR(*)) = 'almond') OR (cast(i_color as VARCHAR(*)) = 'lime'))) AND ((cast(i_units as VARCHAR(*)) = 'Box') OR (cast(i_units as VARCHAR(*)) = 'Dram'))) AND ((cast(i_size as VARCHAR(*)) = 'extra large') OR (cast(i_size as VARCHAR(*)) = 'small')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'chartreuse') OR (cast(i_color as VARCHAR(*)) = 'blue'))) AND ((cast(i_units as VARCHAR(*)) = 'Each') OR (cast(i_units as VARCHAR(*)) = 'Oz'))) AND ((cast(i_size as VARCHAR(*)) = 'N/A') OR (cast(i_size as VARCHAR(*)) = 'large')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'tan') OR (cast(i_color as VARCHAR(*)) = 'dodger'))) AND ((cast(i_units as VARCHAR(*)) = 'Bunch') OR (cast(i_units as VARCHAR(*)) = 'Tsp'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'peru') OR (cast(i_color as VARCHAR(*)) = 'saddle'))) AND ((cast(i_units as VARCHAR(*)) = 'Pallet') OR (cast(i_units as VARCHAR(*)) = 'Gram'))) AND ((cast(i_size as VARCHAR(*)) = 'N/A') OR (cast(i_size as VARCHAR(*)) = 'large')))) OR ((((cast(i_category as VARCHAR(*)) = 'Men') AND ((cast(i_color as VARCHAR(*)) = 'indian') OR (cast(i_color as VARCHAR(*)) = 'spring'))) AND ((cast(i_units as VARCHAR(*)) = 'Unknown') OR (cast(i_units as VARCHAR(*)) = 'Carton'))) AND ((cast(i_size as VARCHAR(*)) = 'medium') OR (cast(i_size as VARCHAR(*)) = 'economy')))))
+----------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query42.out

@@ -1,22 +1,23 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_42 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
-----------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-------------------PhysicalProject
---------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
+------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[store_sales]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter((item.i_manager_id = 1))
+--------------------------PhysicalOlapScan[item]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------filter((item.i_manager_id = 1))
-------------------------PhysicalOlapScan[item]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------filter((dt.d_year = 2002)(dt.d_moy = 11))
-----------------------PhysicalOlapScan[date_dim]
+----------------------filter((dt.d_year = 2002)(dt.d_moy = 11))
+------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query43.out

@@ -1,22 +1,23 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_43 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-----------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
-------------------PhysicalProject
---------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[store_sales]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter((date_dim.d_year = 2000))
+--------------------------PhysicalOlapScan[date_dim]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------filter((date_dim.d_year = 2000))
-------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------filter((store.s_gmt_offset = -5.00))
-----------------------PhysicalOlapScan[store]
+----------------------filter((store.s_gmt_offset = -5.00))
+------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query44.out

@@ -1,17 +1,44 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_44 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashJoin[INNER_JOIN](i1.i_item_sk = asceding.item_sk)
-----------PhysicalProject
-------------PhysicalOlapScan[item]
-----------PhysicalDistribute
-------------hashJoin[INNER_JOIN](asceding.rnk = descending.rnk)
---------------hashJoin[INNER_JOIN](i2.i_item_sk = descending.item_sk)
-----------------PhysicalProject
-------------------PhysicalOlapScan[item]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](i1.i_item_sk = asceding.item_sk)
+------------PhysicalProject
+--------------PhysicalOlapScan[item]
+------------PhysicalDistribute
+--------------hashJoin[INNER_JOIN](asceding.rnk = descending.rnk)
+----------------hashJoin[INNER_JOIN](i2.i_item_sk = descending.item_sk)
+------------------PhysicalProject
+--------------------PhysicalOlapScan[item]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter((rnk < 11))
+------------------------PhysicalWindow
+--------------------------PhysicalQuickSort
+----------------------------PhysicalDistribute
+------------------------------PhysicalQuickSort
+--------------------------------PhysicalPartitionTopN
+----------------------------------PhysicalProject
+------------------------------------NestedLoopJoin[INNER_JOIN](cast(rank_col as DOUBLE) > cast((0.9 * rank_col) as DOUBLE))
+--------------------------------------hashAgg[GLOBAL]
+----------------------------------------PhysicalDistribute
+------------------------------------------hashAgg[LOCAL]
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((ss1.ss_store_sk = 146))
+------------------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalAssertNumRows
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------hashAgg[GLOBAL]
+------------------------------------------------PhysicalDistribute
+--------------------------------------------------hashAgg[LOCAL]
+----------------------------------------------------PhysicalProject
+------------------------------------------------------filter(ss_addr_sk IS NULL(store_sales.ss_store_sk = 146))
+--------------------------------------------------------PhysicalOlapScan[store_sales]
 ----------------PhysicalDistribute
 ------------------PhysicalProject
 --------------------filter((rnk < 11))
@@ -38,30 +65,4 @@ PhysicalTopN
 --------------------------------------------------PhysicalProject
 ----------------------------------------------------filter(ss_addr_sk IS NULL(store_sales.ss_store_sk = 146))
 ------------------------------------------------------PhysicalOlapScan[store_sales]
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------filter((rnk < 11))
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------PhysicalQuickSort
-----------------------------PhysicalPartitionTopN
-------------------------------PhysicalProject
---------------------------------NestedLoopJoin[INNER_JOIN](cast(rank_col as DOUBLE) > cast((0.9 * rank_col) as DOUBLE))
-----------------------------------hashAgg[GLOBAL]
-------------------------------------PhysicalDistribute
---------------------------------------hashAgg[LOCAL]
-----------------------------------------PhysicalProject
-------------------------------------------filter((ss1.ss_store_sk = 146))
---------------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalAssertNumRows
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------hashAgg[GLOBAL]
---------------------------------------------PhysicalDistribute
-----------------------------------------------hashAgg[LOCAL]
-------------------------------------------------PhysicalProject
---------------------------------------------------filter(ss_addr_sk IS NULL(store_sales.ss_store_sk = 146))
-----------------------------------------------------PhysicalOlapScan[store_sales]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query45.out

@@ -1,41 +1,42 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_45 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------filter((substring(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') OR $c$1))
-----------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](web_sales.ws_bill_customer_sk = customer.c_customer_sk)
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-----------------------------PhysicalDistribute
-------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[web_sales]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_qoy = 2)(date_dim.d_year = 2000))
---------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[customer]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[customer_address]
-------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------filter((substring(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') OR $c$1))
+------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
 --------------------PhysicalProject
-----------------------filter(i_item_sk IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29))
-------------------------PhysicalOlapScan[item]
+----------------------hashJoin[INNER_JOIN](web_sales.ws_bill_customer_sk = customer.c_customer_sk)
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+------------------------------PhysicalDistribute
+--------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[web_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((date_dim.d_qoy = 2)(date_dim.d_year = 2000))
+----------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = customer_address.ca_address_sk)
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[customer]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[customer_address]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------filter(i_item_sk IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29))
+--------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query46.out

@@ -1,42 +1,43 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_46 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashJoin[INNER_JOIN](dn.ss_customer_sk = customer.c_customer_sk)( not (ca_city = bought_city))
-----------PhysicalDistribute
-------------PhysicalProject
---------------hashAgg[LOCAL]
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
---------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](dn.ss_customer_sk = customer.c_customer_sk)( not (ca_city = bought_city))
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------hashAgg[LOCAL]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[store_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter(d_dow IN (0, 6)d_year IN (1999, 2000, 2001))
+--------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter(d_dow IN (0, 6)d_year IN (1999, 2000, 2001))
-------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------filter(((household_demographics.hd_dep_count = 6) OR (household_demographics.hd_vehicle_count = 0)))
+------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------filter(((household_demographics.hd_dep_count = 6) OR (household_demographics.hd_vehicle_count = 0)))
-----------------------------------PhysicalOlapScan[household_demographics]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter(s_city IN ('Five Points', 'Centerville', 'Oak Grove', 'Fairview', 'Liberty'))
---------------------------------PhysicalOlapScan[store]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[customer_address]
-----------PhysicalDistribute
-------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = current_addr.ca_address_sk)
---------------PhysicalProject
-----------------PhysicalOlapScan[customer_address]
---------------PhysicalDistribute
+--------------------------------filter(s_city IN ('Five Points', 'Centerville', 'Oak Grove', 'Fairview', 'Liberty'))
+----------------------------------PhysicalOlapScan[store]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[customer_address]
+------------PhysicalDistribute
+--------------hashJoin[INNER_JOIN](customer.c_current_addr_sk = current_addr.ca_address_sk)
 ----------------PhysicalProject
-------------------PhysicalOlapScan[customer]
+------------------PhysicalOlapScan[customer_address]
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------PhysicalOlapScan[customer]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query47.out

@@ -29,23 +29,24 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[store]
---PhysicalProject
-----PhysicalTopN
-------PhysicalDistribute
---------PhysicalTopN
-----------PhysicalProject
-------------hashJoin[INNER_JOIN](v1.i_category = v1_lead.i_category)(v1.i_brand = v1_lead.i_brand)(v1.s_store_name = v1_lead.s_store_name)(v1.s_company_name = v1_lead.s_company_name)(v1.rn = expr_(rn - 1))
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](v1.i_category = v1_lag.i_category)(v1.i_brand = v1_lag.i_brand)(v1.s_store_name = v1_lag.s_store_name)(v1.s_company_name = v1_lag.s_company_name)(v1.rn = expr_(rn + 1))
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1)(v2.d_year = 2001)(v2.avg_monthly_sales > 0.0000))
+--PhysicalResultSink
+----PhysicalProject
+------PhysicalTopN
+--------PhysicalDistribute
+----------PhysicalTopN
+------------PhysicalProject
+--------------hashJoin[INNER_JOIN](v1.i_category = v1_lead.i_category)(v1.i_brand = v1_lead.i_brand)(v1.s_store_name = v1_lead.s_store_name)(v1.s_company_name = v1_lead.s_company_name)(v1.rn = expr_(rn - 1))
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](v1.i_category = v1_lag.i_category)(v1.i_brand = v1_lag.i_brand)(v1.s_store_name = v1_lag.s_store_name)(v1.s_company_name = v1_lag.s_company_name)(v1.rn = expr_(rn + 1))
+----------------------PhysicalDistribute
+------------------------PhysicalProject
 --------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1)(v2.d_year = 2001)(v2.avg_monthly_sales > 0.0000))
+----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out

@@ -1,31 +1,32 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_48 --
-hashAgg[GLOBAL]
---PhysicalDistribute
-----hashAgg[LOCAL]
-------PhysicalProject
---------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
-----------PhysicalProject
-------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)(((ca_state IN ('MD', 'MN', 'IA') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('VA', 'IL', 'TX') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('MI', 'WI', 'IN') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))
-----------------PhysicalDistribute
-------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)(((((cast(cd_marital_status as VARCHAR(*)) = 'U') AND (cast(cd_education_status as VARCHAR(*)) = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((cast(cd_marital_status as VARCHAR(*)) = 'W') AND (cast(cd_education_status as VARCHAR(*)) = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
---------------------PhysicalProject
-----------------------filter(((((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00)))((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
-------------------------PhysicalOlapScan[store_sales]
---------------------PhysicalDistribute
+PhysicalResultSink
+--hashAgg[GLOBAL]
+----PhysicalDistribute
+------hashAgg[LOCAL]
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](store.s_store_sk = store_sales.ss_store_sk)
+------------PhysicalProject
+--------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+----------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)(((ca_state IN ('MD', 'MN', 'IA') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('VA', 'IL', 'TX') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('MI', 'WI', 'IN') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))
+------------------PhysicalDistribute
+--------------------hashJoin[INNER_JOIN](customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)(((((cast(cd_marital_status as VARCHAR(*)) = 'U') AND (cast(cd_education_status as VARCHAR(*)) = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((cast(cd_marital_status as VARCHAR(*)) = 'W') AND (cast(cd_education_status as VARCHAR(*)) = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
 ----------------------PhysicalProject
-------------------------filter(((((cast(cd_marital_status as VARCHAR(*)) = 'U') AND (cast(cd_education_status as VARCHAR(*)) = 'Primary')) OR ((cast(cd_marital_status as VARCHAR(*)) = 'W') AND (cast(cd_education_status as VARCHAR(*)) = 'College'))) OR ((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = '2 yr Degree'))))
---------------------------PhysicalOlapScan[customer_demographics]
+------------------------filter(((((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00)))((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
+--------------------------PhysicalOlapScan[store_sales]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter(((((cast(cd_marital_status as VARCHAR(*)) = 'U') AND (cast(cd_education_status as VARCHAR(*)) = 'Primary')) OR ((cast(cd_marital_status as VARCHAR(*)) = 'W') AND (cast(cd_education_status as VARCHAR(*)) = 'College'))) OR ((cast(cd_marital_status as VARCHAR(*)) = 'D') AND (cast(cd_education_status as VARCHAR(*)) = '2 yr Degree'))))
+----------------------------PhysicalOlapScan[customer_demographics]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------filter(((ca_state IN ('MD', 'MN', 'IA') OR ca_state IN ('VA', 'IL', 'TX')) OR ca_state IN ('MI', 'WI', 'IN'))(customer_address.ca_country = 'United States'))
+------------------------PhysicalOlapScan[customer_address]
 ----------------PhysicalDistribute
 ------------------PhysicalProject
---------------------filter(((ca_state IN ('MD', 'MN', 'IA') OR ca_state IN ('VA', 'IL', 'TX')) OR ca_state IN ('MI', 'WI', 'IN'))(customer_address.ca_country = 'United States'))
-----------------------PhysicalOlapScan[customer_address]
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------filter((date_dim.d_year = 1999))
---------------------PhysicalOlapScan[date_dim]
-----------PhysicalDistribute
-------------PhysicalProject
---------------PhysicalOlapScan[store]
+--------------------filter((date_dim.d_year = 1999))
+----------------------PhysicalOlapScan[date_dim]
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query49.out

@@ -1,86 +1,87 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_49 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[LOCAL]
---------PhysicalUnion
-----------PhysicalDistribute
-------------PhysicalProject
---------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
-----------------PhysicalWindow
-------------------PhysicalQuickSort
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------PhysicalQuickSort
-----------------------------PhysicalProject
-------------------------------hashAgg[GLOBAL]
---------------------------------PhysicalDistribute
-----------------------------------hashAgg[LOCAL]
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](ws.ws_order_number = wr.wr_order_number)(item = wr.wr_item_sk)
-----------------------------------------PhysicalProject
-------------------------------------------filter((wr.wr_return_amt > 10000.00))
---------------------------------------------PhysicalOlapScan[web_returns]
-----------------------------------------hashJoin[INNER_JOIN](ws.ws_sold_date_sk = date_dim.d_date_sk)
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[LOCAL]
+----------PhysicalUnion
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
+------------------PhysicalWindow
+--------------------PhysicalQuickSort
+----------------------PhysicalWindow
+------------------------PhysicalQuickSort
+--------------------------PhysicalDistribute
+----------------------------PhysicalQuickSort
+------------------------------PhysicalProject
+--------------------------------hashAgg[GLOBAL]
+----------------------------------PhysicalDistribute
+------------------------------------hashAgg[LOCAL]
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](ws.ws_order_number = wr.wr_order_number)(item = wr.wr_item_sk)
 ------------------------------------------PhysicalProject
---------------------------------------------filter((ws.ws_net_paid > 0.00)(ws.ws_quantity > 0)(ws.ws_net_profit > 1.00))
-----------------------------------------------PhysicalOlapScan[web_sales]
-------------------------------------------PhysicalDistribute
+--------------------------------------------filter((wr.wr_return_amt > 10000.00))
+----------------------------------------------PhysicalOlapScan[web_returns]
+------------------------------------------hashJoin[INNER_JOIN](ws.ws_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------------PhysicalProject
-----------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
-------------------------------------------------PhysicalOlapScan[date_dim]
-----------PhysicalDistribute
-------------PhysicalProject
---------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
-----------------PhysicalWindow
-------------------PhysicalQuickSort
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------PhysicalQuickSort
-----------------------------PhysicalProject
-------------------------------hashAgg[GLOBAL]
---------------------------------PhysicalDistribute
-----------------------------------hashAgg[LOCAL]
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](cs.cs_order_number = cr.cr_order_number)(item = cr.cr_item_sk)
-----------------------------------------PhysicalProject
-------------------------------------------filter((cr.cr_return_amount > 10000.00))
---------------------------------------------PhysicalOlapScan[catalog_returns]
-----------------------------------------hashJoin[INNER_JOIN](cs.cs_sold_date_sk = date_dim.d_date_sk)
+----------------------------------------------filter((ws.ws_net_paid > 0.00)(ws.ws_quantity > 0)(ws.ws_net_profit > 1.00))
+------------------------------------------------PhysicalOlapScan[web_sales]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalProject
+------------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
+--------------------------------------------------PhysicalOlapScan[date_dim]
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
+------------------PhysicalWindow
+--------------------PhysicalQuickSort
+----------------------PhysicalWindow
+------------------------PhysicalQuickSort
+--------------------------PhysicalDistribute
+----------------------------PhysicalQuickSort
+------------------------------PhysicalProject
+--------------------------------hashAgg[GLOBAL]
+----------------------------------PhysicalDistribute
+------------------------------------hashAgg[LOCAL]
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](cs.cs_order_number = cr.cr_order_number)(item = cr.cr_item_sk)
 ------------------------------------------PhysicalProject
---------------------------------------------filter((cs.cs_net_paid > 0.00)(cs.cs_quantity > 0)(cs.cs_net_profit > 1.00))
-----------------------------------------------PhysicalOlapScan[catalog_sales]
-------------------------------------------PhysicalDistribute
+--------------------------------------------filter((cr.cr_return_amount > 10000.00))
+----------------------------------------------PhysicalOlapScan[catalog_returns]
+------------------------------------------hashJoin[INNER_JOIN](cs.cs_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------------PhysicalProject
-----------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
-------------------------------------------------PhysicalOlapScan[date_dim]
-----------PhysicalDistribute
-------------PhysicalProject
---------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
-----------------PhysicalWindow
-------------------PhysicalQuickSort
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------PhysicalQuickSort
-----------------------------PhysicalProject
-------------------------------hashAgg[GLOBAL]
---------------------------------PhysicalDistribute
-----------------------------------hashAgg[LOCAL]
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](sts.ss_ticket_number = sr.sr_ticket_number)(item = sr.sr_item_sk)
-----------------------------------------PhysicalProject
-------------------------------------------filter((sr.sr_return_amt > 10000.00))
---------------------------------------------PhysicalOlapScan[store_returns]
-----------------------------------------hashJoin[INNER_JOIN](sts.ss_sold_date_sk = date_dim.d_date_sk)
+----------------------------------------------filter((cs.cs_net_paid > 0.00)(cs.cs_quantity > 0)(cs.cs_net_profit > 1.00))
+------------------------------------------------PhysicalOlapScan[catalog_sales]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalProject
+------------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
+--------------------------------------------------PhysicalOlapScan[date_dim]
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------filter(((return_rank <= 10) OR (currency_rank <= 10)))
+------------------PhysicalWindow
+--------------------PhysicalQuickSort
+----------------------PhysicalWindow
+------------------------PhysicalQuickSort
+--------------------------PhysicalDistribute
+----------------------------PhysicalQuickSort
+------------------------------PhysicalProject
+--------------------------------hashAgg[GLOBAL]
+----------------------------------PhysicalDistribute
+------------------------------------hashAgg[LOCAL]
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](sts.ss_ticket_number = sr.sr_ticket_number)(item = sr.sr_item_sk)
 ------------------------------------------PhysicalProject
---------------------------------------------filter((sts.ss_quantity > 0)(sts.ss_net_profit > 1.00)(sts.ss_net_paid > 0.00))
-----------------------------------------------PhysicalOlapScan[store_sales]
-------------------------------------------PhysicalDistribute
+--------------------------------------------filter((sr.sr_return_amt > 10000.00))
+----------------------------------------------PhysicalOlapScan[store_returns]
+------------------------------------------hashJoin[INNER_JOIN](sts.ss_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------------PhysicalProject
-----------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
-------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------------filter((sts.ss_quantity > 0)(sts.ss_net_profit > 1.00)(sts.ss_net_paid > 0.00))
+------------------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------PhysicalProject
+------------------------------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 1999))
+--------------------------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query5.out

@@ -1,79 +1,80 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_5 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalRepeat
-----------------PhysicalUnion
-------------------PhysicalProject
---------------------hashAgg[GLOBAL]
-----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](salesreturns.store_sk = store.s_store_sk)
-------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
---------------------------------PhysicalUnion
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalRepeat
+------------------PhysicalUnion
+--------------------PhysicalProject
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](salesreturns.store_sk = store.s_store_sk)
+--------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
+----------------------------------PhysicalUnion
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[store_returns]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[store_returns]
+--------------------------------------filter((date_dim.d_date <= 2000-09-02)(date_dim.d_date >= 2000-08-19))
+----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_date <= 2000-09-02)(date_dim.d_date >= 2000-08-19))
---------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store]
-------------------PhysicalProject
---------------------hashAgg[GLOBAL]
-----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](salesreturns.page_sk = catalog_page.cp_catalog_page_sk)
-------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
---------------------------------PhysicalUnion
+------------------------------------PhysicalOlapScan[store]
+--------------------PhysicalProject
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](salesreturns.page_sk = catalog_page.cp_catalog_page_sk)
+--------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
+----------------------------------PhysicalUnion
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[catalog_returns]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[catalog_returns]
+--------------------------------------filter((date_dim.d_date >= 2000-08-19)(date_dim.d_date <= 2000-09-02))
+----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_date >= 2000-08-19)(date_dim.d_date <= 2000-09-02))
---------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[catalog_page]
-------------------PhysicalProject
---------------------hashAgg[GLOBAL]
-----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](salesreturns.wsr_web_site_sk = web_site.web_site_sk)
-------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
---------------------------------PhysicalUnion
+------------------------------------PhysicalOlapScan[catalog_page]
+--------------------PhysicalProject
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](salesreturns.wsr_web_site_sk = web_site.web_site_sk)
+--------------------------------hashJoin[INNER_JOIN](salesreturns.date_sk = date_dim.d_date_sk)
+----------------------------------PhysicalUnion
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](web_returns.wr_item_sk = web_sales.ws_item_sk)(web_returns.wr_order_number = web_sales.ws_order_number)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[web_returns]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[web_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](web_returns.wr_item_sk = web_sales.ws_item_sk)(web_returns.wr_order_number = web_sales.ws_order_number)
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[web_sales]
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[web_returns]
+--------------------------------------filter((date_dim.d_date >= 2000-08-19)(date_dim.d_date <= 2000-09-02))
+----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_date >= 2000-08-19)(date_dim.d_date <= 2000-09-02))
---------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[web_site]
+------------------------------------PhysicalOlapScan[web_site]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query50.out

@@ -1,31 +1,32 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_50 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = d1.d_date_sk)
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[date_dim]
-----------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = d1.d_date_sk)
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store_sales]
-----------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
+--------------------------PhysicalOlapScan[date_dim]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = store_returns.sr_item_sk)(store_sales.ss_ticket_number = store_returns.sr_ticket_number)(store_sales.ss_customer_sk = store_returns.sr_customer_sk)
 ------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store_returns]
-------------------------------PhysicalDistribute
+--------------------------------PhysicalOlapScan[store_sales]
+------------------------------hashJoin[INNER_JOIN](store_returns.sr_returned_date_sk = d2.d_date_sk)
 --------------------------------PhysicalProject
-----------------------------------filter((d2.d_year = 2001)(d2.d_moy = 8))
-------------------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[store]
+----------------------------------PhysicalOlapScan[store_returns]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((d2.d_year = 2001)(d2.d_moy = 8))
+--------------------------------------PhysicalOlapScan[date_dim]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query51.out

@@ -1,42 +1,43 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_51 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------filter((web_cumulative > store_cumulative))
---------PhysicalWindow
-----------PhysicalQuickSort
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[FULL_OUTER_JOIN](web.item_sk = store.item_sk)(web.d_date = store.d_date)
-------------------PhysicalProject
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------hashAgg[GLOBAL]
-----------------------------PhysicalDistribute
-------------------------------hashAgg[LOCAL]
---------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[store_sales]
-------------------------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------filter((web_cumulative > store_cumulative))
+----------PhysicalWindow
+------------PhysicalQuickSort
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[FULL_OUTER_JOIN](web.item_sk = store.item_sk)(web.d_date = store.d_date)
+--------------------PhysicalProject
+----------------------PhysicalWindow
+------------------------PhysicalQuickSort
+--------------------------PhysicalDistribute
+----------------------------hashAgg[GLOBAL]
+------------------------------PhysicalDistribute
+--------------------------------hashAgg[LOCAL]
+----------------------------------PhysicalProject
+------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------PhysicalProject
-----------------------------------------filter((date_dim.d_month_seq <= 1227)(date_dim.d_month_seq >= 1216))
-------------------------------------------PhysicalOlapScan[date_dim]
-------------------PhysicalProject
---------------------PhysicalWindow
-----------------------PhysicalQuickSort
-------------------------PhysicalDistribute
---------------------------hashAgg[GLOBAL]
-----------------------------PhysicalDistribute
-------------------------------hashAgg[LOCAL]
---------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[web_sales]
-------------------------------------PhysicalDistribute
+----------------------------------------PhysicalOlapScan[store_sales]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter((date_dim.d_month_seq <= 1227)(date_dim.d_month_seq >= 1216))
+--------------------------------------------PhysicalOlapScan[date_dim]
+--------------------PhysicalProject
+----------------------PhysicalWindow
+------------------------PhysicalQuickSort
+--------------------------PhysicalDistribute
+----------------------------hashAgg[GLOBAL]
+------------------------------PhysicalDistribute
+--------------------------------hashAgg[LOCAL]
+----------------------------------PhysicalProject
+------------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 --------------------------------------PhysicalProject
-----------------------------------------filter((date_dim.d_month_seq >= 1216)(date_dim.d_month_seq <= 1227))
-------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------------PhysicalOlapScan[web_sales]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter((date_dim.d_month_seq >= 1216)(date_dim.d_month_seq <= 1227))
+--------------------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query52.out

@@ -1,23 +1,24 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_52 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
-------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](dt.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[store_sales]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((item.i_manager_id = 1))
+----------------------------PhysicalOlapScan[item]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((item.i_manager_id = 1))
---------------------------PhysicalOlapScan[item]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((dt.d_moy = 12)(dt.d_year = 2002))
-------------------------PhysicalOlapScan[date_dim]
+------------------------filter((dt.d_moy = 12)(dt.d_year = 2002))
+--------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query53.out

@@ -1,33 +1,34 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_53 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------filter((CASE WHEN (avg_quarterly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_quarterly_sales as DOUBLE))) / cast(avg_quarterly_sales as DOUBLE)) ELSE NULL END > 0.1))
-----------PhysicalWindow
-------------PhysicalQuickSort
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------hashAgg[GLOBAL]
---------------------PhysicalDistribute
-----------------------hashAgg[LOCAL]
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------filter((CASE WHEN (avg_quarterly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_quarterly_sales as DOUBLE))) / cast(avg_quarterly_sales as DOUBLE)) ELSE NULL END > 0.1))
+------------PhysicalWindow
+--------------PhysicalQuickSort
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashAgg[GLOBAL]
+----------------------PhysicalDistribute
+------------------------hashAgg[LOCAL]
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) OR ((i_category IN ('Women', 'Music', 'Men') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
+------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) OR ((i_category IN ('Women', 'Music', 'Men') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
-----------------------------------------PhysicalOlapScan[item]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
---------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store]
+--------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
+----------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query54.out

@@ -1,82 +1,83 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_54 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](customer_address.ca_county = store.s_county)(customer_address.ca_state = store.s_state)
---------------------------PhysicalProject
-----------------------------NestedLoopJoin[INNER_JOIN](cast(d_month_seq as BIGINT) <= (d_month_seq + 3))
-------------------------------PhysicalProject
---------------------------------NestedLoopJoin[INNER_JOIN](cast(d_month_seq as BIGINT) >= (d_month_seq + 1))
-----------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](my_customers.c_customer_sk = store_sales.ss_customer_sk)
-----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------------PhysicalDistribute
-------------------------------------------hashJoin[INNER_JOIN](my_customers.c_current_addr_sk = customer_address.ca_address_sk)
---------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[customer_address]
---------------------------------------------PhysicalDistribute
-----------------------------------------------PhysicalProject
-------------------------------------------------hashAgg[GLOBAL]
---------------------------------------------------PhysicalDistribute
-----------------------------------------------------hashAgg[LOCAL]
-------------------------------------------------------PhysicalProject
---------------------------------------------------------hashJoin[INNER_JOIN](customer.c_customer_sk = cs_or_ws_sales.customer_sk)
-----------------------------------------------------------PhysicalProject
-------------------------------------------------------------PhysicalOlapScan[customer]
-----------------------------------------------------------PhysicalDistribute
-------------------------------------------------------------PhysicalProject
---------------------------------------------------------------hashJoin[INNER_JOIN](cs_or_ws_sales.sold_date_sk = date_dim.d_date_sk)
-----------------------------------------------------------------PhysicalProject
-------------------------------------------------------------------hashJoin[INNER_JOIN](cs_or_ws_sales.item_sk = item.i_item_sk)
---------------------------------------------------------------------PhysicalUnion
-----------------------------------------------------------------------PhysicalDistribute
-------------------------------------------------------------------------PhysicalProject
---------------------------------------------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------------------------------------------PhysicalDistribute
-------------------------------------------------------------------------PhysicalProject
---------------------------------------------------------------------------PhysicalOlapScan[web_sales]
---------------------------------------------------------------------PhysicalDistribute
-----------------------------------------------------------------------PhysicalProject
-------------------------------------------------------------------------filter((cast(i_class as VARCHAR(*)) = 'maternity')(cast(i_category as VARCHAR(*)) = 'Women'))
---------------------------------------------------------------------------PhysicalOlapScan[item]
-----------------------------------------------------------------PhysicalDistribute
-------------------------------------------------------------------PhysicalProject
---------------------------------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
-----------------------------------------------------------------------PhysicalOlapScan[date_dim]
-------------------------------------PhysicalDistribute
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalAssertNumRows
---------------------------------------PhysicalDistribute
-----------------------------------------hashAgg[GLOBAL]
-------------------------------------------PhysicalDistribute
---------------------------------------------hashAgg[LOCAL]
-----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
---------------------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalAssertNumRows
-----------------------------------PhysicalDistribute
-------------------------------------hashAgg[GLOBAL]
---------------------------------------PhysicalDistribute
-----------------------------------------hashAgg[LOCAL]
-------------------------------------------PhysicalProject
---------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
-----------------------------------------------PhysicalOlapScan[date_dim]
---------------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](customer_address.ca_county = store.s_county)(customer_address.ca_state = store.s_state)
 ----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store]
+------------------------------NestedLoopJoin[INNER_JOIN](cast(d_month_seq as BIGINT) <= (d_month_seq + 3))
+--------------------------------PhysicalProject
+----------------------------------NestedLoopJoin[INNER_JOIN](cast(d_month_seq as BIGINT) >= (d_month_seq + 1))
+------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](my_customers.c_customer_sk = store_sales.ss_customer_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashJoin[INNER_JOIN](my_customers.c_current_addr_sk = customer_address.ca_address_sk)
+----------------------------------------------PhysicalProject
+------------------------------------------------PhysicalOlapScan[customer_address]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------hashAgg[GLOBAL]
+----------------------------------------------------PhysicalDistribute
+------------------------------------------------------hashAgg[LOCAL]
+--------------------------------------------------------PhysicalProject
+----------------------------------------------------------hashJoin[INNER_JOIN](customer.c_customer_sk = cs_or_ws_sales.customer_sk)
+------------------------------------------------------------PhysicalProject
+--------------------------------------------------------------PhysicalOlapScan[customer]
+------------------------------------------------------------PhysicalDistribute
+--------------------------------------------------------------PhysicalProject
+----------------------------------------------------------------hashJoin[INNER_JOIN](cs_or_ws_sales.sold_date_sk = date_dim.d_date_sk)
+------------------------------------------------------------------PhysicalProject
+--------------------------------------------------------------------hashJoin[INNER_JOIN](cs_or_ws_sales.item_sk = item.i_item_sk)
+----------------------------------------------------------------------PhysicalUnion
+------------------------------------------------------------------------PhysicalDistribute
+--------------------------------------------------------------------------PhysicalProject
+----------------------------------------------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------------------------------------------PhysicalDistribute
+--------------------------------------------------------------------------PhysicalProject
+----------------------------------------------------------------------------PhysicalOlapScan[web_sales]
+----------------------------------------------------------------------PhysicalDistribute
+------------------------------------------------------------------------PhysicalProject
+--------------------------------------------------------------------------filter((cast(i_class as VARCHAR(*)) = 'maternity')(cast(i_category as VARCHAR(*)) = 'Women'))
+----------------------------------------------------------------------------PhysicalOlapScan[item]
+------------------------------------------------------------------PhysicalDistribute
+--------------------------------------------------------------------PhysicalProject
+----------------------------------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
+------------------------------------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalAssertNumRows
+----------------------------------------PhysicalDistribute
+------------------------------------------hashAgg[GLOBAL]
+--------------------------------------------PhysicalDistribute
+----------------------------------------------hashAgg[LOCAL]
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
+----------------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalAssertNumRows
+------------------------------------PhysicalDistribute
+--------------------------------------hashAgg[GLOBAL]
+----------------------------------------PhysicalDistribute
+------------------------------------------hashAgg[LOCAL]
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((date_dim.d_year = 1998)(date_dim.d_moy = 5))
+------------------------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query55.out

@@ -1,23 +1,24 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_55 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
-------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](date_dim.d_date_sk = store_sales.ss_sold_date_sk)
+--------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[store_sales]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((item.i_manager_id = 100))
+----------------------------PhysicalOlapScan[item]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((item.i_manager_id = 100))
---------------------------PhysicalOlapScan[item]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 2000))
-------------------------PhysicalOlapScan[date_dim]
+------------------------filter((date_dim.d_moy = 12)(date_dim.d_year = 2000))
+--------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query56.out

@@ -1,93 +1,94 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_56 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalUnion
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalUnion
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
+------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[item]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
+------------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------PhysicalDistribute
+--------------------------------filter((customer_address.ca_gmt_offset = -6.00))
+----------------------------------PhysicalOlapScan[customer_address]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
 ------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
-----------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[item]
-----------------------------------PhysicalDistribute
+--------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
+------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
 ------------------------------------PhysicalProject
---------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
-----------------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
+--------------------------------------PhysicalOlapScan[item]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
+------------------------------------------PhysicalOlapScan[item]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((customer_address.ca_gmt_offset = -6.00))
+----------------------------------PhysicalOlapScan[customer_address]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
 ----------------------------PhysicalProject
 ------------------------------filter((customer_address.ca_gmt_offset = -6.00))
 --------------------------------PhysicalOlapScan[customer_address]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------PhysicalDistribute
+----------------------------PhysicalDistribute
+------------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
 ------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
-----------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[item]
-----------------------------------PhysicalDistribute
+--------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
+------------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
 ------------------------------------PhysicalProject
---------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
-----------------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((customer_address.ca_gmt_offset = -6.00))
---------------------------------PhysicalOlapScan[customer_address]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
---------------------------PhysicalProject
-----------------------------filter((customer_address.ca_gmt_offset = -6.00))
-------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[web_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 2))
-----------------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[item]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
-----------------------------------------PhysicalOlapScan[item]
+--------------------------------------PhysicalOlapScan[item]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter(i_color IN ('powder', 'green', 'cyan'))
+------------------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query57.out

@@ -29,23 +29,24 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[call_center]
---PhysicalProject
-----PhysicalTopN
-------PhysicalDistribute
---------PhysicalTopN
-----------PhysicalProject
-------------hashJoin[INNER_JOIN](v1.i_category = v1_lead.i_category)(v1.i_brand = v1_lead.i_brand)(v1.cc_name = v1_lead.cc_name)(v1.rn = expr_(rn - 1))
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](v1.i_category = v1_lag.i_category)(v1.i_brand = v1_lag.i_brand)(v1.cc_name = v1_lag.cc_name)(v1.rn = expr_(rn + 1))
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1)(v2.d_year = 1999)(v2.avg_monthly_sales > 0.0000))
+--PhysicalResultSink
+----PhysicalProject
+------PhysicalTopN
+--------PhysicalDistribute
+----------PhysicalTopN
+------------PhysicalProject
+--------------hashJoin[INNER_JOIN](v1.i_category = v1_lead.i_category)(v1.i_brand = v1_lead.i_brand)(v1.cc_name = v1_lead.cc_name)(v1.rn = expr_(rn - 1))
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](v1.i_category = v1_lag.i_category)(v1.i_brand = v1_lag.i_brand)(v1.cc_name = v1_lag.cc_name)(v1.rn = expr_(rn + 1))
+----------------------PhysicalDistribute
+------------------------PhysicalProject
 --------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1)(v2.d_year = 1999)(v2.avg_monthly_sales > 0.0000))
+----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query58.out

@@ -1,93 +1,94 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_58 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashJoin[INNER_JOIN](ss_items.item_id = cs_items.item_id)(cast(cs_item_rev as DOUBLE) >= cast((0.9 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) >= cast((0.9 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) <= cast((1.1 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) <= cast((1.1 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) >= cast((0.9 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) >= cast((0.9 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) <= cast((1.1 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) <= cast((1.1 * cs_item_rev) as DOUBLE))
-----------PhysicalProject
-------------hashAgg[GLOBAL]
---------------PhysicalDistribute
-----------------hashAgg[LOCAL]
-------------------PhysicalProject
---------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
---------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[catalog_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](ss_items.item_id = cs_items.item_id)(cast(cs_item_rev as DOUBLE) >= cast((0.9 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) >= cast((0.9 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) <= cast((1.1 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) <= cast((1.1 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) >= cast((0.9 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) >= cast((0.9 * cs_item_rev) as DOUBLE))(cast(cs_item_rev as DOUBLE) <= cast((1.1 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) <= cast((1.1 * cs_item_rev) as DOUBLE))
+------------PhysicalProject
+--------------hashAgg[GLOBAL]
+----------------PhysicalDistribute
+------------------hashAgg[LOCAL]
+--------------------PhysicalProject
+----------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+----------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[date_dim]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalAssertNumRows
+--------------------------------PhysicalOlapScan[date_dim]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalAssertNumRows
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((date_dim.d_date = 2001-03-24))
+----------------------------------------PhysicalOlapScan[date_dim]
+------------hashJoin[INNER_JOIN](ss_items.item_id = ws_items.item_id)(cast(ws_item_rev as DOUBLE) >= cast((0.9 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) >= cast((0.9 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) <= cast((1.1 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) <= cast((1.1 * ws_item_rev) as DOUBLE))
+--------------PhysicalProject
+----------------hashAgg[GLOBAL]
+------------------PhysicalDistribute
+--------------------hashAgg[LOCAL]
+----------------------PhysicalProject
+------------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[store_sales]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((date_dim.d_date = 2001-03-24))
---------------------------------------PhysicalOlapScan[date_dim]
-----------hashJoin[INNER_JOIN](ss_items.item_id = ws_items.item_id)(cast(ws_item_rev as DOUBLE) >= cast((0.9 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) >= cast((0.9 * ws_item_rev) as DOUBLE))(cast(ws_item_rev as DOUBLE) <= cast((1.1 * ss_item_rev) as DOUBLE))(cast(ss_item_rev as DOUBLE) <= cast((1.1 * ws_item_rev) as DOUBLE))
-------------PhysicalProject
---------------hashAgg[GLOBAL]
-----------------PhysicalDistribute
-------------------hashAgg[LOCAL]
---------------------PhysicalProject
-----------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalOlapScan[item]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[item]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalDistribute
+----------------------------------PhysicalOlapScan[date_dim]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalAssertNumRows
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_date = 2001-03-24))
+------------------------------------------PhysicalOlapScan[date_dim]
+--------------PhysicalProject
+----------------hashAgg[GLOBAL]
+------------------PhysicalDistribute
+--------------------hashAgg[LOCAL]
+----------------------PhysicalProject
+------------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
 --------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalAssertNumRows
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_date = 2001-03-24))
-----------------------------------------PhysicalOlapScan[date_dim]
-------------PhysicalProject
---------------hashAgg[GLOBAL]
-----------------PhysicalDistribute
-------------------hashAgg[LOCAL]
---------------------PhysicalProject
-----------------------hashJoin[LEFT_SEMI_JOIN](date_dim.d_date = date_dim.d_date)
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
-----------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[web_sales]
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[web_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[item]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[item]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[date_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalAssertNumRows
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_date = 2001-03-24))
-----------------------------------------PhysicalOlapScan[date_dim]
+----------------------------------PhysicalOlapScan[date_dim]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](date_dim.d_week_seq = date_dim.d_week_seq)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalAssertNumRows
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_date = 2001-03-24))
+------------------------------------------PhysicalOlapScan[date_dim]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query59.out

@@ -13,37 +13,38 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------PhysicalDistribute
 ------------------PhysicalProject
 --------------------PhysicalOlapScan[date_dim]
---PhysicalTopN
-----PhysicalDistribute
-------PhysicalTopN
---------PhysicalProject
-----------hashJoin[INNER_JOIN](y.s_store_id1 = x.s_store_id2)(expr_cast(d_week_seq1 as BIGINT) = expr_(d_week_seq2 - 52))
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](wss.ss_store_sk = store.s_store_sk)
-------------------hashJoin[INNER_JOIN](d.d_week_seq = d_week_seq2)
+--PhysicalResultSink
+----PhysicalTopN
+------PhysicalDistribute
+--------PhysicalTopN
+----------PhysicalProject
+------------hashJoin[INNER_JOIN](y.s_store_id1 = x.s_store_id2)(expr_cast(d_week_seq1 as BIGINT) = expr_(d_week_seq2 - 52))
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](wss.ss_store_sk = store.s_store_sk)
+--------------------hashJoin[INNER_JOIN](d.d_week_seq = d_week_seq2)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((d.d_month_seq <= 1219)(d.d_month_seq >= 1208))
+----------------------------PhysicalOlapScan[date_dim]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+------------------------PhysicalOlapScan[store]
+--------------PhysicalDistribute
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN](wss.ss_store_sk = store.s_store_sk)
+--------------------hashJoin[INNER_JOIN](d.d_week_seq = d_week_seq1)
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((d.d_month_seq <= 1207)(d.d_month_seq >= 1196))
+----------------------------PhysicalOlapScan[date_dim]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter((d.d_month_seq <= 1219)(d.d_month_seq >= 1208))
---------------------------PhysicalOlapScan[date_dim]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store]
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](wss.ss_store_sk = store.s_store_sk)
-------------------hashJoin[INNER_JOIN](d.d_week_seq = d_week_seq1)
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((d.d_month_seq <= 1207)(d.d_month_seq >= 1196))
---------------------------PhysicalOlapScan[date_dim]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------PhysicalOlapScan[store]
+------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query6.out

@@ -1,52 +1,53 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_6 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------filter((cnt >= 10))
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[LEFT_SEMI_JOIN](j.i_category = i.i_category)(cast(i_current_price as DECIMALV3(38, 5)) > (1.2 * avg(i_current_price)))
-------------------PhysicalProject
---------------------hashJoin[INNER_JOIN](c.c_customer_sk = s.ss_customer_sk)
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](s.ss_item_sk = i.i_item_sk)
-----------------------------PhysicalDistribute
-------------------------------hashJoin[INNER_JOIN](s.ss_sold_date_sk = d.d_date_sk)
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store_sales]
---------------------------------PhysicalDistribute
-----------------------------------hashJoin[INNER_JOIN](d.d_month_seq = date_dim.d_month_seq)
-------------------------------------PhysicalProject
---------------------------------------PhysicalOlapScan[date_dim]
-------------------------------------PhysicalDistribute
---------------------------------------PhysicalAssertNumRows
-----------------------------------------PhysicalDistribute
-------------------------------------------hashAgg[GLOBAL]
---------------------------------------------PhysicalDistribute
-----------------------------------------------hashAgg[LOCAL]
-------------------------------------------------PhysicalProject
---------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 3))
-----------------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](a.ca_address_sk = c.c_current_addr_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[customer]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[customer_address]
-------------------PhysicalDistribute
---------------------hashAgg[GLOBAL]
-----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------filter((cnt >= 10))
+----------hashAgg[GLOBAL]
+------------PhysicalDistribute
+--------------hashAgg[LOCAL]
+----------------PhysicalProject
+------------------hashJoin[LEFT_SEMI_JOIN](j.i_category = i.i_category)(cast(i_current_price as DECIMALV3(38, 5)) > (1.2 * avg(i_current_price)))
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN](c.c_customer_sk = s.ss_customer_sk)
+------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------PhysicalOlapScan[item]
+----------------------------hashJoin[INNER_JOIN](s.ss_item_sk = i.i_item_sk)
+------------------------------PhysicalDistribute
+--------------------------------hashJoin[INNER_JOIN](s.ss_sold_date_sk = d.d_date_sk)
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------PhysicalDistribute
+------------------------------------hashJoin[INNER_JOIN](d.d_month_seq = date_dim.d_month_seq)
+--------------------------------------PhysicalProject
+----------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalAssertNumRows
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashAgg[GLOBAL]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------hashAgg[LOCAL]
+--------------------------------------------------PhysicalProject
+----------------------------------------------------filter((date_dim.d_year = 2002)(date_dim.d_moy = 3))
+------------------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](a.ca_address_sk = c.c_current_addr_sk)
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[customer]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[customer_address]
+--------------------PhysicalDistribute
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query60.out

@@ -1,94 +1,95 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_60 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalUnion
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
---------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[store_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 8))
-----------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((customer_address.ca_gmt_offset = -7.00))
-----------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalUnion
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_addr_sk = customer_address.ca_address_sk)
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter((item.i_category = 'Children'))
-------------------------------------PhysicalOlapScan[item]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
---------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[catalog_sales]
-----------------------------------PhysicalDistribute
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_moy = 8)(date_dim.d_year = 2000))
-----------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((customer_address.ca_gmt_offset = -7.00))
-----------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
+--------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 8))
+------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter((item.i_category = 'Children'))
-------------------------------------PhysicalOlapScan[item]
---------------PhysicalProject
-----------------hashAgg[GLOBAL]
-------------------PhysicalDistribute
---------------------hashAgg[LOCAL]
-----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
---------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
+----------------------------------filter((customer_address.ca_gmt_offset = -7.00))
+------------------------------------PhysicalOlapScan[customer_address]
 ----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[web_sales]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 8))
-----------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((customer_address.ca_gmt_offset = -7.00))
-----------------------------------PhysicalOlapScan[customer_address]
---------------------------PhysicalDistribute
-----------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[item]
+------------------------------------filter((item.i_category = 'Children'))
+--------------------------------------PhysicalOlapScan[item]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](catalog_sales.cs_item_sk = item.i_item_sk)
+----------------------------hashJoin[INNER_JOIN](catalog_sales.cs_bill_addr_sk = customer_address.ca_address_sk)
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter((item.i_category = 'Children'))
-------------------------------------PhysicalOlapScan[item]
+----------------------------------hashJoin[INNER_JOIN](catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_moy = 8)(date_dim.d_year = 2000))
+------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((customer_address.ca_gmt_offset = -7.00))
+------------------------------------PhysicalOlapScan[customer_address]
+----------------------------PhysicalDistribute
+------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((item.i_category = 'Children'))
+--------------------------------------PhysicalOlapScan[item]
+----------------PhysicalProject
+------------------hashAgg[GLOBAL]
+--------------------PhysicalDistribute
+----------------------hashAgg[LOCAL]
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN](web_sales.ws_item_sk = item.i_item_sk)
+----------------------------hashJoin[INNER_JOIN](web_sales.ws_bill_addr_sk = customer_address.ca_address_sk)
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](web_sales.ws_sold_date_sk = date_dim.d_date_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[web_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((date_dim.d_year = 2000)(date_dim.d_moy = 8))
+------------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((customer_address.ca_gmt_offset = -7.00))
+------------------------------------PhysicalOlapScan[customer_address]
+----------------------------PhysicalDistribute
+------------------------------hashJoin[LEFT_SEMI_JOIN](item.i_item_id = item.i_item_id)
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[item]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((item.i_category = 'Children'))
+--------------------------------------PhysicalOlapScan[item]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query61.out

@@ -1,48 +1,10 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_61 --
-PhysicalTopN
+PhysicalResultSink
 --PhysicalTopN
-----PhysicalProject
-------NestedLoopJoin[CROSS_JOIN]
---------hashAgg[GLOBAL]
-----------PhysicalDistribute
-------------hashAgg[LOCAL]
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN](customer_address.ca_address_sk = customer.c_current_addr_sk)
-------------------PhysicalProject
---------------------filter((customer_address.ca_gmt_offset = -7.00))
-----------------------PhysicalOlapScan[customer_address]
-------------------PhysicalDistribute
---------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-----------------------PhysicalProject
-------------------------filter((cast(i_category as VARCHAR(*)) = 'Jewelry'))
---------------------------PhysicalOlapScan[item]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[customer]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_promo_sk = promotion.p_promo_sk)
-----------------------------------PhysicalProject
-------------------------------------filter((((cast(p_channel_dmail as VARCHAR(*)) = 'Y') OR (cast(p_channel_email as VARCHAR(*)) = 'Y')) OR (cast(p_channel_tv as VARCHAR(*)) = 'Y')))
---------------------------------------PhysicalOlapScan[promotion]
-----------------------------------PhysicalDistribute
-------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------------PhysicalProject
-----------------------------------------filter((date_dim.d_moy = 11)(date_dim.d_year = 1999))
-------------------------------------------PhysicalOlapScan[date_dim]
---------------------------------------PhysicalDistribute
-----------------------------------------PhysicalProject
-------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
---------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[store_sales]
---------------------------------------------PhysicalDistribute
-----------------------------------------------PhysicalProject
-------------------------------------------------filter((store.s_gmt_offset = -7.00))
---------------------------------------------------PhysicalOlapScan[store]
---------PhysicalDistribute
+----PhysicalTopN
+------PhysicalProject
+--------NestedLoopJoin[CROSS_JOIN]
 ----------hashAgg[GLOBAL]
 ------------PhysicalDistribute
 --------------hashAgg[LOCAL]
@@ -58,21 +20,60 @@ PhysicalTopN
 ----------------------------PhysicalOlapScan[item]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
 ------------------------------PhysicalProject
---------------------------------filter((date_dim.d_moy = 11)(date_dim.d_year = 1999))
-----------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalOlapScan[customer]
 ------------------------------PhysicalDistribute
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[customer]
-----------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_promo_sk = promotion.p_promo_sk)
 ------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+--------------------------------------filter((((cast(p_channel_dmail as VARCHAR(*)) = 'Y') OR (cast(p_channel_email as VARCHAR(*)) = 'Y')) OR (cast(p_channel_tv as VARCHAR(*)) = 'Y')))
+----------------------------------------PhysicalOlapScan[promotion]
+------------------------------------PhysicalDistribute
+--------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------filter((date_dim.d_moy = 11)(date_dim.d_year = 1999))
+--------------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------------------PhysicalDistribute
 ------------------------------------------PhysicalProject
---------------------------------------------filter((store.s_gmt_offset = -7.00))
-----------------------------------------------PhysicalOlapScan[store]
+--------------------------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+----------------------------------------------PhysicalProject
+------------------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter((store.s_gmt_offset = -7.00))
+----------------------------------------------------PhysicalOlapScan[store]
+----------PhysicalDistribute
+------------hashAgg[GLOBAL]
+--------------PhysicalDistribute
+----------------hashAgg[LOCAL]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](customer_address.ca_address_sk = customer.c_current_addr_sk)
+----------------------PhysicalProject
+------------------------filter((customer_address.ca_gmt_offset = -7.00))
+--------------------------PhysicalOlapScan[customer_address]
+----------------------PhysicalDistribute
+------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+--------------------------PhysicalProject
+----------------------------filter((cast(i_category as VARCHAR(*)) = 'Jewelry'))
+------------------------------PhysicalOlapScan[item]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+--------------------------------PhysicalProject
+----------------------------------filter((date_dim.d_moy = 11)(date_dim.d_year = 1999))
+------------------------------------PhysicalOlapScan[date_dim]
+--------------------------------PhysicalDistribute
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_customer_sk = customer.c_customer_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[customer]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+------------------------------------------PhysicalProject
+--------------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------PhysicalProject
+----------------------------------------------filter((store.s_gmt_offset = -7.00))
+------------------------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query62.out

@@ -1,30 +1,31 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_62 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------hashAgg[GLOBAL]
---------PhysicalDistribute
-----------hashAgg[LOCAL]
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](web_sales.ws_warehouse_sk = warehouse.w_warehouse_sk)
-----------------PhysicalProject
-------------------hashJoin[INNER_JOIN](web_sales.ws_ship_mode_sk = ship_mode.sm_ship_mode_sk)
---------------------hashJoin[INNER_JOIN](web_sales.ws_web_site_sk = web_site.web_site_sk)
-----------------------hashJoin[INNER_JOIN](web_sales.ws_ship_date_sk = date_dim.d_date_sk)
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[web_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------hashAgg[GLOBAL]
+----------PhysicalDistribute
+------------hashAgg[LOCAL]
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](web_sales.ws_warehouse_sk = warehouse.w_warehouse_sk)
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN](web_sales.ws_ship_mode_sk = ship_mode.sm_ship_mode_sk)
+----------------------hashJoin[INNER_JOIN](web_sales.ws_web_site_sk = web_site.web_site_sk)
+------------------------hashJoin[INNER_JOIN](web_sales.ws_ship_date_sk = date_dim.d_date_sk)
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[web_sales]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((date_dim.d_month_seq >= 1194)(date_dim.d_month_seq <= 1205))
+--------------------------------PhysicalOlapScan[date_dim]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((date_dim.d_month_seq >= 1194)(date_dim.d_month_seq <= 1205))
-------------------------------PhysicalOlapScan[date_dim]
+----------------------------PhysicalOlapScan[web_site]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------PhysicalOlapScan[web_site]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[ship_mode]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[warehouse]
+--------------------------PhysicalOlapScan[ship_mode]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[warehouse]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query63.out

@@ -1,33 +1,34 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_63 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1))
-----------PhysicalWindow
-------------PhysicalQuickSort
---------------PhysicalDistribute
-----------------PhysicalProject
-------------------hashAgg[GLOBAL]
---------------------PhysicalDistribute
-----------------------hashAgg[LOCAL]
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
-----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
-----------------------------------PhysicalProject
-------------------------------------PhysicalOlapScan[store_sales]
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------filter((CASE WHEN (avg_monthly_sales > 0.0000) THEN (abs((cast(sum_sales as DOUBLE) - cast(avg_monthly_sales as DOUBLE))) / cast(avg_monthly_sales as DOUBLE)) ELSE NULL END > 0.1))
+------------PhysicalWindow
+--------------PhysicalQuickSort
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashAgg[GLOBAL]
+----------------------PhysicalDistribute
+------------------------hashAgg[LOCAL]
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_store_sk = store.s_store_sk)
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+----------------------------------hashJoin[INNER_JOIN](store_sales.ss_item_sk = item.i_item_sk)
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) OR ((i_category IN ('Women', 'Music', 'Men') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
+------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) OR ((i_category IN ('Women', 'Music', 'Men') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
-----------------------------------------PhysicalOlapScan[item]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
---------------------------------------PhysicalOlapScan[date_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store]
+--------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
+----------------------------------------PhysicalOlapScan[date_dim]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[store]
 

regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query65.out

@@ -1,45 +1,46 @@
 -- This file is automatically generated. You should know what you did if you want to edit this
 -- !ds_shape_65 --
-PhysicalTopN
---PhysicalDistribute
-----PhysicalTopN
-------PhysicalProject
---------hashJoin[INNER_JOIN](item.i_item_sk = sc.ss_item_sk)
-----------PhysicalDistribute
-------------PhysicalProject
---------------hashJoin[INNER_JOIN](store.s_store_sk = sc.ss_store_sk)
-----------------hashJoin[INNER_JOIN](sb.ss_store_sk = sc.ss_store_sk)(cast(revenue as DOUBLE) <= cast((0.1 * ave) as DOUBLE))
-------------------hashAgg[GLOBAL]
---------------------PhysicalDistribute
-----------------------hashAgg[LOCAL]
-------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store_sales]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((date_dim.d_month_seq <= 1232)(date_dim.d_month_seq >= 1221))
-----------------------------------PhysicalOlapScan[date_dim]
-------------------PhysicalDistribute
+PhysicalResultSink
+--PhysicalTopN
+----PhysicalDistribute
+------PhysicalTopN
+--------PhysicalProject
+----------hashJoin[INNER_JOIN](item.i_item_sk = sc.ss_item_sk)
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------hashJoin[INNER_JOIN](store.s_store_sk = sc.ss_store_sk)
+------------------hashJoin[INNER_JOIN](sb.ss_store_sk = sc.ss_store_sk)(cast(revenue as DOUBLE) <= cast((0.1 * ave) as DOUBLE))
 --------------------hashAgg[GLOBAL]
 ----------------------PhysicalDistribute
 ------------------------hashAgg[LOCAL]
 --------------------------PhysicalProject
-----------------------------hashAgg[GLOBAL]
+----------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[store_sales]
 ------------------------------PhysicalDistribute
---------------------------------hashAgg[LOCAL]
-----------------------------------PhysicalProject
-------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
---------------------------------------PhysicalProject
-----------------------------------------PhysicalOlapScan[store_sales]
---------------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((date_dim.d_month_seq <= 1232)(date_dim.d_month_seq >= 1221))
+------------------------------------PhysicalOlapScan[date_dim]
+--------------------PhysicalDistribute
+----------------------hashAgg[GLOBAL]
+------------------------PhysicalDistribute
+--------------------------hashAgg[LOCAL]
+----------------------------PhysicalProject
+------------------------------hashAgg[GLOBAL]
+--------------------------------PhysicalDistribute
+----------------------------------hashAgg[LOCAL]
+------------------------------------PhysicalProject
+--------------------------------------hashJoin[INNER_JOIN](store_sales.ss_sold_date_sk = date_dim.d_date_sk)
 ----------------------------------------PhysicalProject
-------------------------------------------filter((date_dim.d_month_seq >= 1221)(date_dim.d_month_seq <= 1232))
---------------------------------------------PhysicalOlapScan[date_dim]
-----------------PhysicalDistribute
-------------------PhysicalProject
---------------------PhysicalOlapScan[store]
-----------PhysicalDistribute
-------------PhysicalProject
---------------PhysicalOlapScan[item]
+------------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------------PhysicalDistribute
+------------------------------------------PhysicalProject
+--------------------------------------------filter((date_dim.d_month_seq >= 1221)(date_dim.d_month_seq <= 1232))
+----------------------------------------------PhysicalOlapScan[date_dim]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------PhysicalOlapScan[store]
+------------PhysicalDistribute
+--------------PhysicalProject
+----------------PhysicalOlapScan[item]