目录

摘要:

核心函数:

executeImpl

UnaryOperationImpl

MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42

AbsImpl

摘要:

记录clickhouse向量化colume

SIMD:

以加法指令为例，单指令单数据（SISD）的CPU对加法指令译码后，执行部件先访问内存，取得第一个操作数；之后再一次访问内存，取得第二个操作数；随后才能进行求和运算。而在SIMD型的CPU中，指令译码后几个执行部件同时访问内存，一次性获得所有操作数进行运算。这个特点使SIMD特别适合于多媒体应用等数据密集型运算。

如：AMD公司引以为豪的3D NOW! 技术实质就是SIMD，这使K6-2、雷鸟、毒龙处理器在音频解码、视频回放、3D游戏等应用中显示出优异的性能。

讯享网

架构：

静态结构:

核心函数:

executeImpl

src/Functions/FunctionUnaryArithmetic.h:295

 ColumnPtr executeImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & result_type, size_t input_rows_count) const override { /// Special case when the function is negate, argument is tuple. if (auto function_builder = getFunctionForTupleArithmetic(arguments[0].type, context)) { return function_builder->build(arguments)->execute(arguments, result_type, input_rows_count); } ColumnPtr result_column; bool valid = castType(arguments[0].type.get(), [&](const auto & type) { using DataType = std::decay_t<decltype(type)>; if constexpr (std::is_same_v<DataTypeFixedString, DataType>) { if constexpr (allow_fixed_string) { if (const auto * col = checkAndGetColumn<ColumnFixedString>(arguments[0].column.get())) { auto col_res = ColumnFixedString::create(col->getN()); auto & vec_res = col_res->getChars(); vec_res.resize(col->size() * col->getN()); FixedStringUnaryOperationImpl<Op<UInt8>>::vector(col->getChars(), vec_res); result_column = std::move(col_res); return true; } } } else if constexpr (IsDataTypeDecimal<DataType>) { using T0 = typename DataType::FieldType; if constexpr (allow_decimal) { if (auto col = checkAndGetColumn<ColumnDecimal<T0>>(arguments[0].column.get())) { if constexpr (is_sign_function) { auto col_res = ColumnVector<typename Op<T0>::ResultType>::create(); auto & vec_res = col_res->getData(); vec_res.resize(col->getData().size()); UnaryOperationImpl<T0, Op<T0>>::vector(col->getData(), vec_res); result_column = std::move(col_res); return true; } else { auto col_res = ColumnDecimal<typename Op<T0>::ResultType>::create(0, type.getScale()); auto & vec_res = col_res->getData(); vec_res.resize(col->getData().size()); UnaryOperationImpl<T0, Op<T0>>::vector(col->getData(), vec_res); result_column = std::move(col_res); return true; } } } } else { using T0 = typename DataType::FieldType; if (auto col = checkAndGetColumn<ColumnVector<T0>>(arguments[0].column.get())) { auto col_res = ColumnVector<typename Op<T0>::ResultType>::create(); auto & vec_res = col_res->getData(); vec_res.resize(col->getData().size()); UnaryOperationImpl<T0, Op<T0>>::vector(col->getData(), vec_res); result_column = std::move(col_res); return true; } } return false; }); if (!valid) throw Exception(getName() + "'s argument does not match the expected data type", ErrorCodes::LOGICAL_ERROR); return result_column; }

关键点:

讯享网 using T0 = typename DataType::FieldType; if (auto col = checkAndGetColumn<ColumnVector<T0>>(arguments[0].column.get())) { auto col_res = ColumnVector<typename Op<T0>::ResultType>::create(); auto & vec_res = col_res->getData(); vec_res.resize(col->getData().size()); UnaryOperationImpl<T0, Op<T0>>::vector(col->getData(), vec_res); result_column = std::move(col_res); return true; }

UnaryOperationImpl
 

 template <typename A, typename Op> struct UnaryOperationImpl { using ResultType = typename Op::ResultType; using ColVecA = ColumnVectorOrDecimal<A>; using ColVecC = ColumnVectorOrDecimal<ResultType>; using ArrayA = typename ColVecA::Container; using ArrayC = typename ColVecC::Container; MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42(vectorImpl, MULTITARGET_FH( static void NO_INLINE), /*vectorImpl*/ MULTITARGET_FB((const ArrayA & a, ArrayC & c) /// NOLINT { size_t size = a.size(); for (size_t i = 0; i < size; ++i) c[i] = Op::apply(a[i]); })) static void NO_INLINE vector(const ArrayA & a, ArrayC & c) { #if USE_MULTITARGET_CODE if (isArchSupported(TargetArch::AVX2)) { vectorImplAVX2(a, c); return; } else if (isArchSupported(TargetArch::SSE42)) { vectorImplSSE42(a, c); return; } #endif vectorImpl(a, c); } static void constant(A a, ResultType & c) { c = Op::apply(a); } }; 

关键点:

讯享网 MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42(vectorImpl, MULTITARGET_FH( static void NO_INLINE), /*vectorImpl*/ MULTITARGET_FB((const ArrayA & a, ArrayC & c) /// NOLINT { size_t size = a.size(); for (size_t i = 0; i < size; ++i) c[i] = Op::apply(a[i]); }))

MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42

 #if ENABLE_MULTITARGET_CODE && defined(__GNUC__) && defined(__x86_64__) /// NOLINTNEXTLINE #define MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42(name, FUNCTION_HEADER, FUNCTION_BODY) \ FUNCTION_HEADER \ \ AVX2_FUNCTION_SPECIFIC_ATTRIBUTE \ nameAVX2 \ FUNCTION_BODY \ \ FUNCTION_HEADER \ \ SSE42_FUNCTION_SPECIFIC_ATTRIBUTE \ nameSSE42 \ FUNCTION_BODY \ \ FUNCTION_HEADER \ \ name \ FUNCTION_BODY \ #else /// NOLINTNEXTLINE #define MULTITARGET_FUNCTION_WRAPPER_AVX2_SSE42(name, FUNCTION_HEADER, FUNCTION_BODY) \ FUNCTION_HEADER \ \ name \ FUNCTION_BODY \ #endif

AbsImpl
 

讯享网 template <typename A> struct AbsImpl { using ResultType = std::conditional_t<is_decimal<A>, A, typename NumberTraits::ResultOfAbs<A>::Type>; static const constexpr bool allow_fixed_string = false; static const constexpr bool allow_string_integer = false; static inline NO_SANITIZE_UNDEFINED ResultType apply(A a) { if constexpr (is_decimal<A>) return a < A(0) ? A(-a) : a; else if constexpr (is_big_int_v<A> && is_signed_v<A>) return (a < 0) ? -a : a; else if constexpr (is_integer<A> && is_signed_v<A>) return a < 0 ? static_cast<ResultType>(~a) + 1 : static_cast<ResultType>(a); else if constexpr (is_integer<A> && is_unsigned_v<A>) return static_cast<ResultType>(a); else if constexpr (std::is_floating_point_v<A>) return static_cast<ResultType>(std::abs(a)); } #if USE_EMBEDDED_COMPILER static constexpr bool compilable = false; /// special type handling, some other time #endif };