HappenLee commented on code in PR #9056: URL: https://github.com/apache/incubator-doris/pull/9056#discussion_r893062130
########## be/src/vec/functions/array/function_array_aggregation.cpp: ########## @@ -0,0 +1,300 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. +// This file is copied from +// https://github.com/ClickHouse/ClickHouse/blob/master/src/Functions/array/arrayAggregation.cpp +// and modified by Doris + +#include <type_traits> + +#include "vec/aggregate_functions/aggregate_function_avg.h" +#include "vec/aggregate_functions/aggregate_function_min_max.h" +#include "vec/aggregate_functions/aggregate_function_null.h" +#include "vec/aggregate_functions/aggregate_function_product.h" +#include "vec/aggregate_functions/aggregate_function_sum.h" +#include "vec/aggregate_functions/helpers.h" +#include "vec/columns/column_nullable.h" +#include "vec/common/arena.h" +#include "vec/core/types.h" +#include "vec/data_types/data_type.h" +#include "vec/data_types/data_type_nullable.h" +#include "vec/functions/array/function_array_mapped.h" +#include "vec/functions/simple_function_factory.h" + +namespace doris { +namespace vectorized { + +enum class AggregateOperation { MIN, MAX, SUM, AVERAGE, PRODUCT }; + +template <typename Element, AggregateOperation operation> +struct ArrayAggregateResultImpl; + +template <typename Element> +struct ArrayAggregateResultImpl<Element, AggregateOperation::MIN> { + using Result = Element; +}; + +template <typename Element> +struct ArrayAggregateResultImpl<Element, AggregateOperation::MAX> { + using Result = Element; +}; + +template <typename Element> +struct ArrayAggregateResultImpl<Element, AggregateOperation::AVERAGE> { + using Result = std::conditional_t<IsDecimalNumber<Element>, Decimal128, Float64>; +}; + +template <typename Element> +struct ArrayAggregateResultImpl<Element, AggregateOperation::PRODUCT> { + using Result = std::conditional_t<IsDecimalNumber<Element>, Decimal128, Float64>; +}; + +template <typename Element> +struct ArrayAggregateResultImpl<Element, AggregateOperation::SUM> { + using Result = std::conditional_t< + IsDecimalNumber<Element>, Decimal128, + std::conditional_t<IsFloatNumber<Element>, Float64, + std::conditional_t<std::is_same_v<Element, Int128>, Int128, Int64>>>; +}; + +template <typename Element, AggregateOperation operation> +using ArrayAggregateResult = typename ArrayAggregateResultImpl<Element, operation>::Result; + +template <AggregateOperation operation> +struct AggregateFunctionImpl; + +template <> +struct AggregateFunctionImpl<AggregateOperation::SUM> { + template <typename Element> + struct TypeTraits { + using ResultType = ArrayAggregateResult<Element, AggregateOperation::SUM>; + using AggregateDataType = AggregateFunctionSumData<ResultType>; + using Function = AggregateFunctionSum<Element, ResultType, AggregateDataType>; + }; +}; + +template <> +struct AggregateFunctionImpl<AggregateOperation::AVERAGE> { + template <typename Element> + struct TypeTraits { + struct AggregateDataType : public AggregateFunctionAvgData<Element> { + using AggregateFunctionAvgData<Element>::count; + using AggregateFunctionAvgData<Element>::sum; + + template <typename ResultT> + ResultT result() const { + return count ? AggregateFunctionAvgData<Element>::template result<ResultT>() + : static_cast<ResultT>(sum); + } + }; + + using ResultType = ArrayAggregateResult<Element, AggregateOperation::AVERAGE>; + using Function = AggregateFunctionAvg<Element, AggregateDataType>; + static_assert(std::is_same_v<ResultType, typename Function::ResultType>, + "ResultType doesn't match."); + }; +}; + +template <> +struct AggregateFunctionImpl<AggregateOperation::PRODUCT> { + template <typename Element> + struct TypeTraits { + using ResultType = ArrayAggregateResult<Element, AggregateOperation::PRODUCT>; + using AggregateDataType = AggregateFunctionProductData<Element>; + using Function = AggregateFunctionProduct<Element, ResultType, AggregateDataType>; + }; +}; + +template <typename Derived> +struct AggregateFunction { + template <typename T> + using Function = typename Derived::template TypeTraits<T>::Function; + + static auto create(const DataTypePtr& data_type) -> AggregateFunctionPtr { + DataTypes data_types = {data_type}; + AggregateFunctionPtr function; + + if (data_type->is_nullable()) { + const auto& nested_data_type = + static_cast<const DataTypeNullable&>(*data_type).get_nested_type(); + auto nested_function = create(nested_data_type); + function.reset(new AggregateFunctionNullUnary<true>(nested_function, data_types, {})); + } else { + if (is_decimal(data_type)) { + function.reset( + create_with_decimal_type<Function>(*data_type, *data_type, data_types)); + } else { + function.reset(create_with_numeric_type<Function>(*data_type, data_types)); + } + } + return function; + } +}; + +template <AggregateOperation operation> +struct ArrayAggregateImpl { + using column_type = ColumnArray; + using data_type = DataTypeArray; + + static DataTypePtr get_return_type(const DataTypeArray* data_type_array) { + using Function = AggregateFunction<AggregateFunctionImpl<operation>>; + auto function = Function::create(data_type_array->get_nested_type()); + return function->get_return_type(); + } + + static Status execute(Block& block, size_t result, const DataTypeArray* data_type_array, + const ColumnArray& array) { + ColumnPtr res; + DataTypePtr type = data_type_array->get_nested_type(); + const IColumn* data = array.get_data_ptr().get(); + + const auto& offsets = array.get_offsets(); + if (execute_type<Int8>(res, type, data, offsets) || + execute_type<Int16>(res, type, data, offsets) || + execute_type<Int32>(res, type, data, offsets) || + execute_type<Int64>(res, type, data, offsets) || + execute_type<Int128>(res, type, data, offsets) || + execute_type<Float32>(res, type, data, offsets) || + execute_type<Float64>(res, type, data, offsets) || + execute_type<Decimal128>(res, type, data, offsets)) { + block.replace_by_position(result, std::move(res)); + return Status::OK(); + } else { + return Status::RuntimeError("Unexpected column for aggregation: " + data->get_name()); + } + } + + template <typename Element> + static bool execute_type(ColumnPtr& res_ptr, const DataTypePtr& type, const IColumn* data, + const ColumnArray::Offsets& offsets) { + using ColVecType = ColumnVectorOrDecimal<Element>; + using ResultType = ArrayAggregateResult<Element, operation>; + using ColVecResultType = ColumnVectorOrDecimal<ResultType>; + using Function = AggregateFunction<AggregateFunctionImpl<operation>>; + + const ColVecType* column = + data->is_nullable() + ? check_and_get_column<ColVecType>( + static_cast<const ColumnNullable*>(data)->get_nested_column()) + : check_and_get_column<ColVecType>(&*data); + if (!column) { + return false; + } + + ColumnPtr res_column; + if constexpr (IsDecimalNumber<Element>) { + res_column = + make_nullable(ColVecResultType::create(offsets.size(), column->get_scale())); + } else { + res_column = make_nullable(ColVecResultType::create(offsets.size())); + } + static_cast<ColumnNullable&>(res_column->assume_mutable_ref()).clear(); Review Comment: `res_column = make_nullable(res_column);` ########## be/src/vec/functions/array/function_array_mapped.h: ########## @@ -0,0 +1,76 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. +// This file is copied from +// https://github.com/ClickHouse/ClickHouse/blob/master/src/Functions/array/FunctionArrayMapped.h +// and modified by Doris + +#include "vec/columns/column.h" +#include "vec/columns/column_nullable.h" +#include "vec/data_types/data_type_array.h" +#include "vec/data_types/data_type_nullable.h" +#include "vec/functions/function.h" + +namespace doris { +namespace vectorized { + +/** Higher-order functions for arrays. + * These functions optionally apply a map (transform) to array (or multiple arrays of identical size) by lambda function, + * and return some result based on that transformation. + * + * Examples: + * arrayMap(x1,...,xn -> expression, array1,...,arrayn) - apply the expression to each element of the array (or set of parallel arrays). + * arrayFilter(x -> predicate, array) - leave in the array only the elements for which the expression is true. + * + * For some functions arrayCount, arrayExists, arrayAll, an overload of the form f(array) is available, + * which works in the same way as f(x -> x, array). + * + * See the example of Impl template parameter in arrayMap.cpp + */ +template <typename Impl, typename Name> +class FunctionArrayMapped : public IFunction { +public: + static constexpr auto name = Name::name; + static FunctionPtr create() { return std::make_shared<FunctionArrayMapped>(); } + + String get_name() const override { return name; } + Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments, + size_t result, size_t input_rows_count) override { + const auto& typed_column = block.get_by_position(arguments[0]); + const typename Impl::column_type* column_array; + if (typed_column.column->is_nullable()) { + column_array = check_and_get_column<const typename Impl::column_type>( + static_cast<const ColumnNullable*>(typed_column.column.get()) + ->get_nested_column_ptr() + .get()); + } else { + column_array = check_and_get_column<const typename Impl::column_type>( + typed_column.column.get()); + } + const auto* data_type_array = + static_cast<const DataTypeArray*>(remove_nullable(typed_column.type).get()); + return Impl::execute(block, result, data_type_array, *column_array); + } + size_t get_number_of_arguments() const override { return 1; } + DataTypePtr get_return_type_impl(const DataTypes& arguments) const override { + const DataTypeArray* data_type_array = + static_cast<const DataTypeArray*>(remove_nullable(arguments[0]).get()); + return Impl::get_return_type(data_type_array); Review Comment: `make_nullable(Impl::get_return_type(data_type_array)`; -- This is an automated message from the Apache Git Service. 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