2018-12-03 03:17:06 +00:00
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#pragma once
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#include <Core/callOnTypeIndex.h>
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#include <DataTypes/DataTypesNumber.h>
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#include <DataTypes/DataTypesDecimal.h>
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#include <Columns/ColumnsNumber.h>
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#include <Columns/ColumnDecimal.h>
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#include <Functions/IFunction.h>
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#include <Functions/FunctionHelpers.h>
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#include <Common/config.h>
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/** More efficient implementations of mathematical functions are possible when using a separate library.
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2019-01-22 19:56:53 +00:00
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* Disabled due to license compatibility limitations.
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2018-12-03 03:17:06 +00:00
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* To enable: download http://www.agner.org/optimize/vectorclass.zip and unpack to contrib/vectorclass
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* Then rebuild with -DENABLE_VECTORCLASS=1
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*/
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#if USE_VECTORCLASS
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#ifdef __clang__
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#pragma clang diagnostic push
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#pragma clang diagnostic ignored "-Wshift-negative-value"
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#endif
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#include <vectorf128.h> // Y_IGNORE
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#include <vectormath_exp.h> // Y_IGNORE
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#include <vectormath_trig.h> // Y_IGNORE
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#ifdef __clang__
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#pragma clang diagnostic pop
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#endif
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#endif
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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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}
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template <typename Impl>
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class FunctionMathUnaryFloat64 : public IFunction
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{
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public:
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static constexpr auto name = Impl::name;
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static FunctionPtr create(const Context &) { return std::make_shared<FunctionMathUnaryFloat64>(); }
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static_assert(Impl::rows_per_iteration > 0, "Impl must process at least one row per iteration");
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private:
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String getName() const override { return name; }
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size_t getNumberOfArguments() const override { return 1; }
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DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override
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{
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const auto & arg = arguments.front();
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if (!isNumber(arg) && !isDecimal(arg))
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throw Exception{"Illegal type " + arg->getName() + " of argument of function " + getName(),
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ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT};
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return std::make_shared<DataTypeFloat64>();
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}
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template <typename T>
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static void executeInIterations(const T * src_data, Float64 * dst_data, size_t size)
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{
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const size_t rows_remaining = size % Impl::rows_per_iteration;
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const size_t rows_size = size - rows_remaining;
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for (size_t i = 0; i < rows_size; i += Impl::rows_per_iteration)
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Impl::execute(&src_data[i], &dst_data[i]);
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if (rows_remaining != 0)
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{
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T src_remaining[Impl::rows_per_iteration];
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memcpy(src_remaining, &src_data[rows_size], rows_remaining * sizeof(T));
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memset(src_remaining + rows_remaining, 0, (Impl::rows_per_iteration - rows_remaining) * sizeof(T));
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Float64 dst_remaining[Impl::rows_per_iteration];
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Impl::execute(src_remaining, dst_remaining);
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memcpy(&dst_data[rows_size], dst_remaining, rows_remaining * sizeof(Float64));
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}
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}
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template <typename T>
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static bool execute(Block & block, const ColumnVector<T> * col, const size_t result)
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{
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const auto & src_data = col->getData();
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const size_t size = src_data.size();
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auto dst = ColumnVector<Float64>::create();
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auto & dst_data = dst->getData();
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dst_data.resize(size);
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executeInIterations(src_data.data(), dst_data.data(), size);
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block.getByPosition(result).column = std::move(dst);
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return true;
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}
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template <typename T>
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static bool execute(Block & block, const ColumnDecimal<T> * col, const size_t result)
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{
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const auto & src_data = col->getData();
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const size_t size = src_data.size();
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UInt32 scale = src_data.getScale();
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auto dst = ColumnVector<Float64>::create();
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auto & dst_data = dst->getData();
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dst_data.resize(size);
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for (size_t i = 0; i < size; ++i)
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dst_data[i] = convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(src_data[i], scale);
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executeInIterations(dst_data.data(), dst_data.data(), size);
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block.getByPosition(result).column = std::move(dst);
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return true;
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}
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bool useDefaultImplementationForConstants() const override { return true; }
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void executeImpl(Block & block, const ColumnNumbers & arguments, size_t result, size_t /*input_rows_count*/) override
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{
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const ColumnWithTypeAndName & col = block.getByPosition(arguments[0]);
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auto call = [&](const auto & types) -> bool
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{
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using Types = std::decay_t<decltype(types)>;
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using Type = typename Types::RightType;
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using ColVecType = std::conditional_t<IsDecimalNumber<Type>, ColumnDecimal<Type>, ColumnVector<Type>>;
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const auto col_vec = checkAndGetColumn<ColVecType>(col.column.get());
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return execute<Type>(block, col_vec, result);
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};
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if (!callOnBasicType<void, true, true, true, false>(col.type->getTypeId(), call))
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throw Exception{"Illegal column " + col.column->getName() + " of argument of function " + getName(),
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ErrorCodes::ILLEGAL_COLUMN};
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}
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};
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template <typename Name, Float64(Function)(Float64)>
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struct UnaryFunctionPlain
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{
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static constexpr auto name = Name::name;
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static constexpr auto rows_per_iteration = 1;
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template <typename T>
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static void execute(const T * src, Float64 * dst)
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{
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dst[0] = static_cast<Float64>(Function(static_cast<Float64>(src[0])));
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}
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};
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#if USE_VECTORCLASS
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template <typename Name, Vec2d(Function)(const Vec2d &)>
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struct UnaryFunctionVectorized
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{
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static constexpr auto name = Name::name;
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static constexpr auto rows_per_iteration = 2;
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template <typename T>
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static void execute(const T * src, Float64 * dst)
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{
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const auto result = Function(Vec2d(src[0], src[1]));
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result.store(dst);
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}
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};
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#else
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#define UnaryFunctionVectorized UnaryFunctionPlain
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#endif
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}
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