mirror of
https://github.com/ClickHouse/ClickHouse.git
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2380 lines
103 KiB
C++
2380 lines
103 KiB
C++
#pragma once
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// Include this first, because `#define _asan_poison_address` from
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// llvm/Support/Compiler.h conflicts with its forward declaration in
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// sanitizer/asan_interface.h
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#include <memory>
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#include <type_traits>
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#include <base/wide_integer_to_string.h>
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#include <Columns/ColumnAggregateFunction.h>
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#include <Columns/ColumnConst.h>
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#include <Columns/ColumnDecimal.h>
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#include <Columns/ColumnFixedString.h>
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#include <Columns/ColumnNullable.h>
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#include <Columns/ColumnString.h>
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#include <Columns/ColumnVector.h>
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#include <Core/DecimalFunctions.h>
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#include <DataTypes/DataTypeAggregateFunction.h>
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#include <DataTypes/DataTypeDate.h>
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#include <DataTypes/DataTypeDateTime.h>
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#include <DataTypes/DataTypeDateTime64.h>
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#include <DataTypes/DataTypeFactory.h>
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#include <DataTypes/DataTypeFixedString.h>
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#include <DataTypes/DataTypeInterval.h>
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#include <DataTypes/DataTypeTuple.h>
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#include <DataTypes/DataTypeString.h>
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#include <DataTypes/DataTypeIPv4andIPv6.h>
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#include <DataTypes/DataTypesDecimal.h>
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#include <DataTypes/DataTypesNumber.h>
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#include <DataTypes/Native.h>
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#include <DataTypes/NumberTraits.h>
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#include <Functions/DivisionUtils.h>
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#include <Functions/FunctionFactory.h>
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#include <Functions/FunctionHelpers.h>
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#include <Functions/IFunction.h>
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#include <Functions/IsOperation.h>
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#include <Functions/castTypeToEither.h>
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#include <Interpreters/castColumn.h>
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#include <base/TypeList.h>
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#include <base/map.h>
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#include <Common/FieldVisitorsAccurateComparison.h>
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#include <Common/assert_cast.h>
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#include <Common/typeid_cast.h>
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#include <Common/Arena.h>
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#include <DataTypes/DataTypeLowCardinality.h>
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#include <Interpreters/Context.h>
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#if USE_EMBEDDED_COMPILER
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# include <llvm/IR/IRBuilder.h>
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#endif
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#include <cassert>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int ILLEGAL_COLUMN;
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extern const int ILLEGAL_TYPE_OF_ARGUMENT;
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extern const int LOGICAL_ERROR;
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extern const int DECIMAL_OVERFLOW;
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extern const int CANNOT_ADD_DIFFERENT_AGGREGATE_STATES;
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extern const int NUMBER_OF_ARGUMENTS_DOESNT_MATCH;
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}
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namespace traits_
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{
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struct InvalidType; /// Used to indicate undefined operation
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template <bool V, typename T> struct Case : std::bool_constant<V> { using type = T; };
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/// Switch<Case<C0, T0>, ...> -- select the first Ti for which Ci is true, InvalidType if none.
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template <typename... Ts> using Switch = typename std::disjunction<Ts..., Case<true, InvalidType>>::type;
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template <class T>
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using DataTypeFromFieldType = std::conditional_t<std::is_same_v<T, NumberTraits::Error>,
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InvalidType, DataTypeNumber<T>>;
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template <typename DataType> constexpr bool IsIntegral = false;
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template <> inline constexpr bool IsIntegral<DataTypeUInt8> = true;
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template <> inline constexpr bool IsIntegral<DataTypeUInt16> = true;
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template <> inline constexpr bool IsIntegral<DataTypeUInt32> = true;
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template <> inline constexpr bool IsIntegral<DataTypeUInt64> = true;
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template <> inline constexpr bool IsIntegral<DataTypeInt8> = true;
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template <> inline constexpr bool IsIntegral<DataTypeInt16> = true;
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template <> inline constexpr bool IsIntegral<DataTypeInt32> = true;
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template <> inline constexpr bool IsIntegral<DataTypeInt64> = true;
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template <typename DataType> constexpr bool IsExtended = false;
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template <> inline constexpr bool IsExtended<DataTypeUInt128> = true;
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template <> inline constexpr bool IsExtended<DataTypeUInt256> = true;
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template <> inline constexpr bool IsExtended<DataTypeInt128> = true;
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template <> inline constexpr bool IsExtended<DataTypeInt256> = true;
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template <typename DataType> constexpr bool IsIntegralOrExtended = IsIntegral<DataType> || IsExtended<DataType>;
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template <typename DataType> constexpr bool IsIntegralOrExtendedOrDecimal =
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IsIntegralOrExtended<DataType> ||
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IsDataTypeDecimal<DataType>;
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template <typename DataType> constexpr bool IsFloatingPoint = false;
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template <> inline constexpr bool IsFloatingPoint<DataTypeFloat32> = true;
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template <> inline constexpr bool IsFloatingPoint<DataTypeFloat64> = true;
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template <typename DataType> constexpr bool IsDateOrDateTime = false;
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template <> inline constexpr bool IsDateOrDateTime<DataTypeDate> = true;
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template <> inline constexpr bool IsDateOrDateTime<DataTypeDateTime> = true;
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template <typename DataType> constexpr bool IsIPv4 = false;
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template <> inline constexpr bool IsIPv4<DataTypeIPv4> = true;
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template <typename T0, typename T1> constexpr bool UseLeftDecimal = false;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal256>, DataTypeDecimal<Decimal128>> = true;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal256>, DataTypeDecimal<Decimal64>> = true;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal256>, DataTypeDecimal<Decimal32>> = true;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal128>, DataTypeDecimal<Decimal32>> = true;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal128>, DataTypeDecimal<Decimal64>> = true;
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template <> inline constexpr bool UseLeftDecimal<DataTypeDecimal<Decimal64>, DataTypeDecimal<Decimal32>> = true;
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template <typename DataType> constexpr bool IsFixedString = false;
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template <> inline constexpr bool IsFixedString<DataTypeFixedString> = true;
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template <typename DataType> constexpr bool IsString = false;
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template <> inline constexpr bool IsString<DataTypeString> = true;
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template <template <typename, typename> class Operation, typename LeftDataType, typename RightDataType>
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struct BinaryOperationTraits
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{
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using T0 = typename LeftDataType::FieldType;
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using T1 = typename RightDataType::FieldType;
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private: /// it's not correct for Decimal
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using Op = Operation<T0, T1>;
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public:
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static constexpr bool allow_decimal = IsOperation<Operation>::allow_decimal;
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/// Appropriate result type for binary operator on numeric types. "Date" can also mean
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/// DateTime, but if both operands are Dates, their type must be the same (e.g. Date - DateTime is invalid).
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using ResultDataType = Switch<
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/// Decimal cases
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Case<!allow_decimal && (IsDataTypeDecimal<LeftDataType> || IsDataTypeDecimal<RightDataType>), InvalidType>,
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Case<
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IsDataTypeDecimal<LeftDataType> && IsDataTypeDecimal<RightDataType> && UseLeftDecimal<LeftDataType, RightDataType>,
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LeftDataType>,
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Case<IsDataTypeDecimal<LeftDataType> && IsDataTypeDecimal<RightDataType>, RightDataType>,
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Case<IsDataTypeDecimal<LeftDataType> && IsIntegralOrExtended<RightDataType>, LeftDataType>,
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Case<IsDataTypeDecimal<RightDataType> && IsIntegralOrExtended<LeftDataType>, RightDataType>,
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/// e.g Decimal +-*/ Float, least(Decimal, Float), greatest(Decimal, Float) = Float64
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Case<IsOperation<Operation>::allow_decimal && IsDataTypeDecimal<LeftDataType> && IsFloatingPoint<RightDataType>, DataTypeFloat64>,
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Case<IsOperation<Operation>::allow_decimal && IsDataTypeDecimal<RightDataType> && IsFloatingPoint<LeftDataType>, DataTypeFloat64>,
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Case<IsOperation<Operation>::bit_hamming_distance && IsIntegral<LeftDataType> && IsIntegral<RightDataType>, DataTypeUInt8>,
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Case<IsOperation<Operation>::bit_hamming_distance && IsFixedString<LeftDataType> && IsFixedString<RightDataType>, DataTypeUInt16>,
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Case<IsOperation<Operation>::bit_hamming_distance && IsString<LeftDataType> && IsString<RightDataType>, DataTypeUInt64>,
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/// Decimal <op> Real is not supported (traditional DBs convert Decimal <op> Real to Real)
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Case<IsDataTypeDecimal<LeftDataType> && !IsIntegralOrExtendedOrDecimal<RightDataType>, InvalidType>,
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Case<IsDataTypeDecimal<RightDataType> && !IsIntegralOrExtendedOrDecimal<LeftDataType>, InvalidType>,
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/// number <op> number -> see corresponding impl
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Case<!IsDateOrDateTime<LeftDataType> && !IsDateOrDateTime<RightDataType>, DataTypeFromFieldType<typename Op::ResultType>>,
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/// Date + Integral -> Date
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/// Integral + Date -> Date
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Case<
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IsOperation<Operation>::plus,
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Switch<Case<IsIntegral<RightDataType>, LeftDataType>, Case<IsIntegral<LeftDataType>, RightDataType>>>,
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/// Date - Date -> Int32
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/// Date - Integral -> Date
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Case<
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IsOperation<Operation>::minus,
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Switch<
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Case<std::is_same_v<LeftDataType, RightDataType>, DataTypeInt32>,
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Case<IsDateOrDateTime<LeftDataType> && IsIntegral<RightDataType>, LeftDataType>>>,
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/// least(Date, Date) -> Date
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/// greatest(Date, Date) -> Date
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Case<
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std::is_same_v<LeftDataType, RightDataType> && (IsOperation<Operation>::least || IsOperation<Operation>::greatest),
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LeftDataType>,
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/// Date % Int32 -> Int32
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/// Date % Float -> Float64
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Case<
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IsOperation<Operation>::modulo || IsOperation<Operation>::positive_modulo,
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Switch<
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Case<IsDateOrDateTime<LeftDataType> && IsIntegral<RightDataType>, RightDataType>,
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Case<IsDateOrDateTime<LeftDataType> && IsFloatingPoint<RightDataType>, DataTypeFloat64>>>>;
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};
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}
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namespace impl_
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{
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/** Arithmetic operations: +, -, *, /, %,
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* intDiv (integer division)
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* Bitwise operations: |, &, ^, ~.
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* Etc.
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*/
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enum class OpCase { Vector, LeftConstant, RightConstant };
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constexpr const auto & undec(const auto & x) { return x; }
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constexpr const auto & undec(const is_decimal auto & x) { return x.value; }
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template <typename A, typename B, typename Op, typename OpResultType = typename Op::ResultType>
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struct BinaryOperation
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{
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using ResultType = OpResultType;
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static const constexpr bool allow_fixed_string = false;
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static const constexpr bool allow_string_integer = false;
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template <OpCase op_case>
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static void NO_INLINE process(const A * __restrict a, const B * __restrict b, ResultType * __restrict c, size_t size, const NullMap * right_nullmap = nullptr)
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{
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if constexpr (op_case == OpCase::RightConstant)
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{
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if (right_nullmap && (*right_nullmap)[0])
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return;
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for (size_t i = 0; i < size; ++i)
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c[i] = Op::template apply<ResultType>(a[i], *b);
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}
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else
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{
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if (right_nullmap)
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{
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for (size_t i = 0; i < size; ++i)
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if ((*right_nullmap)[i])
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c[i] = ResultType();
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else
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apply<op_case>(a, b, c, i);
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}
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else
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for (size_t i = 0; i < size; ++i)
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apply<op_case>(a, b, c, i);
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}
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}
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static ResultType process(A a, B b) { return Op::template apply<ResultType>(a, b); }
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private:
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template <OpCase op_case>
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static inline void apply(const A * __restrict a, const B * __restrict b, ResultType * __restrict c, size_t i)
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{
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if constexpr (op_case == OpCase::Vector)
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c[i] = Op::template apply<ResultType>(a[i], b[i]);
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else
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c[i] = Op::template apply<ResultType>(*a, b[i]);
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}
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};
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template <typename B, typename Op>
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struct StringIntegerOperationImpl
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{
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template <OpCase op_case>
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static void NO_INLINE processFixedString(const UInt8 * __restrict in_vec, const UInt64 n, const B * __restrict b, ColumnFixedString::Chars & out_vec, size_t size)
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{
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size_t prev_offset = 0;
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out_vec.reserve(n * size);
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for (size_t i = 0; i < size; ++i)
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{
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if constexpr (op_case == OpCase::LeftConstant)
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{
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Op::apply(&in_vec[0], &in_vec[n], b[i], out_vec);
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}
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else
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{
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size_t new_offset = prev_offset + n;
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if constexpr (op_case == OpCase::Vector)
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{
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Op::apply(&in_vec[prev_offset], &in_vec[new_offset], b[i], out_vec);
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}
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else
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{
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Op::apply(&in_vec[prev_offset], &in_vec[new_offset], b[0], out_vec);
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}
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prev_offset = new_offset;
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}
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}
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}
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template <OpCase op_case>
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static void NO_INLINE processString(const UInt8 * __restrict in_vec, const UInt64 * __restrict in_offsets, const B * __restrict b, ColumnString::Chars & out_vec, ColumnString::Offsets & out_offsets, size_t size)
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{
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size_t prev_offset = 0;
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for (size_t i = 0; i < size; ++i)
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{
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if constexpr (op_case == OpCase::LeftConstant)
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{
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Op::apply(&in_vec[0], &in_vec[in_offsets[0] - 1], b[i], out_vec, out_offsets);
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}
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else
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{
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size_t new_offset = in_offsets[i];
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if constexpr (op_case == OpCase::Vector)
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{
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Op::apply(&in_vec[prev_offset], &in_vec[new_offset - 1], b[i], out_vec, out_offsets);
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}
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else
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{
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Op::apply(&in_vec[prev_offset], &in_vec[new_offset - 1], b[0], out_vec, out_offsets);
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}
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prev_offset = new_offset;
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}
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}
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}
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};
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template <typename Op>
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struct FixedStringOperationImpl
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{
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template <OpCase op_case>
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static void NO_INLINE process(
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const UInt8 * __restrict a, const UInt8 * __restrict b, UInt8 * __restrict result,
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size_t size, [[maybe_unused]] size_t N)
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{
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if constexpr (op_case == OpCase::Vector)
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for (size_t i = 0; i < size; ++i)
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result[i] = Op::template apply<UInt8>(a[i], b[i]);
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else if constexpr (op_case == OpCase::LeftConstant)
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withConst<true>(b, a, result, size, N);
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else
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withConst<false>(a, b, result, size, N);
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}
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private:
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template <bool inverted>
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static void NO_INLINE withConst(const UInt8 * __restrict a, const UInt8 * __restrict b, UInt8 * __restrict c, size_t size, size_t N)
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{
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/// These complications are needed to avoid integer division in inner loop.
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/// Create a pattern of repeated values of b with at least 16 bytes,
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/// so we can read 16 bytes of this repeated pattern starting from any offset inside b.
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///
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/// Example:
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///
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/// N = 6
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/// ------
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/// [abcdefabcdefabcdefabc]
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/// ^^^^^^^^^^^^^^^^
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/// 16 bytes starting from the last offset inside b.
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const size_t b_repeated_size = N + 15;
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UInt8 b_repeated[b_repeated_size];
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for (size_t i = 0; i < b_repeated_size; ++i)
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b_repeated[i] = b[i % N];
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size_t b_offset = 0;
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const size_t b_increment = 16 % N;
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/// Example:
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///
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/// At first iteration we copy 16 bytes at offset 0 from b_repeated:
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/// [abcdefabcdefabcdefabc]
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/// ^^^^^^^^^^^^^^^^
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/// At second iteration we copy 16 bytes at offset 4 = 16 % 6 from b_repeated:
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/// [abcdefabcdefabcdefabc]
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/// ^^^^^^^^^^^^^^^^
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/// At third iteration we copy 16 bytes at offset 2 = (16 * 2) % 6 from b_repeated:
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/// [abcdefabcdefabcdefabc]
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/// ^^^^^^^^^^^^^^^^
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/// PaddedPODArray allows overflow for 15 bytes.
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for (size_t i = 0; i < size; i += 16)
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{
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/// This loop is formed in a way to be vectorized into two SIMD mov.
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for (size_t j = 0; j < 16; ++j)
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c[i + j] = inverted
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? Op::template apply<UInt8>(a[i + j], b_repeated[b_offset + j])
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: Op::template apply<UInt8>(b_repeated[b_offset + j], a[i + j]);
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b_offset += b_increment;
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if (b_offset >= N) /// This condition is easily predictable.
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b_offset -= N;
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}
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}
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};
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template <typename Op>
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struct FixedStringReduceOperationImpl
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{
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template <OpCase op_case>
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static void inline process(const UInt8 * __restrict a, const UInt8 * __restrict b, UInt16 * __restrict result, size_t size, size_t N)
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{
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if constexpr (op_case == OpCase::Vector)
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vectorVector(a, b, result, size, N);
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else if constexpr (op_case == OpCase::LeftConstant)
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vectorConstant(b, a, result, size, N);
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else
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vectorConstant(a, b, result, size, N);
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}
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private:
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static void vectorVector(const UInt8 * __restrict a, const UInt8 * __restrict b, UInt16 * __restrict result, size_t size, size_t N)
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{
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for (size_t i = 0; i < size; ++i)
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{
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size_t offset = i * N;
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for (size_t j = 0; j < N; ++j)
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{
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result[i] += Op::template apply<UInt8>(a[offset + j], b[offset + j]);
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}
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}
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}
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static void vectorConstant(const UInt8 * __restrict a, const UInt8 * __restrict b, UInt16 * __restrict result, size_t size, size_t N)
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{
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for (size_t i = 0; i < size; ++i)
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{
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size_t offset = i * N;
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for (size_t j = 0; j < N; ++j)
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{
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result[i] += Op::template apply<UInt8>(a[offset + j], b[j]);
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}
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}
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}
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};
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template <typename Op>
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struct StringReduceOperationImpl
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{
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static void vectorVector(
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const ColumnString::Chars & a,
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const ColumnString::Offsets & offsets_a,
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const ColumnString::Chars & b,
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const ColumnString::Offsets & offsets_b,
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PaddedPODArray<UInt64> & res)
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{
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size_t size = res.size();
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for (size_t i = 0; i < size; ++i)
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{
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res[i] = process(
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a.data() + offsets_a[i - 1],
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a.data() + offsets_a[i] - 1,
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b.data() + offsets_b[i - 1],
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b.data() + offsets_b[i] - 1);
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}
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}
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static void
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vectorConstant(const ColumnString::Chars & a, const ColumnString::Offsets & offsets_a, std::string_view b, PaddedPODArray<UInt64> & res)
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{
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size_t size = res.size();
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for (size_t i = 0; i < size; ++i)
|
|
{
|
|
res[i] = process(
|
|
a.data() + offsets_a[i - 1],
|
|
a.data() + offsets_a[i] - 1,
|
|
reinterpret_cast<const UInt8 *>(b.data()),
|
|
reinterpret_cast<const UInt8 *>(b.data()) + b.size());
|
|
}
|
|
}
|
|
|
|
static inline UInt64 constConst(std::string_view a, std::string_view b)
|
|
{
|
|
return process(
|
|
reinterpret_cast<const UInt8 *>(a.data()),
|
|
reinterpret_cast<const UInt8 *>(a.data()) + a.size(),
|
|
reinterpret_cast<const UInt8 *>(b.data()),
|
|
reinterpret_cast<const UInt8 *>(b.data()) + b.size());
|
|
}
|
|
|
|
private:
|
|
static UInt64 process(const UInt8 * __restrict start_a, const UInt8 * __restrict end_a, const UInt8 * start_b, const UInt8 * end_b)
|
|
{
|
|
UInt64 res = 0;
|
|
while (start_a < end_a && start_b < end_b)
|
|
res += Op::template apply<UInt8>(*start_a++, *start_b++);
|
|
|
|
while (start_a < end_a)
|
|
res += Op::template apply<UInt8>(*start_a++, 0);
|
|
while (start_b < end_b)
|
|
res += Op::template apply<UInt8>(0, *start_b++);
|
|
return res;
|
|
}
|
|
};
|
|
|
|
template <typename A, typename B, typename Op, typename ResultType = typename Op::ResultType>
|
|
struct BinaryOperationImpl : BinaryOperation<A, B, Op, ResultType> { };
|
|
|
|
/**
|
|
* Binary operations with Decimals (either Decimal OP Decimal or Decimal Op Float) need to scale the args correctly.
|
|
* - + (plus), - (minus), * (multiply), least and greatest operations scale one of the args (which scale factor is not 1).
|
|
* The resulting scale is either left or the right scale.
|
|
* - / (divide) operation scales the first argument.
|
|
* The resulting scale is the first one's.
|
|
*/
|
|
template <template <typename, typename> typename Operation, class OpResultType, bool check_overflow = true>
|
|
struct DecimalBinaryOperation
|
|
{
|
|
private:
|
|
using ResultType = OpResultType; // e.g. Decimal32
|
|
using NativeResultType = NativeType<ResultType>; // e.g. UInt32 for Decimal32
|
|
|
|
using ResultContainerType = typename ColumnVectorOrDecimal<ResultType>::Container;
|
|
|
|
public:
|
|
template <OpCase op_case, bool is_decimal_a, bool is_decimal_b>
|
|
static void NO_INLINE process(const auto & a, const auto & b, ResultContainerType & c,
|
|
NativeResultType scale_a, NativeResultType scale_b, const NullMap * right_nullmap = nullptr)
|
|
{
|
|
if constexpr (op_case == OpCase::LeftConstant) static_assert(!is_decimal<decltype(a)>);
|
|
if constexpr (op_case == OpCase::RightConstant) static_assert(!is_decimal<decltype(b)>);
|
|
|
|
size_t size;
|
|
|
|
if constexpr (op_case == OpCase::LeftConstant)
|
|
size = b.size();
|
|
else
|
|
size = a.size();
|
|
|
|
if constexpr (is_plus_minus_compare)
|
|
{
|
|
if (scale_a != 1)
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = applyScaled<true>(
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::LeftConstant>(a, i)),
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::RightConstant>(b, i)),
|
|
scale_a);
|
|
return;
|
|
}
|
|
else if (scale_b != 1)
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = applyScaled<false>(
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::LeftConstant>(a, i)),
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::RightConstant>(b, i)),
|
|
scale_b);
|
|
return;
|
|
}
|
|
}
|
|
else if constexpr (is_multiply)
|
|
{
|
|
if (scale_a != 1)
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = applyScaled<true, false>(
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::LeftConstant>(a, i)),
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::RightConstant>(b, i)),
|
|
scale_a);
|
|
return;
|
|
}
|
|
else if (scale_b != 1)
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = applyScaled<false, false>(
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::LeftConstant>(a, i)),
|
|
static_cast<NativeResultType>(unwrap<op_case, OpCase::RightConstant>(b, i)),
|
|
scale_b);
|
|
return;
|
|
}
|
|
|
|
}
|
|
else if constexpr (is_division && is_decimal_b)
|
|
{
|
|
processWithRightNullmapImpl<op_case>(a, b, c, size, right_nullmap, [&scale_a](const auto & left, const auto & right)
|
|
{
|
|
return applyScaledDiv<is_decimal_a>(
|
|
static_cast<NativeResultType>(left), right, scale_a);
|
|
});
|
|
return;
|
|
}
|
|
|
|
processWithRightNullmapImpl<op_case>(
|
|
a, b, c, size, right_nullmap,
|
|
[](const auto & left, const auto & right)
|
|
{
|
|
return apply(
|
|
static_cast<NativeResultType>(left),
|
|
static_cast<NativeResultType>(right));
|
|
});
|
|
}
|
|
|
|
template <bool is_decimal_a, bool is_decimal_b, class A, class B>
|
|
static ResultType process(A a, B b, NativeResultType scale_a, NativeResultType scale_b)
|
|
requires(!is_decimal<A> && !is_decimal<B>)
|
|
{
|
|
if constexpr (is_division && is_decimal_b)
|
|
return applyScaledDiv<is_decimal_a>(a, b, scale_a);
|
|
else if constexpr (is_plus_minus_compare)
|
|
{
|
|
if (scale_a != 1)
|
|
return applyScaled<true>(a, b, scale_a);
|
|
if (scale_b != 1)
|
|
return applyScaled<false>(a, b, scale_b);
|
|
}
|
|
|
|
return apply(a, b);
|
|
}
|
|
|
|
private:
|
|
template <OpCase op_case, typename ApplyFunc>
|
|
static inline void processWithRightNullmapImpl(const auto & a, const auto & b, ResultContainerType & c, size_t size, const NullMap * right_nullmap, ApplyFunc apply_func)
|
|
{
|
|
if (right_nullmap)
|
|
{
|
|
if constexpr (op_case == OpCase::RightConstant)
|
|
{
|
|
if ((*right_nullmap)[0])
|
|
return;
|
|
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = apply_func(undec(a[i]), undec(b));
|
|
}
|
|
else
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
{
|
|
if ((*right_nullmap)[i])
|
|
c[i] = ResultType();
|
|
else
|
|
c[i] = apply_func(unwrap<op_case, OpCase::LeftConstant>(a, i), undec(b[i]));
|
|
}
|
|
}
|
|
}
|
|
else
|
|
for (size_t i = 0; i < size; ++i)
|
|
c[i] = apply_func(unwrap<op_case, OpCase::LeftConstant>(a, i), unwrap<op_case, OpCase::RightConstant>(b, i));
|
|
}
|
|
|
|
static constexpr bool is_plus_minus = IsOperation<Operation>::plus ||
|
|
IsOperation<Operation>::minus;
|
|
static constexpr bool is_multiply = IsOperation<Operation>::multiply;
|
|
static constexpr bool is_float_division = IsOperation<Operation>::div_floating;
|
|
static constexpr bool is_int_division = IsOperation<Operation>::div_int ||
|
|
IsOperation<Operation>::div_int_or_zero;
|
|
static constexpr bool is_division = is_float_division || is_int_division;
|
|
static constexpr bool is_compare = IsOperation<Operation>::least ||
|
|
IsOperation<Operation>::greatest;
|
|
static constexpr bool is_plus_minus_compare = is_plus_minus || is_compare;
|
|
static constexpr bool can_overflow = is_plus_minus || is_multiply;
|
|
|
|
using Op = std::conditional_t<is_float_division,
|
|
DivideIntegralImpl<NativeResultType, NativeResultType>, /// substitute divide by intDiv (throw on division by zero)
|
|
Operation<NativeResultType, NativeResultType>>;
|
|
|
|
template <OpCase op_case, OpCase target, class E>
|
|
static auto unwrap(const E& elem, size_t i)
|
|
{
|
|
if constexpr (op_case == target)
|
|
return undec(elem);
|
|
else
|
|
return undec(elem[i]);
|
|
}
|
|
|
|
/// there's implicit type conversion here
|
|
static NativeResultType apply(NativeResultType a, NativeResultType b)
|
|
{
|
|
if constexpr (can_overflow && check_overflow)
|
|
{
|
|
NativeResultType res;
|
|
if (Op::template apply<NativeResultType>(a, b, res))
|
|
throw Exception(ErrorCodes::DECIMAL_OVERFLOW, "Decimal math overflow");
|
|
return res;
|
|
}
|
|
else
|
|
return Op::template apply<NativeResultType>(a, b);
|
|
}
|
|
|
|
template <bool scale_left, bool may_check_overflow = true>
|
|
static NO_SANITIZE_UNDEFINED NativeResultType applyScaled(NativeResultType a, NativeResultType b, NativeResultType scale)
|
|
{
|
|
static_assert(is_plus_minus_compare || is_multiply);
|
|
NativeResultType res;
|
|
|
|
if constexpr (check_overflow && may_check_overflow)
|
|
{
|
|
bool overflow = false;
|
|
|
|
if constexpr (scale_left)
|
|
overflow |= common::mulOverflow(a, scale, a);
|
|
else
|
|
overflow |= common::mulOverflow(b, scale, b);
|
|
|
|
if constexpr (can_overflow)
|
|
overflow |= Op::template apply<NativeResultType>(a, b, res);
|
|
else
|
|
res = Op::template apply<NativeResultType>(a, b);
|
|
|
|
if (overflow)
|
|
throw Exception(ErrorCodes::DECIMAL_OVERFLOW, "Decimal math overflow");
|
|
}
|
|
else
|
|
{
|
|
if constexpr (scale_left)
|
|
a *= scale;
|
|
else
|
|
b *= scale;
|
|
res = Op::template apply<NativeResultType>(a, b);
|
|
}
|
|
|
|
return res;
|
|
}
|
|
|
|
template <bool is_decimal_a>
|
|
static NO_SANITIZE_UNDEFINED NativeResultType applyScaledDiv(NativeResultType a, NativeResultType b, NativeResultType scale)
|
|
{
|
|
if constexpr (is_division)
|
|
{
|
|
if constexpr (check_overflow)
|
|
{
|
|
bool overflow = false;
|
|
if constexpr (!is_decimal_a)
|
|
overflow |= common::mulOverflow(scale, scale, scale);
|
|
overflow |= common::mulOverflow(a, scale, a);
|
|
if (overflow)
|
|
throw Exception(ErrorCodes::DECIMAL_OVERFLOW, "Decimal math overflow");
|
|
}
|
|
else
|
|
{
|
|
if constexpr (!is_decimal_a)
|
|
scale *= scale;
|
|
a *= scale;
|
|
}
|
|
|
|
return Op::template apply<NativeResultType>(a, b);
|
|
}
|
|
}
|
|
};
|
|
}
|
|
|
|
using namespace traits_;
|
|
using namespace impl_;
|
|
|
|
template <template <typename, typename> class Op, typename Name, bool valid_on_default_arguments = true, bool valid_on_float_arguments = true, bool division_by_nullable = false>
|
|
class FunctionBinaryArithmetic : public IFunction
|
|
{
|
|
static constexpr bool is_plus = IsOperation<Op>::plus;
|
|
static constexpr bool is_minus = IsOperation<Op>::minus;
|
|
static constexpr bool is_multiply = IsOperation<Op>::multiply;
|
|
static constexpr bool is_division = IsOperation<Op>::division;
|
|
static constexpr bool is_bit_hamming_distance = IsOperation<Op>::bit_hamming_distance;
|
|
|
|
ContextPtr context;
|
|
bool check_decimal_overflow = true;
|
|
|
|
static bool castType(const IDataType * type, auto && f)
|
|
{
|
|
using Types = TypeList<
|
|
DataTypeUInt8, DataTypeUInt16, DataTypeUInt32, DataTypeUInt64, DataTypeUInt128, DataTypeUInt256,
|
|
DataTypeInt8, DataTypeInt16, DataTypeInt32, DataTypeInt64, DataTypeInt128, DataTypeInt256,
|
|
DataTypeDecimal32, DataTypeDecimal64, DataTypeDecimal128, DataTypeDecimal256,
|
|
DataTypeDate, DataTypeDateTime,
|
|
DataTypeFixedString, DataTypeString,
|
|
DataTypeInterval>;
|
|
|
|
using Floats = TypeList<DataTypeFloat32, DataTypeFloat64>;
|
|
|
|
using ValidTypes = std::conditional_t<valid_on_float_arguments,
|
|
TypeListConcat<Types, Floats>,
|
|
Types>;
|
|
|
|
return castTypeToEither(ValidTypes{}, type, std::forward<decltype(f)>(f));
|
|
}
|
|
|
|
template <typename F>
|
|
static bool castBothTypes(const IDataType * left, const IDataType * right, F && f)
|
|
{
|
|
return castType(left, [&](const auto & left_)
|
|
{
|
|
return castType(right, [&](const auto & right_)
|
|
{
|
|
return f(left_, right_);
|
|
});
|
|
});
|
|
}
|
|
|
|
static FunctionOverloadResolverPtr
|
|
getFunctionForIntervalArithmetic(const DataTypePtr & type0, const DataTypePtr & type1, ContextPtr context)
|
|
{
|
|
bool first_is_date_or_datetime = isDateOrDate32(type0) || isDateTime(type0) || isDateTime64(type0);
|
|
bool second_is_date_or_datetime = isDateOrDate32(type1) || isDateTime(type1) || isDateTime64(type1);
|
|
|
|
/// Exactly one argument must be Date or DateTime
|
|
if (first_is_date_or_datetime == second_is_date_or_datetime)
|
|
return {};
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Interval.
|
|
/// We construct another function (example: addMonths) and call it.
|
|
|
|
if constexpr (!is_plus && !is_minus)
|
|
return {};
|
|
|
|
const DataTypePtr & type_time = first_is_date_or_datetime ? type0 : type1;
|
|
const DataTypePtr & type_interval = first_is_date_or_datetime ? type1 : type0;
|
|
|
|
bool interval_is_number = isNumber(type_interval);
|
|
|
|
const DataTypeInterval * interval_data_type = nullptr;
|
|
if (!interval_is_number)
|
|
{
|
|
interval_data_type = checkAndGetDataType<DataTypeInterval>(type_interval.get());
|
|
|
|
if (!interval_data_type)
|
|
return {};
|
|
}
|
|
|
|
if (second_is_date_or_datetime && is_minus)
|
|
throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT, "Wrong order of arguments for function {}: "
|
|
"argument of type Interval cannot be first", name);
|
|
|
|
std::string function_name;
|
|
if (interval_data_type)
|
|
{
|
|
function_name = fmt::format("{}{}s",
|
|
is_plus ? "add" : "subtract",
|
|
interval_data_type->getKind().toString());
|
|
}
|
|
else
|
|
{
|
|
if (isDateOrDate32(type_time))
|
|
function_name = is_plus ? "addDays" : "subtractDays";
|
|
else
|
|
function_name = is_plus ? "addSeconds" : "subtractSeconds";
|
|
}
|
|
|
|
return FunctionFactory::instance().get(function_name, context);
|
|
}
|
|
|
|
static FunctionOverloadResolverPtr
|
|
getFunctionForDateTupleOfIntervalsArithmetic(const DataTypePtr & type0, const DataTypePtr & type1, ContextPtr context)
|
|
{
|
|
bool first_is_date_or_datetime = isDateOrDate32(type0) || isDateTime(type0) || isDateTime64(type0);
|
|
bool second_is_date_or_datetime = isDateOrDate32(type1) || isDateTime(type1) || isDateTime64(type1);
|
|
|
|
/// Exactly one argument must be Date or DateTime
|
|
if (first_is_date_or_datetime == second_is_date_or_datetime)
|
|
return {};
|
|
|
|
if (!isTuple(type0) && !isTuple(type1))
|
|
return {};
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Tuple.
|
|
/// We construct another function and call it.
|
|
if constexpr (!is_plus && !is_minus)
|
|
return {};
|
|
|
|
if (isTuple(type0) && second_is_date_or_datetime && is_minus)
|
|
throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT, "Wrong order of arguments for function {}: "
|
|
"argument of Tuple type cannot be first", name);
|
|
|
|
std::string function_name;
|
|
if (is_plus)
|
|
{
|
|
function_name = "addTupleOfIntervals";
|
|
}
|
|
else
|
|
{
|
|
function_name = "subtractTupleOfIntervals";
|
|
}
|
|
|
|
return FunctionFactory::instance().get(function_name, context);
|
|
}
|
|
|
|
static FunctionOverloadResolverPtr
|
|
getFunctionForMergeIntervalsArithmetic(const DataTypePtr & type0, const DataTypePtr & type1, ContextPtr context)
|
|
{
|
|
/// Special case when the function is plus or minus, first argument is Interval or Tuple of Intervals
|
|
/// and the second argument is the Interval of a different kind.
|
|
/// We construct another function (example: addIntervals) and call it
|
|
|
|
if constexpr (!is_plus && !is_minus)
|
|
return {};
|
|
|
|
const auto * tuple_data_type_0 = checkAndGetDataType<DataTypeTuple>(type0.get());
|
|
const auto * interval_data_type_0 = checkAndGetDataType<DataTypeInterval>(type0.get());
|
|
const auto * interval_data_type_1 = checkAndGetDataType<DataTypeInterval>(type1.get());
|
|
|
|
if ((!tuple_data_type_0 && !interval_data_type_0) || !interval_data_type_1)
|
|
return {};
|
|
|
|
if (interval_data_type_0 && interval_data_type_0->equals(*interval_data_type_1))
|
|
return {};
|
|
|
|
if (tuple_data_type_0)
|
|
{
|
|
const auto & tuple_types = tuple_data_type_0->getElements();
|
|
for (const auto & type : tuple_types)
|
|
if (!isInterval(type))
|
|
return {};
|
|
}
|
|
|
|
std::string function_name;
|
|
if (is_plus)
|
|
{
|
|
function_name = "addInterval";
|
|
}
|
|
else
|
|
{
|
|
function_name = "subtractInterval";
|
|
}
|
|
|
|
return FunctionFactory::instance().get(function_name, context);
|
|
}
|
|
|
|
static FunctionOverloadResolverPtr
|
|
getFunctionForTupleArithmetic(const DataTypePtr & type0, const DataTypePtr & type1, ContextPtr context)
|
|
{
|
|
if (!isTuple(type0) || !isTuple(type1))
|
|
return {};
|
|
|
|
/// Special case when the function is plus, minus or multiply, both arguments are tuples.
|
|
/// We construct another function (example: tuplePlus) and call it.
|
|
|
|
if constexpr (!is_plus && !is_minus && !is_multiply)
|
|
return {};
|
|
|
|
std::string function_name;
|
|
if (is_plus)
|
|
{
|
|
function_name = "tuplePlus";
|
|
}
|
|
else if (is_minus)
|
|
{
|
|
function_name = "tupleMinus";
|
|
}
|
|
else
|
|
{
|
|
function_name = "dotProduct";
|
|
}
|
|
|
|
return FunctionFactory::instance().get(function_name, context);
|
|
}
|
|
|
|
static FunctionOverloadResolverPtr
|
|
getFunctionForTupleAndNumberArithmetic(const DataTypePtr & type0, const DataTypePtr & type1, ContextPtr context)
|
|
{
|
|
if (!(isTuple(type0) && isNumber(type1)) && !(isTuple(type1) && isNumber(type0)))
|
|
return {};
|
|
|
|
/// Special case when the function is multiply or divide, one of arguments is Tuple and another is Number.
|
|
/// We construct another function (example: tupleMultiplyByNumber) and call it.
|
|
|
|
if constexpr (!is_multiply && !is_division)
|
|
return {};
|
|
|
|
if (isNumber(type0) && is_division)
|
|
throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT, "Wrong order of arguments for function {}: "
|
|
"argument of numeric type cannot be first", name);
|
|
|
|
std::string function_name;
|
|
if (is_multiply)
|
|
{
|
|
function_name = "tupleMultiplyByNumber";
|
|
}
|
|
else
|
|
{
|
|
function_name = "tupleDivideByNumber";
|
|
}
|
|
|
|
return FunctionFactory::instance().get(function_name, context);
|
|
}
|
|
|
|
static bool isAggregateMultiply(const DataTypePtr & type0, const DataTypePtr & type1)
|
|
{
|
|
if constexpr (!is_multiply)
|
|
return false;
|
|
|
|
WhichDataType which0(type0);
|
|
WhichDataType which1(type1);
|
|
|
|
return (which0.isAggregateFunction() && which1.isNativeUInt())
|
|
|| (which0.isNativeUInt() && which1.isAggregateFunction());
|
|
}
|
|
|
|
static bool isAggregateAddition(const DataTypePtr & type0, const DataTypePtr & type1)
|
|
{
|
|
if constexpr (!is_plus)
|
|
return false;
|
|
|
|
WhichDataType which0(type0);
|
|
WhichDataType which1(type1);
|
|
|
|
return which0.isAggregateFunction() && which1.isAggregateFunction();
|
|
}
|
|
|
|
/// Multiply aggregation state by integer constant: by merging it with itself specified number of times.
|
|
ColumnPtr executeAggregateMultiply(const ColumnsWithTypeAndName & arguments, const DataTypePtr &, size_t input_rows_count) const
|
|
{
|
|
ColumnsWithTypeAndName new_arguments = arguments;
|
|
if (WhichDataType(new_arguments[1].type).isAggregateFunction())
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
if (!isColumnConst(*new_arguments[1].column))
|
|
throw Exception(ErrorCodes::ILLEGAL_COLUMN, "Illegal column {} of argument of aggregation state multiply. "
|
|
"Should be integer constant", new_arguments[1].column->getName());
|
|
|
|
const IColumn & agg_state_column = *new_arguments[0].column;
|
|
bool agg_state_is_const = isColumnConst(agg_state_column);
|
|
const ColumnAggregateFunction & column = typeid_cast<const ColumnAggregateFunction &>(
|
|
agg_state_is_const ? assert_cast<const ColumnConst &>(agg_state_column).getDataColumn() : agg_state_column);
|
|
|
|
AggregateFunctionPtr function = column.getAggregateFunction();
|
|
|
|
size_t size = agg_state_is_const ? 1 : input_rows_count;
|
|
|
|
auto column_to = ColumnAggregateFunction::create(function);
|
|
column_to->reserve(size);
|
|
|
|
auto column_from = ColumnAggregateFunction::create(function);
|
|
column_from->reserve(size);
|
|
|
|
for (size_t i = 0; i < size; ++i)
|
|
{
|
|
column_to->insertDefault();
|
|
column_from->insertFrom(column.getData()[i]);
|
|
}
|
|
|
|
auto & vec_to = column_to->getData();
|
|
auto & vec_from = column_from->getData();
|
|
|
|
UInt64 m = typeid_cast<const ColumnConst *>(new_arguments[1].column.get())->getValue<UInt64>();
|
|
|
|
// Since we merge the function states by ourselves, we have to have an
|
|
// Arena for this. Pass it to the resulting column so that the arena
|
|
// has a proper lifetime.
|
|
auto arena = std::make_shared<Arena>();
|
|
column_to->addArena(arena);
|
|
|
|
/// We use exponentiation by squaring algorithm to perform multiplying aggregate states by N in O(log(N)) operations
|
|
/// https://en.wikipedia.org/wiki/Exponentiation_by_squaring
|
|
while (m)
|
|
{
|
|
if (m % 2)
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
function->merge(vec_to[i], vec_from[i], arena.get());
|
|
--m;
|
|
}
|
|
else
|
|
{
|
|
for (size_t i = 0; i < size; ++i)
|
|
function->merge(vec_from[i], vec_from[i], arena.get());
|
|
m /= 2;
|
|
}
|
|
}
|
|
|
|
if (agg_state_is_const)
|
|
return ColumnConst::create(std::move(column_to), input_rows_count);
|
|
else
|
|
return column_to;
|
|
}
|
|
|
|
/// Merge two aggregation states together.
|
|
ColumnPtr executeAggregateAddition(const ColumnsWithTypeAndName & arguments, const DataTypePtr &, size_t input_rows_count) const
|
|
{
|
|
const IColumn & lhs_column = *arguments[0].column;
|
|
const IColumn & rhs_column = *arguments[1].column;
|
|
|
|
bool lhs_is_const = isColumnConst(lhs_column);
|
|
bool rhs_is_const = isColumnConst(rhs_column);
|
|
|
|
const ColumnAggregateFunction & lhs = typeid_cast<const ColumnAggregateFunction &>(
|
|
lhs_is_const ? assert_cast<const ColumnConst &>(lhs_column).getDataColumn() : lhs_column);
|
|
const ColumnAggregateFunction & rhs = typeid_cast<const ColumnAggregateFunction &>(
|
|
rhs_is_const ? assert_cast<const ColumnConst &>(rhs_column).getDataColumn() : rhs_column);
|
|
|
|
AggregateFunctionPtr function = lhs.getAggregateFunction();
|
|
|
|
size_t size = (lhs_is_const && rhs_is_const) ? 1 : input_rows_count;
|
|
|
|
auto column_to = ColumnAggregateFunction::create(function);
|
|
column_to->reserve(size);
|
|
|
|
for (size_t i = 0; i < size; ++i)
|
|
{
|
|
column_to->insertFrom(lhs.getData()[lhs_is_const ? 0 : i]);
|
|
column_to->insertMergeFrom(rhs.getData()[rhs_is_const ? 0 : i]);
|
|
}
|
|
|
|
if (lhs_is_const && rhs_is_const)
|
|
return ColumnConst::create(std::move(column_to), input_rows_count);
|
|
else
|
|
return column_to;
|
|
}
|
|
|
|
ColumnPtr executeDateTimeIntervalPlusMinus(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type,
|
|
size_t input_rows_count, const FunctionOverloadResolverPtr & function_builder) const
|
|
{
|
|
ColumnsWithTypeAndName new_arguments = arguments;
|
|
|
|
/// Interval argument must be second.
|
|
if (isDateOrDate32(arguments[1].type) || isDateTime(arguments[1].type) || isDateTime64(arguments[1].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
/// Change interval argument type to its representation
|
|
if (WhichDataType(new_arguments[1].type).isInterval())
|
|
new_arguments[1].type = std::make_shared<DataTypeNumber<DataTypeInterval::FieldType>>();
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->execute(new_arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
ColumnPtr executeDateTimeTupleOfIntervalsPlusMinus(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type,
|
|
size_t input_rows_count, const FunctionOverloadResolverPtr & function_builder) const
|
|
{
|
|
ColumnsWithTypeAndName new_arguments = arguments;
|
|
|
|
/// Tuple argument must be second.
|
|
if (isTuple(arguments[0].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
|
|
return function->execute(new_arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
ColumnPtr executeIntervalTupleOfIntervalsPlusMinus(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type,
|
|
size_t input_rows_count, const FunctionOverloadResolverPtr & function_builder) const
|
|
{
|
|
auto function = function_builder->build(arguments);
|
|
|
|
return function->execute(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
ColumnPtr executeTupleNumberOperator(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type,
|
|
size_t input_rows_count, const FunctionOverloadResolverPtr & function_builder) const
|
|
{
|
|
ColumnsWithTypeAndName new_arguments = arguments;
|
|
|
|
/// Number argument must be second.
|
|
if (isNumber(arguments[0].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
|
|
return function->execute(new_arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
template <typename T, typename ResultDataType>
|
|
static auto helperGetOrConvert(const auto & col_const, const auto & col)
|
|
{
|
|
using ResultType = typename ResultDataType::FieldType;
|
|
using NativeResultType = NativeType<ResultType>;
|
|
|
|
if constexpr (IsFloatingPoint<ResultDataType> && is_decimal<T>)
|
|
return DecimalUtils::convertTo<NativeResultType>(col_const->template getValue<T>(), col.getScale());
|
|
else if constexpr (is_decimal<T>)
|
|
return col_const->template getValue<T>().value;
|
|
else
|
|
return col_const->template getValue<T>();
|
|
}
|
|
|
|
template <OpCase op_case, bool left_decimal, bool right_decimal, typename OpImpl, typename OpImplCheck>
|
|
void helperInvokeEither(const auto& left, const auto& right, auto& vec_res, auto scale_a, auto scale_b, const NullMap * right_nullmap) const
|
|
{
|
|
if (check_decimal_overflow)
|
|
OpImplCheck::template process<op_case, left_decimal, right_decimal>(left, right, vec_res, scale_a, scale_b, right_nullmap);
|
|
else
|
|
OpImpl::template process<op_case, left_decimal, right_decimal>(left, right, vec_res, scale_a, scale_b, right_nullmap);
|
|
}
|
|
|
|
template <class LeftDataType, class RightDataType, class ResultDataType>
|
|
ColumnPtr executeNumericWithDecimal(
|
|
const auto & left, const auto & right,
|
|
const ColumnConst * const col_left_const, const ColumnConst * const col_right_const,
|
|
const auto * const col_left, const auto * const col_right,
|
|
size_t col_left_size, const NullMap * right_nullmap) const
|
|
{
|
|
using T0 = typename LeftDataType::FieldType;
|
|
using T1 = typename RightDataType::FieldType;
|
|
using ResultType = typename ResultDataType::FieldType;
|
|
|
|
using NativeResultType = NativeType<ResultType>;
|
|
using OpImpl = DecimalBinaryOperation<Op, ResultType, false>;
|
|
using OpImplCheck = DecimalBinaryOperation<Op, ResultType, true>;
|
|
|
|
using ColVecResult = ColumnVectorOrDecimal<ResultType>;
|
|
|
|
static constexpr const bool left_is_decimal = is_decimal<T0>;
|
|
static constexpr const bool right_is_decimal = is_decimal<T1>;
|
|
|
|
typename ColVecResult::MutablePtr col_res = nullptr;
|
|
|
|
const ResultDataType type = decimalResultType<is_multiply, is_division>(left, right);
|
|
|
|
const ResultType scale_a = [&]
|
|
{
|
|
if constexpr (IsDataTypeDecimal<RightDataType> && is_division)
|
|
return right.getScaleMultiplier(); // the division impl uses only the scale_a
|
|
else
|
|
{
|
|
if constexpr (is_multiply)
|
|
// the decimal impl uses scales, but if the result is decimal, both of the arguments are decimal,
|
|
// so they would multiply correctly, so we need to scale the result to the neutral element (1).
|
|
// The explicit type is needed as the int (in contrast with float) can't be implicitly converted
|
|
// to decimal.
|
|
return ResultType{1};
|
|
else
|
|
return type.scaleFactorFor(left, false);
|
|
}
|
|
}();
|
|
|
|
const ResultType scale_b = [&]
|
|
{
|
|
if constexpr (is_multiply)
|
|
return ResultType{1};
|
|
else
|
|
return type.scaleFactorFor(right, is_division);
|
|
}();
|
|
|
|
/// non-vector result
|
|
if (col_left_const && col_right_const)
|
|
{
|
|
const NativeResultType const_a = static_cast<NativeResultType>(
|
|
helperGetOrConvert<T0, ResultDataType>(col_left_const, left));
|
|
const NativeResultType const_b = static_cast<NativeResultType>(
|
|
helperGetOrConvert<T1, ResultDataType>(col_right_const, right));
|
|
|
|
ResultType res = {};
|
|
if (!right_nullmap || !(*right_nullmap)[0])
|
|
res = check_decimal_overflow
|
|
? OpImplCheck::template process<left_is_decimal, right_is_decimal>(const_a, const_b, scale_a, scale_b)
|
|
: OpImpl::template process<left_is_decimal, right_is_decimal>(const_a, const_b, scale_a, scale_b);
|
|
|
|
return ResultDataType(type.getPrecision(), type.getScale())
|
|
.createColumnConst(col_left_const->size(), toField(res, type.getScale()));
|
|
}
|
|
|
|
col_res = ColVecResult::create(0, type.getScale());
|
|
|
|
auto & vec_res = col_res->getData();
|
|
vec_res.resize(col_left_size);
|
|
|
|
if (col_left && col_right)
|
|
{
|
|
helperInvokeEither<OpCase::Vector, left_is_decimal, right_is_decimal, OpImpl, OpImplCheck>(
|
|
col_left->getData(), col_right->getData(), vec_res, scale_a, scale_b, right_nullmap);
|
|
}
|
|
else if (col_left_const && col_right)
|
|
{
|
|
const NativeResultType const_a = static_cast<NativeResultType>(
|
|
helperGetOrConvert<T0, ResultDataType>(col_left_const, left));
|
|
|
|
helperInvokeEither<OpCase::LeftConstant, left_is_decimal, right_is_decimal, OpImpl, OpImplCheck>(
|
|
const_a, col_right->getData(), vec_res, scale_a, scale_b, right_nullmap);
|
|
}
|
|
else if (col_left && col_right_const)
|
|
{
|
|
const NativeResultType const_b = static_cast<NativeResultType>(
|
|
helperGetOrConvert<T1, ResultDataType>(col_right_const, right));
|
|
|
|
helperInvokeEither<OpCase::RightConstant, left_is_decimal, right_is_decimal, OpImpl, OpImplCheck>(
|
|
col_left->getData(), const_b, vec_res, scale_a, scale_b, right_nullmap);
|
|
}
|
|
else
|
|
return nullptr;
|
|
|
|
return col_res;
|
|
}
|
|
|
|
public:
|
|
static constexpr auto name = Name::name;
|
|
static FunctionPtr create(ContextPtr context) { return std::make_shared<FunctionBinaryArithmetic>(context); }
|
|
|
|
explicit FunctionBinaryArithmetic(ContextPtr context_)
|
|
: context(context_),
|
|
check_decimal_overflow(decimalCheckArithmeticOverflow(context))
|
|
{}
|
|
|
|
String getName() const override { return name; }
|
|
|
|
size_t getNumberOfArguments() const override { return 2; }
|
|
|
|
bool useDefaultImplementationForNulls() const override
|
|
{
|
|
/// We shouldn't use default implementation for nulls for the case when operation is divide,
|
|
/// intDiv or modulo and denominator is Nullable(Something), because it may cause division
|
|
/// by zero error (when value is Null we store default value 0 in nested column).
|
|
return !division_by_nullable;
|
|
}
|
|
|
|
bool isSuitableForShortCircuitArgumentsExecution(const DataTypesWithConstInfo & arguments) const override
|
|
{
|
|
return ((IsOperation<Op>::div_int || IsOperation<Op>::modulo || IsOperation<Op>::positive_modulo) && !arguments[1].is_const)
|
|
|| (IsOperation<Op>::div_floating
|
|
&& (isDecimalOrNullableDecimal(arguments[0].type) || isDecimalOrNullableDecimal(arguments[1].type)));
|
|
}
|
|
|
|
DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override
|
|
{
|
|
return getReturnTypeImplStatic(arguments, context);
|
|
}
|
|
|
|
static DataTypePtr getReturnTypeImplStatic(const DataTypes & arguments, ContextPtr context)
|
|
{
|
|
/// Special case when multiply aggregate function state
|
|
if (isAggregateMultiply(arguments[0], arguments[1]))
|
|
{
|
|
if (WhichDataType(arguments[0]).isAggregateFunction())
|
|
return arguments[0];
|
|
return arguments[1];
|
|
}
|
|
|
|
/// Special case - addition of two aggregate functions states
|
|
if (isAggregateAddition(arguments[0], arguments[1]))
|
|
{
|
|
if (!arguments[0]->equals(*arguments[1]))
|
|
throw Exception(ErrorCodes::CANNOT_ADD_DIFFERENT_AGGREGATE_STATES,
|
|
"Cannot add aggregate states of different functions: {} and {}",
|
|
arguments[0]->getName(), arguments[1]->getName());
|
|
|
|
return arguments[0];
|
|
}
|
|
|
|
/// Special case - one or both arguments are IPv4
|
|
if (isIPv4(arguments[0]) || isIPv4(arguments[1]))
|
|
{
|
|
DataTypes new_arguments {
|
|
isIPv4(arguments[0]) ? std::make_shared<DataTypeUInt32>() : arguments[0],
|
|
isIPv4(arguments[1]) ? std::make_shared<DataTypeUInt32>() : arguments[1],
|
|
};
|
|
|
|
return getReturnTypeImplStatic(new_arguments, context);
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Interval.
|
|
if (auto function_builder = getFunctionForIntervalArithmetic(arguments[0], arguments[1], context))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments(2);
|
|
|
|
for (size_t i = 0; i < 2; ++i)
|
|
new_arguments[i].type = arguments[i];
|
|
|
|
/// Interval argument must be second.
|
|
if (isDateOrDate32(new_arguments[1].type) || isDateTime(new_arguments[1].type) || isDateTime64(new_arguments[1].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
/// Change interval argument to its representation
|
|
new_arguments[1].type = std::make_shared<DataTypeNumber<DataTypeInterval::FieldType>>();
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->getResultType();
|
|
}
|
|
|
|
/// Special case when the function is plus, minus or multiply, both arguments are tuples.
|
|
if (auto function_builder = getFunctionForTupleArithmetic(arguments[0], arguments[1], context))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments(2);
|
|
|
|
for (size_t i = 0; i < 2; ++i)
|
|
new_arguments[i].type = arguments[i];
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->getResultType();
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Tuple.
|
|
if (auto function_builder = getFunctionForDateTupleOfIntervalsArithmetic(arguments[0], arguments[1], context))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments(2);
|
|
|
|
for (size_t i = 0; i < 2; ++i)
|
|
new_arguments[i].type = arguments[i];
|
|
|
|
/// Tuple argument must be second.
|
|
if (isTuple(new_arguments[0].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->getResultType();
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Interval/Tuple of Intervals and another is Interval.
|
|
if (auto function_builder = getFunctionForMergeIntervalsArithmetic(arguments[0], arguments[1], context))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments(2);
|
|
|
|
for (size_t i = 0; i < 2; ++i)
|
|
new_arguments[i].type = arguments[i];
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->getResultType();
|
|
}
|
|
|
|
/// Special case when the function is multiply or divide, one of arguments is Tuple and another is Number.
|
|
if (auto function_builder = getFunctionForTupleAndNumberArithmetic(arguments[0], arguments[1], context))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments(2);
|
|
|
|
for (size_t i = 0; i < 2; ++i)
|
|
new_arguments[i].type = arguments[i];
|
|
|
|
/// Number argument must be second.
|
|
if (isNumber(new_arguments[0].type))
|
|
std::swap(new_arguments[0], new_arguments[1]);
|
|
|
|
auto function = function_builder->build(new_arguments);
|
|
return function->getResultType();
|
|
}
|
|
|
|
DataTypePtr type_res;
|
|
|
|
const bool valid = castBothTypes(arguments[0].get(), arguments[1].get(), [&](const auto & left, const auto & right)
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
|
|
if constexpr ((std::is_same_v<DataTypeFixedString, LeftDataType> || std::is_same_v<DataTypeString, LeftDataType>) ||
|
|
(std::is_same_v<DataTypeFixedString, RightDataType> || std::is_same_v<DataTypeString, RightDataType>))
|
|
{
|
|
if constexpr (std::is_same_v<DataTypeFixedString, LeftDataType> &&
|
|
std::is_same_v<DataTypeFixedString, RightDataType>)
|
|
{
|
|
if constexpr (!Op<DataTypeFixedString, DataTypeFixedString>::allow_fixed_string)
|
|
return false;
|
|
else
|
|
{
|
|
if (left.getN() == right.getN())
|
|
{
|
|
if constexpr (is_bit_hamming_distance)
|
|
type_res = std::make_shared<DataTypeUInt16>();
|
|
else
|
|
type_res = std::make_shared<LeftDataType>(left.getN());
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
if constexpr (
|
|
is_bit_hamming_distance
|
|
&& std::is_same_v<DataTypeString, LeftDataType> && std::is_same_v<DataTypeString, RightDataType>)
|
|
type_res = std::make_shared<DataTypeUInt64>();
|
|
else if constexpr (!Op<LeftDataType, RightDataType>::allow_string_integer)
|
|
return false;
|
|
else if constexpr (!IsIntegral<RightDataType>)
|
|
return false;
|
|
else if constexpr (std::is_same_v<DataTypeFixedString, LeftDataType>)
|
|
type_res = std::make_shared<LeftDataType>(left.getN());
|
|
else
|
|
type_res = std::make_shared<DataTypeString>();
|
|
return true;
|
|
}
|
|
else if constexpr (std::is_same_v<LeftDataType, DataTypeInterval> || std::is_same_v<RightDataType, DataTypeInterval>)
|
|
{
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeInterval> &&
|
|
std::is_same_v<RightDataType, DataTypeInterval>)
|
|
{
|
|
if constexpr (is_plus || is_minus)
|
|
{
|
|
if (left.getKind() == right.getKind())
|
|
{
|
|
type_res = std::make_shared<LeftDataType>(left.getKind());
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
using ResultDataType = typename BinaryOperationTraits<Op, LeftDataType, RightDataType>::ResultDataType;
|
|
|
|
if constexpr (!std::is_same_v<ResultDataType, InvalidType>)
|
|
{
|
|
if constexpr (IsDataTypeDecimal<LeftDataType> && IsDataTypeDecimal<RightDataType>)
|
|
{
|
|
if constexpr (is_division)
|
|
{
|
|
if (context->getSettingsRef().decimal_check_overflow)
|
|
{
|
|
/// Check overflow by using operands scale (based on big decimal division implementation details):
|
|
/// big decimal arithmetic is based on big integers, decimal operands are converted to big integers
|
|
/// i.e. int_operand = decimal_operand*10^scale
|
|
/// For division, left operand will be scaled by right operand scale also to do big integer division,
|
|
/// BigInt result = left*10^(left_scale + right_scale) / right * 10^right_scale
|
|
/// So, we can check upfront possible overflow just by checking max scale used for left operand
|
|
/// Note: it doesn't detect all possible overflow during big decimal division
|
|
if (left.getScale() + right.getScale() > ResultDataType::maxPrecision())
|
|
throw Exception(ErrorCodes::DECIMAL_OVERFLOW, "Overflow during decimal division");
|
|
}
|
|
}
|
|
ResultDataType result_type = decimalResultType<is_multiply, is_division>(left, right);
|
|
type_res = std::make_shared<ResultDataType>(result_type.getPrecision(), result_type.getScale());
|
|
}
|
|
else if constexpr ((IsDataTypeDecimal<LeftDataType> && IsFloatingPoint<RightDataType>) ||
|
|
(IsDataTypeDecimal<RightDataType> && IsFloatingPoint<LeftDataType>))
|
|
type_res = std::make_shared<DataTypeFloat64>();
|
|
else if constexpr (IsDataTypeDecimal<LeftDataType>)
|
|
type_res = std::make_shared<LeftDataType>(left.getPrecision(), left.getScale());
|
|
else if constexpr (IsDataTypeDecimal<RightDataType>)
|
|
type_res = std::make_shared<RightDataType>(right.getPrecision(), right.getScale());
|
|
else if constexpr (std::is_same_v<ResultDataType, DataTypeDateTime>)
|
|
{
|
|
// Special case for DateTime: binary OPS should reuse timezone
|
|
// of DateTime argument as timezeone of result type.
|
|
// NOTE: binary plus/minus are not allowed on DateTime64, and we are not handling it here.
|
|
|
|
const TimezoneMixin * tz = nullptr;
|
|
if constexpr (std::is_same_v<RightDataType, DataTypeDateTime>)
|
|
tz = &right;
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeDateTime>)
|
|
tz = &left;
|
|
type_res = std::make_shared<ResultDataType>(*tz);
|
|
}
|
|
else
|
|
type_res = std::make_shared<ResultDataType>();
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
});
|
|
|
|
if (valid)
|
|
return type_res;
|
|
|
|
throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT, "Illegal types {} and {} of arguments of function {}",
|
|
arguments[0]->getName(), arguments[1]->getName(), String(name));
|
|
}
|
|
|
|
ColumnPtr executeFixedString(const ColumnsWithTypeAndName & arguments) const
|
|
{
|
|
using OpImpl = FixedStringOperationImpl<Op<UInt8, UInt8>>;
|
|
using OpReduceImpl = FixedStringReduceOperationImpl<Op<UInt8, UInt8>>;
|
|
|
|
const auto * const col_left_raw = arguments[0].column.get();
|
|
const auto * const col_right_raw = arguments[1].column.get();
|
|
|
|
if (const auto * col_left_const = checkAndGetColumnConst<ColumnFixedString>(col_left_raw))
|
|
{
|
|
if (const auto * col_right_const = checkAndGetColumnConst<ColumnFixedString>(col_right_raw))
|
|
{
|
|
const auto * col_left = checkAndGetColumn<ColumnFixedString>(col_left_const->getDataColumn());
|
|
const auto * col_right = checkAndGetColumn<ColumnFixedString>(col_right_const->getDataColumn());
|
|
|
|
if (col_left->getN() != col_right->getN())
|
|
return nullptr;
|
|
|
|
if constexpr (is_bit_hamming_distance)
|
|
{
|
|
auto col_res = ColumnUInt16::create();
|
|
auto & data = col_res->getData();
|
|
data.resize_fill(col_left->size());
|
|
|
|
OpReduceImpl::template process<OpCase::Vector>(
|
|
col_left->getChars().data(), col_right->getChars().data(), data.data(), data.size(), col_left->getN());
|
|
|
|
return ColumnConst::create(std::move(col_res), col_left_raw->size());
|
|
}
|
|
else
|
|
{
|
|
auto col_res = ColumnFixedString::create(col_left->getN());
|
|
auto & out_chars = col_res->getChars();
|
|
|
|
out_chars.resize(col_left->getN());
|
|
|
|
OpImpl::template process<OpCase::Vector>(
|
|
col_left->getChars().data(), col_right->getChars().data(), out_chars.data(), out_chars.size(), {});
|
|
|
|
return ColumnConst::create(std::move(col_res), col_left_raw->size());
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
const bool is_left_column_const = checkAndGetColumnConst<ColumnFixedString>(col_left_raw) != nullptr;
|
|
const bool is_right_column_const = checkAndGetColumnConst<ColumnFixedString>(col_right_raw) != nullptr;
|
|
|
|
const auto * col_left = is_left_column_const
|
|
? checkAndGetColumn<ColumnFixedString>(
|
|
checkAndGetColumnConst<ColumnFixedString>(col_left_raw)->getDataColumn())
|
|
: checkAndGetColumn<ColumnFixedString>(col_left_raw);
|
|
const auto * col_right = is_right_column_const
|
|
? checkAndGetColumn<ColumnFixedString>(
|
|
checkAndGetColumnConst<ColumnFixedString>(col_right_raw)->getDataColumn())
|
|
: checkAndGetColumn<ColumnFixedString>(col_right_raw);
|
|
|
|
if (col_left && col_right)
|
|
{
|
|
if (col_left->getN() != col_right->getN())
|
|
return nullptr;
|
|
|
|
if constexpr (is_bit_hamming_distance)
|
|
{
|
|
auto col_res = ColumnUInt16::create();
|
|
auto & data = col_res->getData();
|
|
data.resize_fill(is_right_column_const ? col_left->size() : col_right->size());
|
|
|
|
if (!is_left_column_const && !is_right_column_const)
|
|
{
|
|
OpReduceImpl::template process<OpCase::Vector>(
|
|
col_left->getChars().data(), col_right->getChars().data(), data.data(), data.size(), col_left->getN());
|
|
}
|
|
else if (is_left_column_const)
|
|
{
|
|
OpReduceImpl::template process<OpCase::LeftConstant>(
|
|
col_left->getChars().data(), col_right->getChars().data(), data.data(), data.size(), col_left->getN());
|
|
}
|
|
else
|
|
{
|
|
OpReduceImpl::template process<OpCase::RightConstant>(
|
|
col_left->getChars().data(), col_right->getChars().data(), data.data(), data.size(), col_left->getN());
|
|
}
|
|
|
|
return col_res;
|
|
}
|
|
else
|
|
{
|
|
auto col_res = ColumnFixedString::create(col_left->getN());
|
|
auto & out_chars = col_res->getChars();
|
|
out_chars.resize((is_right_column_const ? col_left->size() : col_right->size()) * col_left->getN());
|
|
|
|
if (!is_left_column_const && !is_right_column_const)
|
|
{
|
|
OpImpl::template process<OpCase::Vector>(
|
|
col_left->getChars().data(), col_right->getChars().data(), out_chars.data(), out_chars.size(), {});
|
|
}
|
|
else if (is_left_column_const)
|
|
{
|
|
OpImpl::template process<OpCase::LeftConstant>(
|
|
col_left->getChars().data(), col_right->getChars().data(), out_chars.data(), out_chars.size(), col_left->getN());
|
|
}
|
|
else
|
|
{
|
|
OpImpl::template process<OpCase::RightConstant>(
|
|
col_left->getChars().data(), col_right->getChars().data(), out_chars.data(), out_chars.size(), col_left->getN());
|
|
}
|
|
|
|
return col_res;
|
|
}
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
/// Only used for bitHammingDistance
|
|
ColumnPtr executeString(const ColumnsWithTypeAndName & arguments) const
|
|
{
|
|
using OpImpl = StringReduceOperationImpl<Op<UInt8, UInt8>>;
|
|
|
|
const auto * const col_left_raw = arguments[0].column.get();
|
|
const auto * const col_right_raw = arguments[1].column.get();
|
|
|
|
if (const auto * col_left_const = checkAndGetColumnConst<ColumnString>(col_left_raw))
|
|
{
|
|
if (const auto * col_right_const = checkAndGetColumnConst<ColumnString>(col_right_raw))
|
|
{
|
|
const auto * col_left = checkAndGetColumn<ColumnString>(col_left_const->getDataColumn());
|
|
const auto * col_right = checkAndGetColumn<ColumnString>(col_right_const->getDataColumn());
|
|
|
|
std::string_view a = col_left->getDataAt(0).toView();
|
|
std::string_view b = col_right->getDataAt(0).toView();
|
|
|
|
auto res = OpImpl::constConst(a, b);
|
|
|
|
return DataTypeUInt64{}.createColumnConst(1, res);
|
|
}
|
|
}
|
|
|
|
const bool is_left_column_const = checkAndGetColumnConst<ColumnString>(col_left_raw) != nullptr;
|
|
const bool is_right_column_const = checkAndGetColumnConst<ColumnString>(col_right_raw) != nullptr;
|
|
|
|
const auto * col_left = is_left_column_const
|
|
? checkAndGetColumn<ColumnString>(checkAndGetColumnConst<ColumnString>(col_left_raw)->getDataColumn())
|
|
: checkAndGetColumn<ColumnString>(col_left_raw);
|
|
const auto * col_right = is_right_column_const
|
|
? checkAndGetColumn<ColumnString>(checkAndGetColumnConst<ColumnString>(col_right_raw)->getDataColumn())
|
|
: checkAndGetColumn<ColumnString>(col_right_raw);
|
|
|
|
if (col_left && col_right)
|
|
{
|
|
auto col_res = ColumnUInt64::create();
|
|
auto & data = col_res->getData();
|
|
data.resize(is_right_column_const ? col_left->size() : col_right->size());
|
|
|
|
if (!is_left_column_const && !is_right_column_const)
|
|
{
|
|
OpImpl::vectorVector(
|
|
col_left->getChars(), col_left->getOffsets(), col_right->getChars(), col_right->getOffsets(), data);
|
|
}
|
|
else if (is_left_column_const)
|
|
{
|
|
std::string_view str_view = col_left->getDataAt(0).toView();
|
|
OpImpl::vectorConstant(col_right->getChars(), col_right->getOffsets(), str_view, data);
|
|
}
|
|
else
|
|
{
|
|
std::string_view str_view = col_right->getDataAt(0).toView();
|
|
OpImpl::vectorConstant(col_left->getChars(), col_left->getOffsets(), str_view, data);
|
|
}
|
|
|
|
return col_res;
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
template <typename LeftColumnType, typename A, typename B>
|
|
ColumnPtr executeStringInteger(const ColumnsWithTypeAndName & arguments, const A & left, const B & right) const
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
|
|
const auto * const col_left_raw = arguments[0].column.get();
|
|
const auto * const col_right_raw = arguments[1].column.get();
|
|
using T1 = typename RightDataType::FieldType;
|
|
|
|
using ColVecT1 = ColumnVector<T1>;
|
|
const ColVecT1 * const col_right = checkAndGetColumn<ColVecT1>(col_right_raw);
|
|
const ColumnConst * const col_right_const = checkAndGetColumnConst<ColVecT1>(col_right_raw);
|
|
|
|
using OpImpl = StringIntegerOperationImpl<T1, Op<LeftDataType, T1>>;
|
|
|
|
const ColumnConst * const col_left_const = checkAndGetColumnConst<LeftColumnType>(col_left_raw);
|
|
|
|
const auto * col_left = col_left_const ? checkAndGetColumn<LeftColumnType>(col_left_const->getDataColumn())
|
|
: checkAndGetColumn<LeftColumnType>(col_left_raw);
|
|
|
|
if (!col_left)
|
|
return nullptr;
|
|
|
|
const typename LeftColumnType::Chars & in_vec = col_left->getChars();
|
|
|
|
typename LeftColumnType::MutablePtr col_res;
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeFixedString>)
|
|
col_res = LeftColumnType::create(col_left->getN());
|
|
else
|
|
col_res = LeftColumnType::create();
|
|
|
|
typename LeftColumnType::Chars & out_vec = col_res->getChars();
|
|
|
|
if (col_left_const && col_right_const)
|
|
{
|
|
const T1 value = col_right_const->template getValue<T1>();
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeFixedString>)
|
|
{
|
|
OpImpl::template processFixedString<OpCase::Vector>(in_vec.data(), col_left->getN(), &value, out_vec, 1);
|
|
}
|
|
else
|
|
{
|
|
ColumnString::Offsets & out_offsets = col_res->getOffsets();
|
|
OpImpl::template processString<OpCase::Vector>(in_vec.data(), col_left->getOffsets().data(), &value, out_vec, out_offsets, 1);
|
|
}
|
|
|
|
return ColumnConst::create(std::move(col_res), col_left_const->size());
|
|
}
|
|
else if (!col_left_const && !col_right_const && col_right)
|
|
{
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeFixedString>)
|
|
{
|
|
OpImpl::template processFixedString<OpCase::Vector>(in_vec.data(), col_left->getN(), col_right->getData().data(), out_vec, col_left->size());
|
|
}
|
|
else
|
|
{
|
|
ColumnString::Offsets & out_offsets = col_res->getOffsets();
|
|
out_offsets.reserve(col_left->size());
|
|
OpImpl::template processString<OpCase::Vector>(
|
|
in_vec.data(), col_left->getOffsets().data(), col_right->getData().data(), out_vec, out_offsets, col_left->size());
|
|
}
|
|
}
|
|
else if (col_left_const && col_right)
|
|
{
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeFixedString>)
|
|
{
|
|
OpImpl::template processFixedString<OpCase::LeftConstant>(
|
|
in_vec.data(), col_left->getN(), col_right->getData().data(), out_vec, col_right->size());
|
|
}
|
|
else
|
|
{
|
|
ColumnString::Offsets & out_offsets = col_res->getOffsets();
|
|
out_offsets.reserve(col_right->size());
|
|
OpImpl::template processString<OpCase::LeftConstant>(
|
|
in_vec.data(), col_left->getOffsets().data(), col_right->getData().data(), out_vec, out_offsets, col_right->size());
|
|
}
|
|
}
|
|
else if (col_right_const)
|
|
{
|
|
const T1 value = col_right_const->template getValue<T1>();
|
|
if constexpr (std::is_same_v<LeftDataType, DataTypeFixedString>)
|
|
{
|
|
OpImpl::template processFixedString<OpCase::RightConstant>(in_vec.data(), col_left->getN(), &value, out_vec, col_left->size());
|
|
}
|
|
else
|
|
{
|
|
ColumnString::Offsets & out_offsets = col_res->getOffsets();
|
|
out_offsets.reserve(col_left->size());
|
|
OpImpl::template processString<OpCase::RightConstant>(
|
|
in_vec.data(), col_left->getOffsets().data(), &value, out_vec, out_offsets, col_left->size());
|
|
}
|
|
}
|
|
else
|
|
return nullptr;
|
|
|
|
return col_res;
|
|
}
|
|
|
|
template <typename A, typename B>
|
|
ColumnPtr executeNumeric(const ColumnsWithTypeAndName & arguments, const A & left, const B & right, const NullMap * right_nullmap) const
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
using ResultDataType = typename BinaryOperationTraits<Op, LeftDataType, RightDataType>::ResultDataType;
|
|
|
|
if constexpr (std::is_same_v<ResultDataType, InvalidType>)
|
|
return nullptr;
|
|
else // we can't avoid the else because otherwise the compiler may assume the ResultDataType may be Invalid
|
|
// and that would produce the compile error.
|
|
{
|
|
constexpr bool decimal_with_float = (IsDataTypeDecimal<LeftDataType> && IsFloatingPoint<RightDataType>)
|
|
|| (IsFloatingPoint<LeftDataType> && IsDataTypeDecimal<RightDataType>);
|
|
|
|
using T0 = std::conditional_t<decimal_with_float, Float64, typename LeftDataType::FieldType>;
|
|
using T1 = std::conditional_t<decimal_with_float, Float64, typename RightDataType::FieldType>;
|
|
using ResultType = typename ResultDataType::FieldType;
|
|
using ColVecT0 = ColumnVectorOrDecimal<T0>;
|
|
using ColVecT1 = ColumnVectorOrDecimal<T1>;
|
|
using ColVecResult = ColumnVectorOrDecimal<ResultType>;
|
|
|
|
ColumnPtr left_col = nullptr;
|
|
ColumnPtr right_col = nullptr;
|
|
|
|
/// When Decimal op Float32/64, convert both of them into Float64
|
|
if constexpr (decimal_with_float)
|
|
{
|
|
const auto converted_type = std::make_shared<DataTypeFloat64>();
|
|
left_col = castColumn(arguments[0], converted_type);
|
|
right_col = castColumn(arguments[1], converted_type);
|
|
}
|
|
else
|
|
{
|
|
left_col = arguments[0].column;
|
|
right_col = arguments[1].column;
|
|
}
|
|
const auto * const col_left_raw = left_col.get();
|
|
const auto * const col_right_raw = right_col.get();
|
|
|
|
const size_t col_left_size = col_left_raw->size();
|
|
|
|
const ColumnConst * const col_left_const = checkAndGetColumnConst<ColVecT0>(col_left_raw);
|
|
const ColumnConst * const col_right_const = checkAndGetColumnConst<ColVecT1>(col_right_raw);
|
|
|
|
const ColVecT0 * const col_left = checkAndGetColumn<ColVecT0>(col_left_raw);
|
|
const ColVecT1 * const col_right = checkAndGetColumn<ColVecT1>(col_right_raw);
|
|
|
|
if constexpr (IsDataTypeDecimal<ResultDataType>)
|
|
{
|
|
return executeNumericWithDecimal<LeftDataType, RightDataType, ResultDataType>(
|
|
left, right,
|
|
col_left_const, col_right_const,
|
|
col_left, col_right,
|
|
col_left_size,
|
|
right_nullmap);
|
|
}
|
|
else // can't avoid else and another indentation level, otherwise the compiler would try to instantiate
|
|
// ColVecResult for Decimals which would lead to a compile error.
|
|
{
|
|
using OpImpl = BinaryOperationImpl<T0, T1, Op<T0, T1>, ResultType>;
|
|
|
|
/// non-vector result
|
|
if (col_left_const && col_right_const)
|
|
{
|
|
const auto res = right_nullmap && (*right_nullmap)[0] ? ResultType() : OpImpl::process(
|
|
col_left_const->template getValue<T0>(),
|
|
col_right_const->template getValue<T1>());
|
|
|
|
return ResultDataType().createColumnConst(col_left_const->size(), toField(res));
|
|
}
|
|
|
|
typename ColVecResult::MutablePtr col_res = ColVecResult::create();
|
|
|
|
auto & vec_res = col_res->getData();
|
|
vec_res.resize(col_left_size);
|
|
|
|
if (col_left && col_right)
|
|
{
|
|
OpImpl::template process<OpCase::Vector>(
|
|
col_left->getData().data(),
|
|
col_right->getData().data(),
|
|
vec_res.data(),
|
|
vec_res.size(),
|
|
right_nullmap);
|
|
}
|
|
else if (col_left_const && col_right)
|
|
{
|
|
const T0 value = col_left_const->template getValue<T0>();
|
|
|
|
OpImpl::template process<OpCase::LeftConstant>(
|
|
&value,
|
|
col_right->getData().data(),
|
|
vec_res.data(),
|
|
vec_res.size(),
|
|
right_nullmap);
|
|
}
|
|
else if (col_left && col_right_const)
|
|
{
|
|
const T1 value = col_right_const->template getValue<T1>();
|
|
|
|
OpImpl::template process<OpCase::RightConstant>(
|
|
col_left->getData().data(), &value, vec_res.data(), vec_res.size(), right_nullmap);
|
|
}
|
|
else
|
|
return nullptr;
|
|
|
|
return col_res;
|
|
}
|
|
}
|
|
}
|
|
|
|
ColumnPtr executeImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type, size_t input_rows_count) const override
|
|
{
|
|
/// Special case when multiply aggregate function state
|
|
if (isAggregateMultiply(arguments[0].type, arguments[1].type))
|
|
{
|
|
return executeAggregateMultiply(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
/// Special case - addition of two aggregate functions states
|
|
if (isAggregateAddition(arguments[0].type, arguments[1].type))
|
|
{
|
|
return executeAggregateAddition(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
/// Special case - one or both arguments are IPv4
|
|
if (isIPv4(arguments[0].type) || isIPv4(arguments[1].type))
|
|
{
|
|
ColumnsWithTypeAndName new_arguments {
|
|
{
|
|
isIPv4(arguments[0].type) ? castColumn(arguments[0], std::make_shared<DataTypeUInt32>()) : arguments[0].column,
|
|
isIPv4(arguments[0].type) ? std::make_shared<DataTypeUInt32>() : arguments[0].type,
|
|
arguments[0].name,
|
|
},
|
|
{
|
|
isIPv4(arguments[1].type) ? castColumn(arguments[1], std::make_shared<DataTypeUInt32>()) : arguments[1].column,
|
|
isIPv4(arguments[1].type) ? std::make_shared<DataTypeUInt32>() : arguments[1].type,
|
|
arguments[1].name
|
|
}
|
|
};
|
|
|
|
return executeImpl(new_arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Interval.
|
|
if (auto function_builder = getFunctionForIntervalArithmetic(arguments[0].type, arguments[1].type, context))
|
|
{
|
|
return executeDateTimeIntervalPlusMinus(arguments, result_type, input_rows_count, function_builder);
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Date/DateTime and another is Tuple.
|
|
if (auto function_builder = getFunctionForDateTupleOfIntervalsArithmetic(arguments[0].type, arguments[1].type, context))
|
|
{
|
|
return executeDateTimeTupleOfIntervalsPlusMinus(arguments, result_type, input_rows_count, function_builder);
|
|
}
|
|
|
|
/// Special case when the function is plus or minus, one of arguments is Interval/Tuple of Intervals and another is Interval.
|
|
if (auto function_builder = getFunctionForMergeIntervalsArithmetic(arguments[0].type, arguments[1].type, context))
|
|
{
|
|
return executeIntervalTupleOfIntervalsPlusMinus(arguments, result_type, input_rows_count, function_builder);
|
|
}
|
|
|
|
/// Special case when the function is plus, minus or multiply, both arguments are tuples.
|
|
if (auto function_builder = getFunctionForTupleArithmetic(arguments[0].type, arguments[1].type, context))
|
|
{
|
|
return function_builder->build(arguments)->execute(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
/// Special case when the function is multiply or divide, one of arguments is Tuple and another is Number.
|
|
if (auto function_builder = getFunctionForTupleAndNumberArithmetic(arguments[0].type, arguments[1].type, context))
|
|
{
|
|
return executeTupleNumberOperator(arguments, result_type, input_rows_count, function_builder);
|
|
}
|
|
|
|
return executeImpl2(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
ColumnPtr executeImpl2(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type, size_t input_rows_count, const NullMap * right_nullmap = nullptr) const
|
|
{
|
|
const auto & left_argument = arguments[0];
|
|
const auto & right_argument = arguments[1];
|
|
|
|
/// Process special case when operation is divide, intDiv or modulo and denominator
|
|
/// is Nullable(Something) to prevent division by zero error.
|
|
if (division_by_nullable && !right_nullmap)
|
|
{
|
|
assert(right_argument.type->isNullable());
|
|
|
|
bool is_const = checkColumnConst<ColumnNullable>(right_argument.column.get());
|
|
const ColumnNullable * nullable_column = is_const ? checkAndGetColumnConstData<ColumnNullable>(right_argument.column.get())
|
|
: checkAndGetColumn<ColumnNullable>(*right_argument.column);
|
|
|
|
const auto & null_bytemap = nullable_column->getNullMapData();
|
|
auto res = executeImpl2(createBlockWithNestedColumns(arguments), removeNullable(result_type), input_rows_count, &null_bytemap);
|
|
return wrapInNullable(res, arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
const auto * const left_generic = left_argument.type.get();
|
|
const auto * const right_generic = right_argument.type.get();
|
|
ColumnPtr res;
|
|
|
|
const bool valid = castBothTypes(left_generic, right_generic, [&](const auto & left, const auto & right)
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
|
|
if constexpr ((std::is_same_v<DataTypeFixedString, LeftDataType> || std::is_same_v<DataTypeString, LeftDataType>) ||
|
|
(std::is_same_v<DataTypeFixedString, RightDataType> || std::is_same_v<DataTypeString, RightDataType>))
|
|
{
|
|
if constexpr (std::is_same_v<DataTypeFixedString, LeftDataType> &&
|
|
std::is_same_v<DataTypeFixedString, RightDataType>)
|
|
{
|
|
if constexpr (!Op<DataTypeFixedString, DataTypeFixedString>::allow_fixed_string)
|
|
return false;
|
|
else
|
|
return (res = executeFixedString(arguments)) != nullptr;
|
|
}
|
|
|
|
if constexpr (
|
|
is_bit_hamming_distance
|
|
&& std::is_same_v<DataTypeString, LeftDataType> && std::is_same_v<DataTypeString, RightDataType>)
|
|
return (res = executeString(arguments)) != nullptr;
|
|
else if constexpr (!Op<LeftDataType, RightDataType>::allow_string_integer)
|
|
return false;
|
|
else if constexpr (!IsIntegral<RightDataType>)
|
|
return false;
|
|
else if constexpr (std::is_same_v<DataTypeFixedString, LeftDataType>)
|
|
{
|
|
return (res = executeStringInteger<ColumnFixedString>(arguments, left, right)) != nullptr;
|
|
}
|
|
else if constexpr (std::is_same_v<DataTypeString, LeftDataType>)
|
|
return (res = executeStringInteger<ColumnString>(arguments, left, right)) != nullptr;
|
|
}
|
|
else
|
|
return (res = executeNumeric(arguments, left, right, right_nullmap)) != nullptr;
|
|
});
|
|
|
|
if (!valid)
|
|
{
|
|
// This is a logical error, because the types should have been checked
|
|
// by getReturnTypeImpl().
|
|
throw Exception(ErrorCodes::LOGICAL_ERROR,
|
|
"Arguments of '{}' have incorrect data types: '{}' of type '{}',"
|
|
" '{}' of type '{}'", getName(),
|
|
left_argument.name, left_argument.type->getName(),
|
|
right_argument.name, right_argument.type->getName());
|
|
}
|
|
|
|
return res;
|
|
}
|
|
|
|
#if USE_EMBEDDED_COMPILER
|
|
bool isCompilableImpl(const DataTypes & arguments, const DataTypePtr & result_type) const override
|
|
{
|
|
if (2 != arguments.size())
|
|
return false;
|
|
|
|
if (!canBeNativeType(*arguments[0]) || !canBeNativeType(*arguments[1]) || !canBeNativeType(*result_type))
|
|
return false;
|
|
|
|
WhichDataType data_type_lhs(arguments[0]);
|
|
WhichDataType data_type_rhs(arguments[1]);
|
|
if ((data_type_lhs.isDateOrDate32() || data_type_lhs.isDateTime()) ||
|
|
(data_type_rhs.isDateOrDate32() || data_type_rhs.isDateTime()))
|
|
return false;
|
|
|
|
return castBothTypes(arguments[0].get(), arguments[1].get(), [&](const auto & left, const auto & right)
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
if constexpr (!std::is_same_v<DataTypeFixedString, LeftDataType> &&
|
|
!std::is_same_v<DataTypeFixedString, RightDataType> &&
|
|
!std::is_same_v<DataTypeString, LeftDataType> &&
|
|
!std::is_same_v<DataTypeString, RightDataType>)
|
|
{
|
|
using ResultDataType = typename BinaryOperationTraits<Op, LeftDataType, RightDataType>::ResultDataType;
|
|
using OpSpec = Op<typename LeftDataType::FieldType, typename RightDataType::FieldType>;
|
|
if constexpr (!std::is_same_v<ResultDataType, InvalidType> && !IsDataTypeDecimal<ResultDataType> && OpSpec::compilable)
|
|
return true;
|
|
}
|
|
return false;
|
|
});
|
|
}
|
|
|
|
llvm::Value * compileImpl(llvm::IRBuilderBase & builder, const ValuesWithType & arguments, const DataTypePtr & result_type) const override
|
|
{
|
|
assert(2 == arguments.size());
|
|
|
|
llvm::Value * result = nullptr;
|
|
castBothTypes(arguments[0].type.get(), arguments[1].type.get(), [&](const auto & left, const auto & right)
|
|
{
|
|
using LeftDataType = std::decay_t<decltype(left)>;
|
|
using RightDataType = std::decay_t<decltype(right)>;
|
|
if constexpr (!std::is_same_v<DataTypeFixedString, LeftDataType> &&
|
|
!std::is_same_v<DataTypeFixedString, RightDataType> &&
|
|
!std::is_same_v<DataTypeString, LeftDataType> &&
|
|
!std::is_same_v<DataTypeString, RightDataType>)
|
|
{
|
|
using ResultDataType = typename BinaryOperationTraits<Op, LeftDataType, RightDataType>::ResultDataType;
|
|
using OpSpec = Op<typename LeftDataType::FieldType, typename RightDataType::FieldType>;
|
|
if constexpr (!std::is_same_v<ResultDataType, InvalidType> && !IsDataTypeDecimal<ResultDataType> && OpSpec::compilable)
|
|
{
|
|
auto & b = static_cast<llvm::IRBuilder<> &>(builder);
|
|
auto * lval = nativeCast(b, arguments[0], result_type);
|
|
auto * rval = nativeCast(b, arguments[1], result_type);
|
|
result = OpSpec::compile(b, lval, rval, std::is_signed_v<typename ResultDataType::FieldType>);
|
|
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return false;
|
|
});
|
|
|
|
return result;
|
|
}
|
|
#endif
|
|
|
|
bool canBeExecutedOnDefaultArguments() const override { return valid_on_default_arguments; }
|
|
};
|
|
|
|
|
|
template <template <typename, typename> class Op, typename Name, bool valid_on_default_arguments = true, bool valid_on_float_arguments = true, bool division_by_nullable = false>
|
|
class FunctionBinaryArithmeticWithConstants : public FunctionBinaryArithmetic<Op, Name, valid_on_default_arguments, valid_on_float_arguments, division_by_nullable>
|
|
{
|
|
public:
|
|
using Base = FunctionBinaryArithmetic<Op, Name, valid_on_default_arguments, valid_on_float_arguments, division_by_nullable>;
|
|
using Monotonicity = typename Base::Monotonicity;
|
|
|
|
static FunctionPtr create(
|
|
const ColumnWithTypeAndName & left_,
|
|
const ColumnWithTypeAndName & right_,
|
|
const DataTypePtr & return_type_,
|
|
ContextPtr context)
|
|
{
|
|
return std::make_shared<FunctionBinaryArithmeticWithConstants>(left_, right_, return_type_, context);
|
|
}
|
|
|
|
FunctionBinaryArithmeticWithConstants(
|
|
const ColumnWithTypeAndName & left_,
|
|
const ColumnWithTypeAndName & right_,
|
|
const DataTypePtr & return_type_,
|
|
ContextPtr context_)
|
|
: Base(context_), left(left_), right(right_), return_type(return_type_)
|
|
{
|
|
}
|
|
|
|
ColumnPtr executeImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type, size_t input_rows_count) const override
|
|
{
|
|
if (left.column && isColumnConst(*left.column) && arguments.size() == 1)
|
|
{
|
|
ColumnsWithTypeAndName columns_with_constant
|
|
= {{left.column->cloneResized(input_rows_count), left.type, left.name},
|
|
arguments[0]};
|
|
|
|
return Base::executeImpl(columns_with_constant, result_type, input_rows_count);
|
|
}
|
|
else if (right.column && isColumnConst(*right.column) && arguments.size() == 1)
|
|
{
|
|
ColumnsWithTypeAndName columns_with_constant
|
|
= {arguments[0],
|
|
{right.column->cloneResized(input_rows_count), right.type, right.name}};
|
|
|
|
return Base::executeImpl(columns_with_constant, result_type, input_rows_count);
|
|
}
|
|
else
|
|
return Base::executeImpl(arguments, result_type, input_rows_count);
|
|
}
|
|
|
|
bool hasInformationAboutMonotonicity() const override
|
|
{
|
|
const std::string_view name_view = Name::name;
|
|
return (name_view == "minus" || name_view == "plus" || name_view == "divide" || name_view == "intDiv");
|
|
}
|
|
|
|
Monotonicity getMonotonicityForRange(const IDataType &, const Field & left_point, const Field & right_point) const override
|
|
{
|
|
const std::string_view name_view = Name::name;
|
|
|
|
// For simplicity, we treat null values as monotonicity breakers, except for variable / non-zero constant.
|
|
if (left_point.isNull() || right_point.isNull())
|
|
{
|
|
if (name_view == "divide" || name_view == "intDiv")
|
|
{
|
|
// variable / constant
|
|
if (right.column && isColumnConst(*right.column))
|
|
{
|
|
auto constant = (*right.column)[0];
|
|
if (applyVisitor(FieldVisitorAccurateEquals(), constant, Field(0)))
|
|
return {false, true, false}; // variable / 0 is undefined, let's treat it as non-monotonic
|
|
bool is_constant_positive = applyVisitor(FieldVisitorAccurateLess(), Field(0), constant);
|
|
|
|
// division is saturated to `inf`, thus it doesn't have overflow issues.
|
|
return {true, is_constant_positive, true};
|
|
}
|
|
}
|
|
return {false, true, false, false};
|
|
}
|
|
|
|
// For simplicity, we treat every single value interval as positive monotonic.
|
|
if (applyVisitor(FieldVisitorAccurateEquals(), left_point, right_point))
|
|
return {true, true, false, false};
|
|
|
|
if (name_view == "minus" || name_view == "plus")
|
|
{
|
|
// const +|- variable
|
|
if (left.column && isColumnConst(*left.column))
|
|
{
|
|
auto left_type = removeNullable(removeLowCardinality(left.type));
|
|
auto right_type = removeNullable(removeLowCardinality(right.type));
|
|
auto ret_type = removeNullable(removeLowCardinality(return_type));
|
|
|
|
auto transform = [&](const Field & point)
|
|
{
|
|
ColumnsWithTypeAndName columns_with_constant
|
|
= {{left_type->createColumnConst(1, (*left.column)[0]), left_type, left.name},
|
|
{right_type->createColumnConst(1, point), right_type, right.name}};
|
|
|
|
/// This is a bit dangerous to call Base::executeImpl cause it ignores `use Default Implementation For XXX` flags.
|
|
/// It was possible to check monotonicity for nullable right type which result to exception.
|
|
/// Adding removeNullable above fixes the issue, but some other inconsistency may left.
|
|
auto col = Base::executeImpl(columns_with_constant, ret_type, 1);
|
|
Field point_transformed;
|
|
col->get(0, point_transformed);
|
|
return point_transformed;
|
|
};
|
|
|
|
bool is_positive_monotonicity = applyVisitor(FieldVisitorAccurateLess(), left_point, right_point)
|
|
== applyVisitor(FieldVisitorAccurateLess(), transform(left_point), transform(right_point));
|
|
|
|
if (name_view == "plus")
|
|
{
|
|
// Check if there is an overflow
|
|
if (is_positive_monotonicity)
|
|
return {true, true, false, true};
|
|
else
|
|
return {false, true, false, false};
|
|
}
|
|
else
|
|
{
|
|
// Check if there is an overflow
|
|
if (!is_positive_monotonicity)
|
|
return {true, false, false, true};
|
|
else
|
|
return {false, false, false, false};
|
|
}
|
|
}
|
|
// variable +|- constant
|
|
else if (right.column && isColumnConst(*right.column))
|
|
{
|
|
auto left_type = removeNullable(removeLowCardinality(left.type));
|
|
auto right_type = removeNullable(removeLowCardinality(right.type));
|
|
auto ret_type = removeNullable(removeLowCardinality(return_type));
|
|
|
|
auto transform = [&](const Field & point)
|
|
{
|
|
ColumnsWithTypeAndName columns_with_constant
|
|
= {{left_type->createColumnConst(1, point), left_type, left.name},
|
|
{right_type->createColumnConst(1, (*right.column)[0]), right_type, right.name}};
|
|
|
|
auto col = Base::executeImpl(columns_with_constant, ret_type, 1);
|
|
Field point_transformed;
|
|
col->get(0, point_transformed);
|
|
return point_transformed;
|
|
};
|
|
|
|
// Check if there is an overflow
|
|
if (applyVisitor(FieldVisitorAccurateLess(), left_point, right_point)
|
|
== applyVisitor(FieldVisitorAccurateLess(), transform(left_point), transform(right_point)))
|
|
return {true, true, false, true};
|
|
else
|
|
return {false, true, false, false};
|
|
}
|
|
}
|
|
if (name_view == "divide" || name_view == "intDiv")
|
|
{
|
|
bool is_strict = name_view == "divide";
|
|
|
|
// const / variable
|
|
if (left.column && isColumnConst(*left.column))
|
|
{
|
|
auto constant = (*left.column)[0];
|
|
if (applyVisitor(FieldVisitorAccurateEquals(), constant, Field(0)))
|
|
return {true, true, false, false}; // 0 / 0 is undefined, thus it's not always monotonic
|
|
|
|
bool is_constant_positive = applyVisitor(FieldVisitorAccurateLess(), Field(0), constant);
|
|
if (applyVisitor(FieldVisitorAccurateLess(), left_point, Field(0))
|
|
&& applyVisitor(FieldVisitorAccurateLess(), right_point, Field(0)))
|
|
{
|
|
return {true, is_constant_positive, false, is_strict};
|
|
}
|
|
else if (
|
|
applyVisitor(FieldVisitorAccurateLess(), Field(0), left_point)
|
|
&& applyVisitor(FieldVisitorAccurateLess(), Field(0), right_point))
|
|
{
|
|
return {true, !is_constant_positive, false, is_strict};
|
|
}
|
|
}
|
|
// variable / constant
|
|
else if (right.column && isColumnConst(*right.column))
|
|
{
|
|
auto constant = (*right.column)[0];
|
|
if (applyVisitor(FieldVisitorAccurateEquals(), constant, Field(0)))
|
|
return {false, true, false, false}; // variable / 0 is undefined, let's treat it as non-monotonic
|
|
|
|
bool is_constant_positive = applyVisitor(FieldVisitorAccurateLess(), Field(0), constant);
|
|
// division is saturated to `inf`, thus it doesn't have overflow issues.
|
|
return {true, is_constant_positive, true, is_strict};
|
|
}
|
|
}
|
|
return {false, true, false};
|
|
}
|
|
|
|
private:
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|
ColumnWithTypeAndName left;
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|
ColumnWithTypeAndName right;
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|
DataTypePtr return_type;
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|
};
|
|
|
|
template <template <typename, typename> class Op, typename Name, bool valid_on_default_arguments = true, bool valid_on_float_arguments = true>
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|
class BinaryArithmeticOverloadResolver : public IFunctionOverloadResolver
|
|
{
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|
public:
|
|
static constexpr auto name = Name::name;
|
|
static FunctionOverloadResolverPtr create(ContextPtr context)
|
|
{
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|
return std::make_unique<BinaryArithmeticOverloadResolver>(context);
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|
}
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|
|
|
explicit BinaryArithmeticOverloadResolver(ContextPtr context_) : context(context_) {}
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|
|
|
String getName() const override { return name; }
|
|
size_t getNumberOfArguments() const override { return 2; }
|
|
bool isVariadic() const override { return false; }
|
|
|
|
FunctionBasePtr buildImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & return_type) const override
|
|
{
|
|
/// Check the case when operation is divide, intDiv or modulo and denominator is Nullable(Something).
|
|
/// For divide operation we should check only Nullable(Decimal), because only this case can throw division by zero error.
|
|
bool division_by_nullable = !arguments[0].type->onlyNull() && !arguments[1].type->onlyNull() && arguments[1].type->isNullable()
|
|
&& (IsOperation<Op>::div_int || IsOperation<Op>::modulo || IsOperation<Op>::positive_modulo
|
|
|| (IsOperation<Op>::div_floating
|
|
&& (isDecimalOrNullableDecimal(arguments[0].type) || isDecimalOrNullableDecimal(arguments[1].type))));
|
|
|
|
/// More efficient specialization for two numeric arguments.
|
|
if (arguments.size() == 2
|
|
&& ((arguments[0].column && isColumnConst(*arguments[0].column))
|
|
|| (arguments[1].column && isColumnConst(*arguments[1].column))))
|
|
{
|
|
auto function = division_by_nullable ? FunctionBinaryArithmeticWithConstants<Op, Name, valid_on_default_arguments, valid_on_float_arguments, true>::create(
|
|
arguments[0], arguments[1], return_type, context)
|
|
: FunctionBinaryArithmeticWithConstants<Op, Name, valid_on_default_arguments, valid_on_float_arguments, false>::create(
|
|
arguments[0], arguments[1], return_type, context);
|
|
|
|
return std::make_unique<FunctionToFunctionBaseAdaptor>(
|
|
function,
|
|
collections::map<DataTypes>(arguments, [](const auto & elem) { return elem.type; }),
|
|
return_type);
|
|
}
|
|
auto function = division_by_nullable
|
|
? FunctionBinaryArithmetic<Op, Name, valid_on_default_arguments, valid_on_float_arguments, true>::create(context)
|
|
: FunctionBinaryArithmetic<Op, Name, valid_on_default_arguments, valid_on_float_arguments, false>::create(context);
|
|
|
|
return std::make_unique<FunctionToFunctionBaseAdaptor>(
|
|
function,
|
|
collections::map<DataTypes>(arguments, [](const auto & elem) { return elem.type; }),
|
|
return_type);
|
|
|
|
}
|
|
|
|
DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override
|
|
{
|
|
if (arguments.size() != 2)
|
|
throw Exception(ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH,
|
|
"Number of arguments for function {} doesn't match: passed {}, should be 2",
|
|
getName(), arguments.size());
|
|
return FunctionBinaryArithmetic<Op, Name, valid_on_default_arguments, valid_on_float_arguments>::getReturnTypeImplStatic(arguments, context);
|
|
}
|
|
|
|
private:
|
|
ContextPtr context;
|
|
};
|
|
}
|