# Proposed changes Issue Number: close #6238 Co-authored-by: HappenLee <happenlee@hotmail.com> Co-authored-by: stdpain <34912776+stdpain@users.noreply.github.com> Co-authored-by: Zhengguo Yang <yangzhgg@gmail.com> Co-authored-by: wangbo <506340561@qq.com> Co-authored-by: emmymiao87 <522274284@qq.com> Co-authored-by: Pxl <952130278@qq.com> Co-authored-by: zhangstar333 <87313068+zhangstar333@users.noreply.github.com> Co-authored-by: thinker <zchw100@qq.com> Co-authored-by: Zeno Yang <1521564989@qq.com> Co-authored-by: Wang Shuo <wangshuo128@gmail.com> Co-authored-by: zhoubintao <35688959+zbtzbtzbt@users.noreply.github.com> Co-authored-by: Gabriel <gabrielleebuaa@gmail.com> Co-authored-by: xinghuayu007 <1450306854@qq.com> Co-authored-by: weizuo93 <weizuo@apache.org> Co-authored-by: yiguolei <guoleiyi@tencent.com> Co-authored-by: anneji-dev <85534151+anneji-dev@users.noreply.github.com> Co-authored-by: awakeljw <993007281@qq.com> Co-authored-by: taberylyang <95272637+taberylyang@users.noreply.github.com> Co-authored-by: Cui Kaifeng <48012748+azurenake@users.noreply.github.com> ## Problem Summary: ### 1. Some code from clickhouse **ClickHouse is an excellent implementation of the vectorized execution engine database, so here we have referenced and learned a lot from its excellent implementation in terms of data structure and function implementation. We are based on ClickHouse v19.16.2.2 and would like to thank the ClickHouse community and developers.** The following comment has been added to the code from Clickhouse, eg: // This file is copied from // https://github.com/ClickHouse/ClickHouse/blob/master/src/Interpreters/AggregationCommon.h // and modified by Doris ### 2. Support exec node and query: * vaggregation_node * vanalytic_eval_node * vassert_num_rows_node * vblocking_join_node * vcross_join_node * vempty_set_node * ves_http_scan_node * vexcept_node * vexchange_node * vintersect_node * vmysql_scan_node * vodbc_scan_node * volap_scan_node * vrepeat_node * vschema_scan_node * vselect_node * vset_operation_node * vsort_node * vunion_node * vhash_join_node You can run exec engine of SSB/TPCH and 70% TPCDS stand query test set. ### 3. Data Model Vec Exec Engine Support **Dup/Agg/Unq** table, Support Block Reader Vectorized. Segment Vec is working in process. ### 4. How to use 1. Set the environment variable `set enable_vectorized_engine = true; `(required) 2. Set the environment variable `set batch_size = 4096; ` (recommended) ### 5. Some diff from origin exec engine https://github.com/doris-vectorized/doris-vectorized/issues/294 ## Checklist(Required) 1. Does it affect the original behavior: (No) 2. Has unit tests been added: (Yes) 3. Has document been added or modified: (No) 4. Does it need to update dependencies: (No) 5. Are there any changes that cannot be rolled back: (Yes)
129 lines
4.9 KiB
C++
129 lines
4.9 KiB
C++
// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations
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// under the License.
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// This file is copied from
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// https://github.com/ClickHouse/ClickHouse/blob/master/src/AggregateFunctions/AggregateFunctionAvg.h
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// and modified by Doris
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#pragma once
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#include "common/status.h"
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#include "vec/aggregate_functions/aggregate_function.h"
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#include "vec/columns/columns_number.h"
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#include "vec/data_types/data_type_decimal.h"
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#include "vec/data_types/data_type_number.h"
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#include "vec/io/io_helper.h"
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namespace doris::vectorized {
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template <typename T>
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struct AggregateFunctionAvgData {
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T sum = 0;
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UInt64 count = 0;
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template <typename ResultT>
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ResultT result() const {
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if constexpr (std::is_floating_point_v<ResultT>)
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if constexpr (std::numeric_limits<ResultT>::is_iec559)
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return static_cast<ResultT>(sum) / count; /// allow division by zero
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if (!count)
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throw Exception("AggregateFunctionAvg with zero values", TStatusCode::VEC_LOGIC_ERROR);
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return static_cast<ResultT>(sum) / count;
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}
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void write(BufferWritable& buf) const {
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write_binary(sum, buf);
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write_binary(count, buf);
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}
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void read(BufferReadable& buf) {
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read_binary(sum, buf);
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read_binary(count, buf);
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}
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};
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/// Calculates arithmetic mean of numbers.
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template <typename T, typename Data>
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class AggregateFunctionAvg final
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: public IAggregateFunctionDataHelper<Data, AggregateFunctionAvg<T, Data>> {
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public:
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using ResultType = std::conditional_t<IsDecimalNumber<T>, Decimal128, Float64>;
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using ResultDataType = std::conditional_t<IsDecimalNumber<T>, DataTypeDecimal<Decimal128>,
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DataTypeNumber<Float64>>;
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using ColVecType = std::conditional_t<IsDecimalNumber<T>, ColumnDecimal<T>, ColumnVector<T>>;
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using ColVecResult = std::conditional_t<IsDecimalNumber<T>, ColumnDecimal<Decimal128>,
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ColumnVector<Float64>>;
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/// ctor for native types
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AggregateFunctionAvg(const DataTypes& argument_types_)
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: IAggregateFunctionDataHelper<Data, AggregateFunctionAvg<T, Data>>(argument_types_,
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{}),
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scale(0) {}
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/// ctor for Decimals
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AggregateFunctionAvg(const IDataType& data_type, const DataTypes& argument_types_)
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: IAggregateFunctionDataHelper<Data, AggregateFunctionAvg<T, Data>>(argument_types_,
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{}),
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scale(get_decimal_scale(data_type)) {}
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String get_name() const override { return "avg"; }
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DataTypePtr get_return_type() const override {
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if constexpr (IsDecimalNumber<T>)
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return std::make_shared<ResultDataType>(ResultDataType::max_precision(), scale);
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else
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return std::make_shared<ResultDataType>();
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}
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void add(AggregateDataPtr __restrict place, const IColumn** columns, size_t row_num,
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Arena*) const override {
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const auto& column = static_cast<const ColVecType&>(*columns[0]);
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this->data(place).sum += column.get_data()[row_num];
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++this->data(place).count;
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}
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void reset(AggregateDataPtr place) const override {
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this->data(place).sum = 0;
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this->data(place).count = 0;
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}
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void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena*) const override {
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this->data(place).sum += this->data(rhs).sum;
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this->data(place).count += this->data(rhs).count;
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}
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void serialize(ConstAggregateDataPtr __restrict place, BufferWritable& buf) const override {
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this->data(place).write(buf);
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}
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void deserialize(AggregateDataPtr __restrict place, BufferReadable& buf, Arena*) const override {
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this->data(place).read(buf);
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}
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void insert_result_into(ConstAggregateDataPtr __restrict place, IColumn& to) const override {
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auto& column = static_cast<ColVecResult&>(to);
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column.get_data().push_back(this->data(place).template result<ResultType>());
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}
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const char* get_header_file_path() const override { return __FILE__; }
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private:
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UInt32 scale;
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};
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} // namespace doris::vectorized
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