diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/jobs/cascades/DeriveStatsJob.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/jobs/cascades/DeriveStatsJob.java
index 572b07a134..c0ef0345a2 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/jobs/cascades/DeriveStatsJob.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/jobs/cascades/DeriveStatsJob.java
@@ -125,7 +125,7 @@ public class DeriveStatsJob extends Job {
                 // child group's row count unchanged when the parent group expression is a project operation.
                 double parentRowCount = groupExpression.getOwnerGroup().getStatistics().getRowCount();
                 groupExpression.children().forEach(g -> g.setStatistics(
-                        g.getStatistics().updateRowCountOnly(parentRowCount))
+                        g.getStatistics().updateRowCountAndColStats(parentRowCount))
                 );
             }
         }
diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
index 00f55936c1..6dd117305e 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
@@ -49,10 +49,11 @@ import org.apache.doris.statistics.StatisticRange;
 import org.apache.doris.statistics.Statistics;
 import org.apache.doris.statistics.StatisticsBuilder;
 
+import com.google.common.base.Preconditions;
+import com.google.common.collect.Sets;
+
 import java.util.ArrayList;
 import java.util.List;
-import java.util.Map;
-import java.util.Map.Entry;
 import java.util.Set;
 import java.util.function.Predicate;
 
@@ -83,12 +84,14 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
     public Statistics estimate(Expression expression, Statistics statistics) {
         // For a comparison predicate, only when it's left side is a slot and right side is a literal, we would
         // consider is a valid predicate.
-        return expression.accept(this, new EstimationContext(statistics));
+        Statistics stats = expression.accept(this, new EstimationContext(statistics));
+        stats.enforceValid();
+        return stats;
     }
 
     @Override
     public Statistics visit(Expression expr, EstimationContext context) {
-        return context.statistics.withSel(DEFAULT_INEQUALITY_COEFFICIENT);
+        return context.statistics.withSel(DEFAULT_INEQUALITY_COEFFICIENT, false);
     }
 
     @Override
@@ -96,35 +99,37 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         Expression leftExpr = predicate.child(0);
         Expression rightExpr = predicate.child(1);
         Statistics leftStats = leftExpr.accept(this, context);
-        Statistics andStats = rightExpr.accept(new FilterEstimation(),
+        Statistics andStats = rightExpr.accept(this,
                 new EstimationContext(leftStats));
         if (predicate instanceof And) {
             return andStats;
         } else if (predicate instanceof Or) {
             Statistics rightStats = rightExpr.accept(this, context);
             double rowCount = leftStats.getRowCount() + rightStats.getRowCount() - andStats.getRowCount();
-            Statistics orStats = context.statistics.withRowCount(rowCount);
-            for (Map.Entry<Expression, ColumnStatistic> entry : orStats.columnStatistics().entrySet()) {
-                ColumnStatistic leftColStats = leftStats.findColumnStatistics(entry.getKey());
-                ColumnStatistic rightColStats = rightStats.findColumnStatistics(entry.getKey());
-                ColumnStatisticBuilder estimatedColStatsBuilder = new ColumnStatisticBuilder(entry.getValue());
-                if (leftColStats.minValue <= rightColStats.minValue) {
-                    estimatedColStatsBuilder.setMinValue(leftColStats.minValue);
-                    estimatedColStatsBuilder.setMinExpr(leftColStats.minExpr);
-                } else {
-                    estimatedColStatsBuilder.setMinValue(rightColStats.minValue);
-                    estimatedColStatsBuilder.setMinExpr(rightColStats.minExpr);
-                }
-                if (leftColStats.maxValue >= rightColStats.maxValue) {
-                    estimatedColStatsBuilder.setMaxValue(leftColStats.maxValue);
-                    estimatedColStatsBuilder.setMaxExpr(leftColStats.maxExpr);
-                } else {
-                    estimatedColStatsBuilder.setMaxValue(rightColStats.maxValue);
-                    estimatedColStatsBuilder.setMaxExpr(rightColStats.maxExpr);
+            Statistics orStats = context.statistics.setRowCount(rowCount);
+            Set<Slot> leftInputSlots = leftExpr.getInputSlots();
+            Set<Slot> rightInputSlots = rightExpr.getInputSlots();
+            for (Slot slot : context.keyColumns) {
+                if (leftInputSlots.contains(slot) && rightInputSlots.contains(slot)) {
+                    ColumnStatistic leftColStats = leftStats.findColumnStatistics(slot);
+                    ColumnStatistic rightColStats = rightStats.findColumnStatistics(slot);
+                    StatisticRange leftRange = StatisticRange.from(leftColStats, slot.getDataType());
+                    StatisticRange rightRange = StatisticRange.from(rightColStats, slot.getDataType());
+                    StatisticRange union = leftRange.union(rightRange);
+                    ColumnStatisticBuilder colBuilder = new ColumnStatisticBuilder(
+                            context.statistics.findColumnStatistics(slot));
+                    colBuilder.setMinValue(union.getLow()).setMinExpr(union.getLowExpr())
+                            .setMaxValue(union.getHigh()).setMaxExpr(union.getHighExpr())
+                            .setNdv(union.getDistinctValues());
+                    orStats.addColumnStats(slot, colBuilder.build());
                 }
             }
             return orStats;
         }
+        // should not come here
+        Preconditions.checkArgument(false,
+                "unsupported compound operator: %s in %s",
+                predicate.getClass().getName(), predicate.toSql());
         return context.statistics;
     }
 
@@ -159,7 +164,7 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
                 double rowCount = context.statistics.getRowCount();
                 double newRowCount = Math.max(rowCount * DEFAULT_HAVING_COEFFICIENT,
                         Math.max(statsForLeft.ndv, statsForRight.ndv));
-                return context.statistics.withRowCount(newRowCount);
+                return context.statistics.setRowCount(newRowCount);
             }
         }
         if (!left.isConstant() && !right.isConstant()) {
@@ -202,7 +207,7 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
     private Statistics calculateWhenLiteralRight(ComparisonPredicate cp,
             ColumnStatistic statsForLeft, ColumnStatistic statsForRight, EstimationContext context) {
         if (statsForLeft.isUnKnown) {
-            return context.statistics.withSel(DEFAULT_INEQUALITY_COEFFICIENT);
+            return context.statistics.withSel(DEFAULT_INEQUALITY_COEFFICIENT, false);
         }
 
         if (cp instanceof EqualTo || cp instanceof NullSafeEqual) {
@@ -236,9 +241,10 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
             return estimateEqualToWithHistogram(cp.left(), statsForLeft, val, context);
         }
 
-        Statistics equalStats = context.statistics.withSel(selectivity);
+        Statistics equalStats = context.statistics.withSel(selectivity, false);
         Expression left = cp.left();
         equalStats.addColumnStats(left, statsForRight);
+        context.addKeyIfSlot(left);
         if (!(left instanceof SlotReference)) {
             left.accept(new ColumnStatsAdjustVisitor(), equalStats);
         }
@@ -266,7 +272,7 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         Expression compareExpr = inPredicate.getCompareExpr();
         ColumnStatistic compareExprStats = ExpressionEstimation.estimate(compareExpr, context.statistics);
         if (compareExprStats.isUnKnown || compareExpr instanceof Function) {
-            return context.statistics.withSel(DEFAULT_IN_COEFFICIENT);
+            return context.statistics.withSel(DEFAULT_IN_COEFFICIENT, false);
         }
         List<Expression> options = inPredicate.getOptions();
         // init minOption and maxOption by compareExpr.max and compareExpr.min respectively,
@@ -342,10 +348,10 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
             }
         }
         Statistics estimated = new Statistics(context.statistics);
-        estimated = estimated.withSel(selectivity);
+        estimated = estimated.withSel(selectivity, false);
         estimated.addColumnStats(compareExpr,
                 compareExprStatsBuilder.build());
-
+        context.addKeyIfSlot(compareExpr);
         return estimated;
     }
 
@@ -359,31 +365,55 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         if (context.statistics.isInputSlotsUnknown(not.getInputSlots())) {
             return handleUnknownCase(context);
         }
-        Statistics childStats = new FilterEstimation().estimate(not.child(), context.statistics);
+        Expression child = not.child();
+        Statistics childStats = child.accept(this, context);
         //if estimated rowCount is 0, adjust to 1 to make upper join reorder reasonable.
         double rowCount = Math.max(context.statistics.getRowCount() - childStats.getRowCount(), 1);
         StatisticsBuilder statisticsBuilder = new StatisticsBuilder(context.statistics).setRowCount(rowCount);
-        for (Entry<Expression, ColumnStatistic> entry : context.statistics.columnStatistics().entrySet()) {
-            Expression expr = entry.getKey();
-            ColumnStatistic originColStats = entry.getValue();
-            ColumnStatistic childColStats = childStats.findColumnStatistics(expr);
-            double originNonNullCount = Math.max(originColStats.count - originColStats.numNulls, 0);
-            double childNonNullCount = Math.max(childColStats.count - childColStats.numNulls, 0);
-            double supersetValuesPerDistinctValue = StatsMathUtil.divide(originNonNullCount, originColStats.ndv);
-            double subsetValuesPerDistinctValue = StatsMathUtil.divide(childNonNullCount, childColStats.ndv);
-            double ndv;
-            if (supersetValuesPerDistinctValue <= subsetValuesPerDistinctValue) {
-                ndv = Math.max(originColStats.ndv - childColStats.ndv, 0);
-            } else {
-                ndv = originColStats.ndv;
+        // update key col stats
+        for (Slot slot : not.child().getInputSlots()) {
+            ColumnStatistic originColStats = context.statistics.findColumnStatistics(slot);
+            ColumnStatistic childColStats = childStats.findColumnStatistics(slot);
+            if (context.isKeySlot(slot)) {
+                ColumnStatisticBuilder colBuilder = new ColumnStatisticBuilder(childColStats);
+                // update column stats for
+                // 1. not (A=B)
+                // 2. not A in (...)
+                // 3. not A is null
+                // 4. not A like XXX
+                colBuilder.setNumNulls(0);
+                Preconditions.checkArgument(
+                        child instanceof EqualTo
+                                || child instanceof InPredicate
+                                || child instanceof IsNull
+                                || child instanceof Like,
+                        "Not-predicate meet unexpected child: %s", child.toSql());
+                if (child instanceof Like) {
+                    rowCount = context.statistics.getRowCount() - childStats.getRowCount();
+                    colBuilder.setNdv(originColStats.ndv - childColStats.ndv);
+                } else if (child instanceof InPredicate) {
+                    colBuilder.setNdv(originColStats.ndv - childColStats.ndv);
+                    colBuilder.setMinValue(originColStats.minValue)
+                            .setMinExpr(originColStats.minExpr)
+                            .setMaxValue(originColStats.maxValue)
+                            .setMaxExpr(originColStats.maxExpr);
+                } else if (child instanceof IsNull) {
+                    colBuilder.setNdv(originColStats.ndv);
+                    colBuilder.setMinValue(originColStats.minValue)
+                            .setMinExpr(originColStats.minExpr)
+                            .setMaxValue(originColStats.maxValue)
+                            .setMaxExpr(originColStats.maxExpr);
+                } else if (child instanceof EqualTo) {
+                    colBuilder.setNdv(originColStats.ndv - childColStats.ndv);
+                    colBuilder.setMinValue(originColStats.minValue)
+                            .setMinExpr(originColStats.minExpr)
+                            .setMaxValue(originColStats.maxValue)
+                            .setMaxExpr(originColStats.maxExpr);
+                }
+                statisticsBuilder.putColumnStatistics(slot, colBuilder.build());
             }
-            double nullCount = Math.max(originColStats.numNulls - childColStats.numNulls, 0);
-            ColumnStatistic columnStatistic = new ColumnStatisticBuilder(originColStats)
-                    .setNdv(ndv)
-                    .setNumNulls(nullCount)
-                    .build();
-            statisticsBuilder.putColumnStatistics(expr, columnStatistic);
         }
+
         return statisticsBuilder.build();
     }
 
@@ -395,20 +425,37 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         }
         double outputRowCount = childStats.numNulls;
         ColumnStatisticBuilder colBuilder = new ColumnStatisticBuilder(childStats);
-        // do not modify ndv/min/max to make is-not-null work
-        colBuilder.setCount(outputRowCount).setNumNulls(outputRowCount);
+        colBuilder.setCount(outputRowCount).setNumNulls(outputRowCount)
+                .setMaxValue(Double.POSITIVE_INFINITY)
+                .setMinValue(Double.NEGATIVE_INFINITY)
+                .setNdv(0);
         StatisticsBuilder builder = new StatisticsBuilder(context.statistics);
         builder.putColumnStatistics(isNull.child(), colBuilder.build());
-        // TODO we do not call updateRowCountOnly() to make is-not-null work. this need refactor
+        context.addKeyIfSlot(isNull.child());
         return builder.build();
     }
 
     static class EstimationContext {
         private final Statistics statistics;
 
+        private final Set<Slot> keyColumns = Sets.newHashSet();
+
         public EstimationContext(Statistics statistics) {
             this.statistics = statistics;
         }
+
+        public void addKeyIfSlot(Expression expr) {
+            if (expr instanceof Slot) {
+                keyColumns.add((Slot) expr);
+            }
+        }
+
+        public boolean isKeySlot(Expression expr) {
+            if (expr instanceof Slot) {
+                return keyColumns.contains((Slot) expr);
+            }
+            return false;
+        }
     }
 
     private Statistics estimateBinaryComparisonFilter(Expression leftExpr, ColumnStatistic leftStats,
@@ -421,7 +468,7 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         ColumnStatisticBuilder leftColumnStatisticBuilder;
         Statistics updatedStatistics;
         if (intersectRange.isEmpty()) {
-            updatedStatistics = context.statistics.updateRowCountOnly(0);
+            updatedStatistics = context.statistics.setRowCount(0);
             leftColumnStatisticBuilder = new ColumnStatisticBuilder(leftStats)
                     .setMinValue(Double.NEGATIVE_INFINITY)
                     .setMinExpr(null)
@@ -437,10 +484,11 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
                     .setMaxExpr(intersectRange.getHighExpr())
                     .setNdv(intersectRange.getDistinctValues());
             double sel = leftRange.overlapPercentWith(rightRange);
-            updatedStatistics = context.statistics.withSel(sel);
+            updatedStatistics = context.statistics.withSel(sel, false);
             leftColumnStatisticBuilder.setCount(updatedStatistics.getRowCount());
         }
         updatedStatistics.addColumnStats(leftExpr, leftColumnStatisticBuilder.build());
+        context.addKeyIfSlot(leftExpr);
         leftExpr.accept(new ColumnStatsAdjustVisitor(), updatedStatistics);
         return updatedStatistics;
     }
@@ -450,19 +498,17 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         StatisticRange leftRange = StatisticRange.from(leftStats, leftExpr.getDataType());
         StatisticRange rightRange = StatisticRange.from(rightStats, rightExpr.getDataType());
         StatisticRange leftIntersectRight = leftRange.intersect(rightRange);
-        StatisticRange rightIntersectLeft = rightRange.intersect(leftIntersectRight);
-        ColumnStatisticBuilder leftBuilder = new ColumnStatisticBuilder(leftStats);
-        leftBuilder.setNdv(leftIntersectRight.getDistinctValues());
-        leftBuilder.setMinValue(leftIntersectRight.getLow());
-        leftBuilder.setMaxValue(leftIntersectRight.getHigh());
-        ColumnStatisticBuilder rightBuilder = new ColumnStatisticBuilder(rightStats);
-        rightBuilder.setNdv(rightIntersectLeft.getDistinctValues());
-        rightBuilder.setMinValue(rightIntersectLeft.getLow());
-        rightBuilder.setMaxValue(rightIntersectLeft.getDistinctValues());
+        StatisticRange intersect = rightRange.intersect(leftIntersectRight);
+        ColumnStatisticBuilder intersectBuilder = new ColumnStatisticBuilder(leftStats);
+        intersectBuilder.setNdv(intersect.getDistinctValues());
+        intersectBuilder.setMinValue(intersect.getLow());
+        intersectBuilder.setMaxValue(intersect.getHigh());
         double sel = 1 / StatsMathUtil.nonZeroDivisor(Math.max(leftStats.ndv, rightStats.ndv));
-        Statistics updatedStatistics = context.statistics.withSel(sel);
-        updatedStatistics.addColumnStats(leftExpr, leftBuilder.build());
-        updatedStatistics.addColumnStats(rightExpr, rightBuilder.build());
+        Statistics updatedStatistics = context.statistics.withSel(sel, false);
+        updatedStatistics.addColumnStats(leftExpr, intersectBuilder.build());
+        updatedStatistics.addColumnStats(rightExpr, intersectBuilder.build());
+        context.addKeyIfSlot(leftExpr);
+        context.addKeyIfSlot(rightExpr);
         return updatedStatistics;
     }
 
@@ -474,16 +520,18 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         // Left always less than Right
         if (leftRange.getHigh() < rightRange.getLow()) {
             statistics =
-                    context.statistics.withRowCount(Math.min(context.statistics.getRowCount() - leftStats.numNulls,
+                    context.statistics.setRowCount(Math.min(context.statistics.getRowCount() - leftStats.numNulls,
                             context.statistics.getRowCount() - rightStats.numNulls));
             statistics.addColumnStats(leftExpr, new ColumnStatisticBuilder(leftStats).setNumNulls(0.0).build());
             statistics.addColumnStats(rightExpr, new ColumnStatisticBuilder(rightStats).setNumNulls(0.0).build());
+            context.addKeyIfSlot(leftExpr);
+            context.addKeyIfSlot(rightExpr);
             return statistics;
         }
         double leftOverlapPercent = leftRange.overlapPercentWith(rightRange);
         // Left always greater than right
         if (leftOverlapPercent == 0) {
-            return context.statistics.withRowCount(0.0);
+            return context.statistics.setRowCount(0.0);
         }
         StatisticRange leftAlwaysLessThanRightRange = new StatisticRange(leftStats.minValue, leftStats.minExpr,
                 rightStats.minValue, rightStats.minExpr, Double.NaN, leftExpr.getDataType());
@@ -514,7 +562,9 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
         double sel = leftAlwaysLessThanRightPercent
                 + leftOverlapPercent * rightOverlappingRangeFraction * DEFAULT_INEQUALITY_COEFFICIENT
                 + leftOverlapPercent * rightAlwaysGreaterRangeFraction;
-        return context.statistics.withSel(sel)
+        context.addKeyIfSlot(leftExpr);
+        context.addKeyIfSlot(rightExpr);
+        return context.statistics.withSel(sel, false)
                 .addColumnStats(leftExpr, leftColumnStatistic)
                 .addColumnStats(rightExpr, rightColumnStatistic);
     }
@@ -547,10 +597,11 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
                         .setMaxValue(numVal)
                         .setHistogram(new HistogramBuilder(leftHist).setBuckets(updatedBucketList).build())
                         .build();
-                return context.statistics.withSel(sel).addColumnStats(leftExpr, columnStatistic);
+                context.addKeyIfSlot(leftExpr);
+                return context.statistics.withSel(sel, false).addColumnStats(leftExpr, columnStatistic);
             }
         }
-        return context.statistics.withSel(0);
+        return context.statistics.withSel(0, false);
     }
 
     private Statistics estimateGreaterThanLiteralWithHistogram(Expression leftExpr, ColumnStatistic leftStats,
@@ -583,10 +634,11 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
                         .setMaxValue(numVal)
                         .setHistogram(new HistogramBuilder(leftHist).setBuckets(updatedBucketList).build())
                         .build();
-                return context.statistics.withSel(sel).addColumnStats(leftExpr, columnStatistic);
+                context.addKeyIfSlot(leftExpr);
+                return context.statistics.withSel(sel, false).addColumnStats(leftExpr, columnStatistic);
             }
         }
-        return context.statistics.withSel(0);
+        return context.statistics.withSel(0, false);
     }
 
     private Statistics estimateEqualToWithHistogram(Expression leftExpr, ColumnStatistic leftStats,
@@ -610,11 +662,24 @@ public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationCo
                 .setMaxValue(numVal)
                 .setMinValue(numVal)
                 .build();
-        return context.statistics.withSel(sel).addColumnStats(leftExpr, columnStatistic);
+        context.addKeyIfSlot(leftExpr);
+        return context.statistics.withSel(sel, false).addColumnStats(leftExpr, columnStatistic);
     }
 
     @Override
     public Statistics visitLike(Like like, EstimationContext context) {
-        return context.statistics.withSel(DEFAULT_LIKE_COMPARISON_SELECTIVITY);
+        StatisticsBuilder statsBuilder = new StatisticsBuilder(context.statistics);
+        statsBuilder.setRowCount(context.statistics.getRowCount() * DEFAULT_LIKE_COMPARISON_SELECTIVITY);
+        if (like.left() instanceof Slot) {
+            ColumnStatistic origin = context.statistics.findColumnStatistics(like.left());
+            Preconditions.checkArgument(origin != null,
+                    "col stats not found. slot=%s in %s",
+                    like.left().toSql(), like.toSql());
+            ColumnStatisticBuilder colBuilder = new ColumnStatisticBuilder(origin);
+            colBuilder.setNdv(origin.ndv * DEFAULT_LIKE_COMPARISON_SELECTIVITY).setNumNulls(0);
+            statsBuilder.putColumnStatistics(like.left(), colBuilder.build());
+            context.addKeyIfSlot(like.left());
+        }
+        return statsBuilder.build();
     }
 }
diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/JoinEstimation.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/JoinEstimation.java
index 62f650f798..533184887b 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/JoinEstimation.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/JoinEstimation.java
@@ -142,7 +142,7 @@ public class JoinEstimation {
                 outputRowCount = Math.max(1, outputRowCount * ratio.get());
             }
         }
-        innerJoinStats = crossJoinStats.updateRowCountOnly(outputRowCount);
+        innerJoinStats = crossJoinStats.updateRowCountAndColStats(outputRowCount);
         return innerJoinStats;
     }
 
diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/StatsCalculator.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/StatsCalculator.java
index c7470a793a..f39c79391e 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/StatsCalculator.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/StatsCalculator.java
@@ -690,7 +690,7 @@ public class StatsCalculator extends DefaultPlanVisitor<Statistics, Void> {
         // TODO: for the filter push down window situation, we will prune the row count twice
         //  because we keep the pushed down filter. And it will be calculated twice, one of them in 'PartitionTopN'
         //  and the other is in 'Filter'. It's hard to dismiss.
-        return childStats.updateRowCountOnly(rowCount);
+        return childStats.updateRowCountAndColStats(rowCount);
     }
 
     private Statistics computeLimit(Limit limit) {
diff --git a/fe/fe-core/src/main/java/org/apache/doris/statistics/StatisticRange.java b/fe/fe-core/src/main/java/org/apache/doris/statistics/StatisticRange.java
index 360f5f5cdd..74b77c2ee7 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/statistics/StatisticRange.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/statistics/StatisticRange.java
@@ -44,14 +44,22 @@ public class StatisticRange {
 
     private final DataType dataType;
 
+    private final boolean isEmpty;
+
     public StatisticRange(double low, LiteralExpr lowExpr, double high, LiteralExpr highExpr,
                           double distinctValues, DataType dataType) {
+        this(low, lowExpr, high, highExpr, distinctValues, dataType, false);
+    }
+
+    private StatisticRange(double low, LiteralExpr lowExpr, double high, LiteralExpr highExpr,
+                          double distinctValues, DataType dataType, boolean isEmpty) {
         this.low = low;
         this.lowExpr = lowExpr;
         this.high = high;
         this.highExpr = highExpr;
         this.distinctValues = distinctValues;
         this.dataType = dataType;
+        this.isEmpty = isEmpty;
     }
 
     public LiteralExpr getLowExpr() {
@@ -100,17 +108,26 @@ public class StatisticRange {
     }
 
     public static StatisticRange empty(DataType dataType) {
-        return new StatisticRange(Double.NaN, null, Double.NaN, null, 0, dataType);
+        return new StatisticRange(Double.NEGATIVE_INFINITY, null, Double.POSITIVE_INFINITY,
+                null, 0, dataType, true);
     }
 
     public boolean isEmpty() {
-        return Double.isNaN(low) && Double.isNaN(high);
+        return isEmpty;
     }
 
     public boolean isBothInfinite() {
         return Double.isInfinite(low) && Double.isInfinite(high);
     }
 
+    public boolean isInfinite() {
+        return Double.isInfinite(low) || Double.isInfinite(high);
+    }
+
+    public boolean isFinite() {
+        return Double.isFinite(low) && Double.isFinite(high);
+    }
+
     public static StatisticRange from(ColumnStatistic colStats, DataType dataType) {
         return new StatisticRange(colStats.minValue, colStats.minExpr, colStats.maxValue, colStats.maxExpr,
                 colStats.ndv, dataType);
diff --git a/fe/fe-core/src/main/java/org/apache/doris/statistics/Statistics.java b/fe/fe-core/src/main/java/org/apache/doris/statistics/Statistics.java
index 871fdf927c..ef9d77d1c5 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/statistics/Statistics.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/statistics/Statistics.java
@@ -92,10 +92,14 @@ public class Statistics {
         return statistics;
     }
 
+    public Statistics setRowCount(double rowCount) {
+        return new Statistics(rowCount, new HashMap<>(expressionToColumnStats));
+    }
+
     /**
      * Update by count.
      */
-    public Statistics updateRowCountOnly(double rowCount) {
+    public Statistics updateRowCountAndColStats(double rowCount) {
         Statistics statistics = new Statistics(rowCount, expressionToColumnStats);
         for (Entry<Expression, ColumnStatistic> entry : expressionToColumnStats.entrySet()) {
             ColumnStatistic columnStatistic = entry.getValue();
@@ -144,8 +148,21 @@ public class Statistics {
     }
 
     public Statistics withSel(double sel) {
+        return withSel(sel, true);
+    }
+
+    public Statistics withSel(double sel, boolean updateColStats) {
         sel = StatsMathUtil.minNonNaN(sel, 1);
-        return withRowCount(rowCount * sel);
+        if (Double.isNaN(rowCount)) {
+            return this;
+        }
+        double newCount = rowCount * sel;
+        double originCount = rowCount;
+        Statistics statistics = new Statistics(newCount, new HashMap<>(expressionToColumnStats));
+        if (updateColStats) {
+            statistics.fix(newCount, StatsMathUtil.nonZeroDivisor(originCount));
+        }
+        return statistics;
     }
 
     public Statistics addColumnStats(Expression expression, ColumnStatistic columnStatistic) {
diff --git a/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java b/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
index ff53e87910..246e556824 100644
--- a/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
+++ b/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
@@ -198,7 +198,7 @@ class FilterEstimationTest {
         Statistics stat = new Statistics(1000, slotToColumnStat);
         FilterEstimation filterEstimation = new FilterEstimation();
         Statistics expected = filterEstimation.estimate(or, stat);
-        Assertions.assertEquals(51, expected.getRowCount(), 0.1);
+        Assertions.assertEquals(51.9, expected.getRowCount(), 0.1);
     }
 
     // a > 500 and b < 100 or a > c
@@ -503,7 +503,7 @@ class FilterEstimationTest {
      * filter range has intersection with (c.min, c.max)
      *      rows = 100
      *     a primary key, a.ndv reduced by 1/4
-     *     b normal field, b.ndv=20 =>
+     *     b normal field, b.ndv=20
      *     c.ndv = 10/40 * c.ndv
      */
     @Test
@@ -550,7 +550,7 @@ class FilterEstimationTest {
         Assertions.assertEquals(100, statsA.maxValue);
 
         ColumnStatistic statsB = estimated.findColumnStatistics(b);
-        Assertions.assertEquals(15.6, statsB.ndv, 0.1);
+        Assertions.assertEquals(20, statsB.ndv, 0.1);
         Assertions.assertEquals(0, statsB.minValue);
         Assertions.assertEquals(500, statsB.maxValue);
 
@@ -679,7 +679,7 @@ class FilterEstimationTest {
         Assertions.assertEquals(5, statsA.ndv, 0.1);
         Assertions.assertEquals(0, statsA.minValue);
         Assertions.assertEquals(100, statsA.maxValue);
-        Assertions.assertEquals(4.5, statsB.ndv, 0.1);
+        Assertions.assertEquals(5, statsB.ndv, 0.1);
         Assertions.assertEquals(0, statsB.minValue);
         Assertions.assertEquals(500, statsB.maxValue);
         Assertions.assertEquals(2, statsC.ndv);
@@ -753,7 +753,7 @@ class FilterEstimationTest {
         Assertions.assertEquals(5, statsA.ndv, 0.1);
         Assertions.assertEquals(0, statsA.minValue);
         Assertions.assertEquals(100, statsA.maxValue);
-        Assertions.assertEquals(4.5, statsB.ndv, 0.1);
+        Assertions.assertEquals(5, statsB.ndv, 0.1);
         Assertions.assertEquals(0, statsB.minValue);
         Assertions.assertEquals(500, statsB.maxValue);
         Assertions.assertEquals(2, statsC.ndv);
@@ -819,7 +819,7 @@ class FilterEstimationTest {
         Assertions.assertEquals(75, statsA.ndv);
         Assertions.assertEquals(0, statsA.minValue);
         Assertions.assertEquals(100, statsA.maxValue);
-        Assertions.assertEquals(19.9, statsB.ndv, 0.1);
+        Assertions.assertEquals(20, statsB.ndv, 0.1);
         Assertions.assertEquals(0, statsB.minValue);
         Assertions.assertEquals(500, statsB.maxValue);
         Assertions.assertEquals(30, statsC.ndv);
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
index 79a3e5613c..f53714fda8 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
@@ -5,34 +5,36 @@ PhysicalResultSink
 ----PhysicalDistribute
 ------hashAgg[LOCAL]
 --------PhysicalProject
-----------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk))otherCondition=()
+----------hashJoin[INNER_JOIN] hashCondition=((store.s_store_sk = store_sales.ss_store_sk))otherCondition=()
 ------------PhysicalProject
---------------filter((date_dim.d_year = 2001))
-----------------PhysicalOlapScan[date_dim]
+--------------PhysicalOlapScan[store]
 ------------PhysicalDistribute
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN] hashCondition=((store.s_store_sk = store_sales.ss_store_sk))otherCondition=()
-------------------PhysicalProject
---------------------PhysicalOlapScan[store]
+----------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk))otherCondition=(((((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '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 ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = '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 ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '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))))
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk))otherCondition=(((((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '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 ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = '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 ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '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(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
-----------------------------PhysicalOlapScan[customer_demographics]
+----------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
+------------------------PhysicalOlapScan[customer_demographics]
+------------------PhysicalDistribute
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
 ------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-----------------------------PhysicalProject
-------------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
---------------------------------PhysicalOlapScan[household_demographics]
+--------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk))otherCondition=()
+----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk))otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') 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)))))
+------------------------------PhysicalDistribute
+--------------------------------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))) and ((((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(((ca_state IN ('KS', 'MI', 'SD') OR ca_state IN ('CO', 'MO', 'ND')) OR ca_state IN ('NH', 'OH', 'TX')) and (customer_address.ca_country = 'United States'))
+------------------------------------PhysicalOlapScan[customer_address]
 ----------------------------PhysicalDistribute
-------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk))otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') 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)))))
---------------------------------PhysicalDistribute
-----------------------------------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))) and ((((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(((ca_state IN ('KS', 'MI', 'SD') OR ca_state IN ('CO', 'MO', 'ND')) OR ca_state IN ('NH', 'OH', 'TX')) and (customer_address.ca_country = 'United States'))
---------------------------------------PhysicalOlapScan[customer_address]
+------------------------------PhysicalProject
+--------------------------------filter((date_dim.d_year = 2001))
+----------------------------------PhysicalOlapScan[date_dim]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
+------------------------------PhysicalOlapScan[household_demographics]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query18.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query18.out
index 980b95e190..77e1ffc5f9 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query18.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query18.out
@@ -21,30 +21,29 @@ PhysicalResultSink
 --------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------hashJoin[INNER_JOIN] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk))otherCondition=()
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalProject
---------------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk))otherCondition=()
-----------------------------------------PhysicalDistribute
-------------------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk))otherCondition=()
---------------------------------------------PhysicalProject
-----------------------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_bill_cdemo_sk = cd1.cd_demo_sk))otherCondition=()
-------------------------------------------------PhysicalProject
---------------------------------------------------PhysicalOlapScan[catalog_sales]
-------------------------------------------------PhysicalDistribute
---------------------------------------------------PhysicalProject
-----------------------------------------------------filter((cd1.cd_education_status = 'Advanced Degree') and (cd1.cd_gender = 'F'))
-------------------------------------------------------PhysicalOlapScan[customer_demographics]
---------------------------------------------PhysicalDistribute
-----------------------------------------------PhysicalProject
-------------------------------------------------filter((date_dim.d_year = 1998))
---------------------------------------------------PhysicalOlapScan[date_dim]
-----------------------------------------PhysicalDistribute
+--------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk))otherCondition=()
+----------------------------------PhysicalProject
+------------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_bill_cdemo_sk = cd1.cd_demo_sk))otherCondition=()
+--------------------------------------PhysicalProject
+----------------------------------------hashJoin[INNER_JOIN] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk))otherCondition=()
 ------------------------------------------PhysicalProject
---------------------------------------------filter(c_birth_month IN (1, 10, 2, 4, 7, 8))
-----------------------------------------------PhysicalOlapScan[customer]
+--------------------------------------------PhysicalOlapScan[catalog_sales]
+------------------------------------------PhysicalDistribute
+--------------------------------------------hashJoin[INNER_JOIN] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk))otherCondition=()
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter(c_birth_month IN (1, 10, 2, 4, 7, 8))
+----------------------------------------------------PhysicalOlapScan[customer]
+----------------------------------------------PhysicalDistribute
+------------------------------------------------PhysicalProject
+--------------------------------------------------filter(ca_state IN ('GA', 'IN', 'ME', 'NC', 'OK', 'WA', 'WY'))
+----------------------------------------------------PhysicalOlapScan[customer_address]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter((cd1.cd_education_status = 'Advanced Degree') and (cd1.cd_gender = 'F'))
+--------------------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------filter(ca_state IN ('GA', 'IN', 'ME', 'NC', 'OK', 'WA', 'WY'))
-----------------------------------------PhysicalOlapScan[customer_address]
+--------------------------------------filter((date_dim.d_year = 1998))
+----------------------------------------PhysicalOlapScan[date_dim]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query4.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query4.out
index 95d9e38065..f6731eeefb 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query4.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query4.out
@@ -63,9 +63,9 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN] hashCondition=((t_s_firstyear.customer_id = t_w_firstyear.customer_id))otherCondition=()
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN] hashCondition=((t_s_firstyear.customer_id = t_c_secyear.customer_id))otherCondition=((if((year_total > 0.000000), (cast(year_total as DOUBLE) / cast(year_total as DOUBLE)), NULL) > if((year_total > 0.000000), (cast(year_total as DOUBLE) / cast(year_total as DOUBLE)), NULL)))
+--------------------hashJoin[INNER_JOIN] hashCondition=((t_s_secyear.customer_id = t_s_firstyear.customer_id))otherCondition=((if((year_total > 0.000000), (cast(year_total as DOUBLE) / cast(year_total as DOUBLE)), NULL) > if((year_total > 0.000000), (cast(year_total as DOUBLE) / cast(year_total as DOUBLE)), NULL)))
 ----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN] hashCondition=((t_s_secyear.customer_id = t_s_firstyear.customer_id))otherCondition=()
+------------------------hashJoin[INNER_JOIN] hashCondition=((t_s_firstyear.customer_id = t_c_secyear.customer_id))otherCondition=()
 --------------------------hashJoin[INNER_JOIN] hashCondition=((t_s_firstyear.customer_id = t_c_firstyear.customer_id))otherCondition=()
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
@@ -77,11 +77,11 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ----------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((t_s_secyear.dyear = 2000) and (t_s_secyear.sale_type = 's'))
+------------------------------filter((t_c_secyear.dyear = 2000) and (t_c_secyear.sale_type = 'c'))
 --------------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------filter((t_c_secyear.dyear = 2000) and (t_c_secyear.sale_type = 'c'))
+--------------------------filter((t_s_secyear.dyear = 2000) and (t_s_secyear.sale_type = 's'))
 ----------------------------PhysicalCteConsumer ( cteId=CTEId#0 )
 ------------------PhysicalDistribute
 --------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
index c26a22c632..0e1041e12f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
@@ -11,20 +11,20 @@ PhysicalResultSink
 ----------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk))otherCondition=()
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk))otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk))otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00)))))
 ------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk))otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00)))))
+--------------------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk))otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '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))) and ((((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(((ca_state IN ('IA', 'MD', 'MN') OR ca_state IN ('IL', 'TX', 'VA')) OR ca_state IN ('IN', 'MI', 'WI')) and (customer_address.ca_country = 'United States'))
-----------------------------------PhysicalOlapScan[customer_address]
+--------------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
+----------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
-------------------------------PhysicalOlapScan[customer_demographics]
+----------------------------filter(((ca_state IN ('IA', 'MD', 'MN') OR ca_state IN ('IL', 'TX', 'VA')) OR ca_state IN ('IN', 'MI', 'WI')) and (customer_address.ca_country = 'United States'))
+------------------------------PhysicalOlapScan[customer_address]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
index ec3fa8c91b..ff44888133 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
@@ -10,13 +10,9 @@ PhysicalResultSink
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk))otherCondition=()
---------------------PhysicalProject
-----------------------PhysicalOlapScan[reason]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
 ------------------------hashJoin[INNER_JOIN] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk))otherCondition=()
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[web_page]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk))otherCondition=()
@@ -25,9 +21,10 @@ PhysicalResultSink
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
 ------------------------------------hashJoin[INNER_JOIN] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk))otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00)))))
---------------------------------------PhysicalProject
-----------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
-------------------------------------------PhysicalOlapScan[customer_demographics]
+--------------------------------------PhysicalDistribute
+----------------------------------------PhysicalProject
+------------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
+--------------------------------------------PhysicalOlapScan[customer_demographics]
 --------------------------------------PhysicalDistribute
 ----------------------------------------hashJoin[INNER_JOIN] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk))otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00)))))
 ------------------------------------------PhysicalDistribute
@@ -47,4 +44,10 @@ PhysicalResultSink
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter(((ca_state IN ('DE', 'FL', 'TX') OR ca_state IN ('ID', 'IN', 'ND')) OR ca_state IN ('IL', 'MT', 'OH')) and (customer_address.ca_country = 'United States'))
 ------------------------------------------------PhysicalOlapScan[customer_address]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[web_page]
+--------------------PhysicalDistribute
+----------------------PhysicalProject
+------------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
index 0240079d90..198713620a 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
@@ -13,175 +13,183 @@ PhysicalResultSink
 --------------------PhysicalDistribute
 ----------------------hashAgg[LOCAL]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
-------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store_sales]
---------------------------------PhysicalDistribute
-----------------------------------PhysicalProject
-------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
---------------------------------------PhysicalOlapScan[time_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter((store.s_store_name = 'ese'))
-------------------------------------PhysicalOlapScan[store]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-----------------------------------PhysicalOlapScan[household_demographics]
-------------------PhysicalDistribute
---------------------hashAgg[GLOBAL]
-----------------------PhysicalDistribute
-------------------------hashAgg[LOCAL]
---------------------------PhysicalProject
-----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+--------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
 --------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales]
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
---------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
+--------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 ----------------------------------------PhysicalOlapScan[time_dim]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((store.s_store_name = 'ese'))
---------------------------------------PhysicalOlapScan[store]
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+--------------------------------------PhysicalOlapScan[household_demographics]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((store.s_store_name = 'ese'))
+----------------------------------PhysicalOlapScan[store]
+------------------PhysicalDistribute
+--------------------hashAgg[GLOBAL]
+----------------------PhysicalDistribute
+------------------------hashAgg[LOCAL]
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+------------------------------PhysicalProject
+--------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+----------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+------------------------------------PhysicalProject
+--------------------------------------PhysicalOlapScan[store_sales]
+------------------------------------PhysicalDistribute
+--------------------------------------PhysicalProject
+----------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
+------------------------------------------PhysicalOlapScan[time_dim]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+----------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-------------------------------------PhysicalOlapScan[household_demographics]
+----------------------------------filter((store.s_store_name = 'ese'))
+------------------------------------PhysicalOlapScan[store]
 ----------------PhysicalDistribute
 ------------------hashAgg[GLOBAL]
 --------------------PhysicalDistribute
 ----------------------hashAgg[LOCAL]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
-------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
---------------------------------PhysicalProject
-----------------------------------PhysicalOlapScan[store_sales]
+--------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+----------------------------PhysicalProject
+------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+--------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+----------------------------------PhysicalProject
+------------------------------------PhysicalOlapScan[store_sales]
+----------------------------------PhysicalDistribute
+------------------------------------PhysicalProject
+--------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
+----------------------------------------PhysicalOlapScan[time_dim]
 --------------------------------PhysicalDistribute
 ----------------------------------PhysicalProject
-------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
---------------------------------------PhysicalOlapScan[time_dim]
-------------------------------PhysicalDistribute
---------------------------------PhysicalProject
-----------------------------------filter((store.s_store_name = 'ese'))
-------------------------------------PhysicalOlapScan[store]
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+--------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-----------------------------------PhysicalOlapScan[household_demographics]
+--------------------------------filter((store.s_store_name = 'ese'))
+----------------------------------PhysicalOlapScan[store]
 --------------PhysicalDistribute
 ----------------hashAgg[GLOBAL]
 ------------------PhysicalDistribute
 --------------------hashAgg[LOCAL]
 ----------------------PhysicalProject
-------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
-----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
-------------------------------PhysicalProject
---------------------------------PhysicalOlapScan[store_sales]
+------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+--------------------------PhysicalProject
+----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+------------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+--------------------------------PhysicalProject
+----------------------------------PhysicalOlapScan[store_sales]
+--------------------------------PhysicalDistribute
+----------------------------------PhysicalProject
+------------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
+--------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalDistribute
 --------------------------------PhysicalProject
-----------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
-------------------------------------PhysicalOlapScan[time_dim]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((store.s_store_name = 'ese'))
-----------------------------------PhysicalOlapScan[store]
+----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+------------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
---------------------------------PhysicalOlapScan[household_demographics]
+------------------------------filter((store.s_store_name = 'ese'))
+--------------------------------PhysicalOlapScan[store]
 ------------PhysicalDistribute
 --------------hashAgg[GLOBAL]
 ----------------PhysicalDistribute
 ------------------hashAgg[LOCAL]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[store_sales]
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+----------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+------------------------------PhysicalProject
+--------------------------------PhysicalOlapScan[store_sales]
+------------------------------PhysicalDistribute
+--------------------------------PhysicalProject
+----------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
+------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalDistribute
 ------------------------------PhysicalProject
---------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
-----------------------------------PhysicalOlapScan[time_dim]
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter((store.s_store_name = 'ese'))
---------------------------------PhysicalOlapScan[store]
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+----------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-------------------------------PhysicalOlapScan[household_demographics]
+----------------------------filter((store.s_store_name = 'ese'))
+------------------------------PhysicalOlapScan[store]
 ----------PhysicalDistribute
 ------------hashAgg[GLOBAL]
 --------------PhysicalDistribute
 ----------------hashAgg[LOCAL]
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
-------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[store_sales]
+--------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+----------------------PhysicalProject
+------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+--------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[store_sales]
+----------------------------PhysicalDistribute
+------------------------------PhysicalProject
+--------------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
+----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
---------------------------------PhysicalOlapScan[time_dim]
-------------------------PhysicalDistribute
---------------------------PhysicalProject
-----------------------------filter((store.s_store_name = 'ese'))
-------------------------------PhysicalOlapScan[store]
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+--------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-----------------------------PhysicalOlapScan[household_demographics]
+--------------------------filter((store.s_store_name = 'ese'))
+----------------------------PhysicalOlapScan[store]
 --------PhysicalDistribute
 ----------hashAgg[GLOBAL]
 ------------PhysicalDistribute
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
---------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
-----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[store_sales]
+------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+--------------------PhysicalProject
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+--------------------------PhysicalProject
+----------------------------PhysicalOlapScan[store_sales]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
+--------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
-------------------------------PhysicalOlapScan[time_dim]
-----------------------PhysicalDistribute
-------------------------PhysicalProject
---------------------------filter((store.s_store_name = 'ese'))
-----------------------------PhysicalOlapScan[store]
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+------------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalDistribute
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
---------------------------PhysicalOlapScan[household_demographics]
+------------------------filter((store.s_store_name = 'ese'))
+--------------------------PhysicalOlapScan[store]
 ------PhysicalDistribute
 --------hashAgg[GLOBAL]
 ----------PhysicalDistribute
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
-------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
---------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
-----------------------PhysicalProject
-------------------------PhysicalOlapScan[store_sales]
+----------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_store_sk = store.s_store_sk))otherCondition=()
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk))otherCondition=()
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_time_sk = time_dim.t_time_sk))otherCondition=()
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[store_sales]
+------------------------PhysicalDistribute
+--------------------------PhysicalProject
+----------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
+------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalDistribute
 ------------------------PhysicalProject
---------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
-----------------------------PhysicalOlapScan[time_dim]
---------------------PhysicalDistribute
-----------------------PhysicalProject
-------------------------filter((store.s_store_name = 'ese'))
---------------------------PhysicalOlapScan[store]
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
+----------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
-------------------------PhysicalOlapScan[household_demographics]
+----------------------filter((store.s_store_name = 'ese'))
+------------------------PhysicalOlapScan[store]
 
diff --git a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf13.groovy b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf13.groovy
index 8a6479ba73..7794d8f4be 100644
--- a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf13.groovy
+++ b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf13.groovy
@@ -103,5 +103,5 @@ suite("ds_rf13") {
     // def outFile = "regression-test/suites/nereids_tpcds_shape_sf100_p0/ddl/rf/rf.13"
     // File file = new File(outFile)
     // file.write(getRuntimeFilters(plan))
-     assertEquals("RF4[ss_sold_date_sk->[d_date_sk],RF3[ss_store_sk->[s_store_sk],RF2[ss_cdemo_sk->[cd_demo_sk],RF1[ss_hdemo_sk->[hd_demo_sk],RF0[ca_address_sk->[ss_addr_sk]", getRuntimeFilters(plan))
+     assertEquals("RF4[ss_store_sk->[s_store_sk],RF3[ss_cdemo_sk->[cd_demo_sk],RF2[hd_demo_sk->[ss_hdemo_sk],RF1[d_date_sk->[ss_sold_date_sk],RF0[ca_address_sk->[ss_addr_sk]", getRuntimeFilters(plan))
 }
diff --git a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf18.groovy b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf18.groovy
index 76e44365ac..da219a0328 100644
--- a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf18.groovy
+++ b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf18.groovy
@@ -86,5 +86,5 @@ suite("ds_rf18") {
     // File file = new File(outFile)
     // file.write(getRuntimeFilters(plan))
     
-     assertEquals("RF5[cs_item_sk->[i_item_sk],RF4[c_current_cdemo_sk->[cd_demo_sk],RF3[ca_address_sk->[c_current_addr_sk],RF2[c_customer_sk->[cs_bill_customer_sk],RF1[d_date_sk->[cs_sold_date_sk],RF0[cd_demo_sk->[cs_bill_cdemo_sk]", getRuntimeFilters(plan))
+     assertEquals("RF5[cs_item_sk->[i_item_sk],RF4[c_current_cdemo_sk->[cd_demo_sk],RF3[d_date_sk->[cs_sold_date_sk],RF2[cd_demo_sk->[cs_bill_cdemo_sk],RF1[c_customer_sk->[cs_bill_customer_sk],RF0[ca_address_sk->[c_current_addr_sk]", getRuntimeFilters(plan))
 }
diff --git a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf48.groovy b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf48.groovy
index a49a2af318..b8024c5a0c 100644
--- a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf48.groovy
+++ b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf48.groovy
@@ -119,5 +119,5 @@ suite("ds_rf48") {
     // File file = new File(outFile)
     // file.write(getRuntimeFilters(plan))
     
-     assertEquals("RF3[s_store_sk->[ss_store_sk],RF2[d_date_sk->[ss_sold_date_sk],RF1[cd_demo_sk->[ss_cdemo_sk],RF0[ca_address_sk->[ss_addr_sk]", getRuntimeFilters(plan))
+     assertEquals("RF3[s_store_sk->[ss_store_sk],RF2[d_date_sk->[ss_sold_date_sk],RF1[ca_address_sk->[ss_addr_sk],RF0[cd_demo_sk->[ss_cdemo_sk]", getRuntimeFilters(plan))
 }
diff --git a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf85.groovy b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf85.groovy
index 9f5999c833..833ab5491f 100644
--- a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf85.groovy
+++ b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf85.groovy
@@ -136,5 +136,5 @@ limit 100;
     // File file = new File(outFile)
     // file.write(getRuntimeFilters(plan))
 
-     assertEquals("RF9[wr_reason_sk->[r_reason_sk],RF8[ws_web_page_sk->[wp_web_page_sk],RF5[cd_marital_status->[cd_marital_status],RF6[cd_education_status->[cd_education_status],RF7[wr_returning_cdemo_sk->[cd_demo_sk],RF4[wr_refunded_cdemo_sk->[cd_demo_sk],RF3[ca_address_sk->[wr_refunded_addr_sk],RF1[ws_item_sk->[wr_item_sk],RF2[ws_order_number->[wr_order_number],RF0[d_date_sk->[ws_sold_date_sk]", getRuntimeFilters(plan))
+     assertEquals("RF9[r_reason_sk->[wr_reason_sk],RF8[wp_web_page_sk->[ws_web_page_sk],RF5[cd_marital_status->[cd_marital_status],RF6[cd_education_status->[cd_education_status],RF7[wr_returning_cdemo_sk->[cd_demo_sk],RF4[wr_refunded_cdemo_sk->[cd_demo_sk],RF3[ca_address_sk->[wr_refunded_addr_sk],RF1[ws_item_sk->[wr_item_sk],RF2[ws_order_number->[wr_order_number],RF0[d_date_sk->[ws_sold_date_sk]", getRuntimeFilters(plan))
 }
diff --git a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf88.groovy b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf88.groovy
index b33e94c632..590bcd9566 100644
--- a/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf88.groovy
+++ b/regression-test/suites/nereids_tpcds_shape_sf100_p0/rf/ds_rf88.groovy
@@ -146,5 +146,5 @@ from
     // File file = new File(outFile)
     // file.write(getRuntimeFilters(plan))
     
-     assertEquals("RF23[hd_demo_sk->[ss_hdemo_sk],RF22[s_store_sk->[ss_store_sk],RF21[t_time_sk->[ss_sold_time_sk],RF20[hd_demo_sk->[ss_hdemo_sk],RF19[s_store_sk->[ss_store_sk],RF18[t_time_sk->[ss_sold_time_sk],RF17[hd_demo_sk->[ss_hdemo_sk],RF16[s_store_sk->[ss_store_sk],RF15[t_time_sk->[ss_sold_time_sk],RF14[hd_demo_sk->[ss_hdemo_sk],RF13[s_store_sk->[ss_store_sk],RF12[t_time_sk->[ss_sold_time_sk],RF11[hd_demo_sk->[ss_hdemo_sk],RF10[s_store_sk->[ss_store_sk],RF9[t_time_sk->[ss_sold_time_sk],RF8[hd_demo_sk->[ss_hdemo_sk],RF7[s_store_sk->[ss_store_sk],RF6[t_time_sk->[ss_sold_time_sk],RF5[hd_demo_sk->[ss_hdemo_sk],RF4[s_store_sk->[ss_store_sk],RF3[t_time_sk->[ss_sold_time_sk],RF2[hd_demo_sk->[ss_hdemo_sk],RF1[s_store_sk->[ss_store_sk],RF0[t_time_sk->[ss_sold_time_sk]", getRuntimeFilters(plan))
+     assertEquals("RF23[s_store_sk->[ss_store_sk],RF22[hd_demo_sk->[ss_hdemo_sk],RF21[t_time_sk->[ss_sold_time_sk],RF20[s_store_sk->[ss_store_sk],RF19[hd_demo_sk->[ss_hdemo_sk],RF18[t_time_sk->[ss_sold_time_sk],RF17[s_store_sk->[ss_store_sk],RF16[hd_demo_sk->[ss_hdemo_sk],RF15[t_time_sk->[ss_sold_time_sk],RF14[s_store_sk->[ss_store_sk],RF13[hd_demo_sk->[ss_hdemo_sk],RF12[t_time_sk->[ss_sold_time_sk],RF11[s_store_sk->[ss_store_sk],RF10[hd_demo_sk->[ss_hdemo_sk],RF9[t_time_sk->[ss_sold_time_sk],RF8[s_store_sk->[ss_store_sk],RF7[hd_demo_sk->[ss_hdemo_sk],RF6[t_time_sk->[ss_sold_time_sk],RF5[s_store_sk->[ss_store_sk],RF4[hd_demo_sk->[ss_hdemo_sk],RF3[t_time_sk->[ss_sold_time_sk],RF2[s_store_sk->[ss_store_sk],RF1[hd_demo_sk->[ss_hdemo_sk],RF0[t_time_sk->[ss_sold_time_sk]", getRuntimeFilters(plan))
 }
diff --git a/tools/profile_viewer.py b/tools/profile_viewer.py
index 7fb77ceb5b..d8fce4f6c8 100644
--- a/tools/profile_viewer.py
+++ b/tools/profile_viewer.py
@@ -25,7 +25,7 @@ import argparse
 
 FE_HOST = "http://127.0.0.1:8030"
 MYSQL = "mysql -h:: -P9030 -u root "
-DB = "tpcds_sf1"
+DB = "tpcds_sf100"
 WORK_DIR="./tmp/"
 
 
@@ -290,9 +290,9 @@ def print_usage():
 if __name__ == '__main__':
     USAGE ="""
     1. execute a sql file, and draw its profile  
-          python3 profile_viewer.py -f [path to sql file] -o [output png file]
+          python3 profile_viewer.py -f [path to sql file] -t [png title]
     2. draw a given profile
-          python3 profile_viewer.py -qid [query_id] -o [output png file]
+          python3 profile_viewer.py -qid [query_id] -t [png title]
     
     graphviz is required(https://graphviz.org/)
     on linux: apt install graphviz