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284 lines
12 KiB
C++
284 lines
12 KiB
C++
#pragma once
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#include <cmath>
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#include <common/arithmeticOverflow.h>
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#include <IO/WriteHelpers.h>
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#include <IO/ReadHelpers.h>
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#include <AggregateFunctions/IAggregateFunction.h>
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#include <AggregateFunctions/Moments.h>
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#include <DataTypes/DataTypesNumber.h>
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#include <DataTypes/DataTypesDecimal.h>
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#include <Columns/ColumnVector.h>
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#include <Columns/ColumnDecimal.h>
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/** This is simple, not numerically stable
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* implementations of variance/covariance/correlation functions.
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*
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* It is about two times faster than stable variants.
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* Numerical errors may occur during summation.
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*
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* This implementation is selected as default,
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* because "you don't pay for what you don't need" principle.
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*
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* For more sophisticated implementation, look at AggregateFunctionStatistics.h
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*/
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namespace DB
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{
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enum class StatisticsFunctionKind
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{
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varPop, varSamp,
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stddevPop, stddevSamp,
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skewPop, skewSamp,
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kurtPop, kurtSamp,
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covarPop, covarSamp,
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corr
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};
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template <typename T, StatisticsFunctionKind _kind, size_t _level>
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struct StatFuncOneArg
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{
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using Type1 = T;
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using Type2 = T;
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using ResultType = std::conditional_t<std::is_same_v<T, Float32>, Float32, Float64>;
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using Data = std::conditional_t<IsDecimalNumber<T>, VarMomentsDecimal<Decimal128, _level>, VarMoments<ResultType, _level>>;
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static constexpr StatisticsFunctionKind kind = _kind;
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static constexpr UInt32 num_args = 1;
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};
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template <typename T1, typename T2, StatisticsFunctionKind _kind>
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struct StatFuncTwoArg
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{
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using Type1 = T1;
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using Type2 = T2;
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using ResultType = std::conditional_t<std::is_same_v<T1, T2> && std::is_same_v<T1, Float32>, Float32, Float64>;
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using Data = std::conditional_t<_kind == StatisticsFunctionKind::corr, CorrMoments<ResultType>, CovarMoments<ResultType>>;
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static constexpr StatisticsFunctionKind kind = _kind;
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static constexpr UInt32 num_args = 2;
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};
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template <typename StatFunc>
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class AggregateFunctionVarianceSimple final
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: public IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>
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{
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public:
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using T1 = typename StatFunc::Type1;
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using T2 = typename StatFunc::Type2;
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using ColVecT1 = std::conditional_t<IsDecimalNumber<T1>, ColumnDecimal<T1>, ColumnVector<T1>>;
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using ColVecT2 = std::conditional_t<IsDecimalNumber<T2>, ColumnDecimal<T2>, ColumnVector<T2>>;
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using ResultType = typename StatFunc::ResultType;
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using ColVecResult = ColumnVector<ResultType>;
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AggregateFunctionVarianceSimple(const DataTypes & argument_types_)
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: IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>(argument_types_, {})
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, src_scale(0)
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{}
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AggregateFunctionVarianceSimple(const IDataType & data_type, const DataTypes & argument_types_)
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: IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>(argument_types_, {})
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, src_scale(getDecimalScale(data_type))
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{}
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String getName() const override
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{
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
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return "varPop";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
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return "varSamp";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
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return "stddevPop";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
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return "stddevSamp";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
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return "skewPop";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
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return "skewSamp";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
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return "kurtPop";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
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return "kurtSamp";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::covarPop)
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return "covarPop";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::covarSamp)
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return "covarSamp";
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if constexpr (StatFunc::kind == StatisticsFunctionKind::corr)
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return "corr";
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__builtin_unreachable();
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}
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DataTypePtr getReturnType() const override
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{
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return std::make_shared<DataTypeNumber<ResultType>>();
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}
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void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
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{
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if constexpr (StatFunc::num_args == 2)
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this->data(place).add(
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static_cast<ResultType>(static_cast<const ColVecT1 &>(*columns[0]).getData()[row_num]),
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static_cast<ResultType>(static_cast<const ColVecT2 &>(*columns[1]).getData()[row_num]));
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else
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{
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if constexpr (std::is_same_v<T1, Decimal256>)
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{
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this->data(place).add(static_cast<ResultType>(
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static_cast<const ColVecT1 &>(*columns[0]).getData()[row_num].value
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));
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}
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else
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this->data(place).add(
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static_cast<ResultType>(static_cast<const ColVecT1 &>(*columns[0]).getData()[row_num]));
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}
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}
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void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
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{
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this->data(place).merge(this->data(rhs));
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}
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void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
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{
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this->data(place).write(buf);
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}
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void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
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{
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this->data(place).read(buf);
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}
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void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
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{
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const auto & data = this->data(place);
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auto & dst = static_cast<ColVecResult &>(to).getData();
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if constexpr (IsDecimalNumber<T1>)
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{
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
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dst.push_back(data.getPopulation(src_scale * 2));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
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dst.push_back(data.getSample(src_scale * 2));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
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dst.push_back(sqrt(data.getPopulation(src_scale * 2)));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
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dst.push_back(sqrt(data.getSample(src_scale * 2)));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
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{
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Float64 var_value = data.getPopulation(src_scale * 2);
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if (var_value > 0)
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dst.push_back(data.getMoment3(src_scale * 3) / pow(var_value, 1.5));
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else
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dst.push_back(std::numeric_limits<Float64>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
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{
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Float64 var_value = data.getSample(src_scale * 2);
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if (var_value > 0)
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dst.push_back(data.getMoment3(src_scale * 3) / pow(var_value, 1.5));
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else
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dst.push_back(std::numeric_limits<Float64>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
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{
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Float64 var_value = data.getPopulation(src_scale * 2);
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if (var_value > 0)
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dst.push_back(data.getMoment4(src_scale * 4) / pow(var_value, 2));
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else
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dst.push_back(std::numeric_limits<Float64>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
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{
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Float64 var_value = data.getSample(src_scale * 2);
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if (var_value > 0)
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dst.push_back(data.getMoment4(src_scale * 4) / pow(var_value, 2));
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else
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dst.push_back(std::numeric_limits<Float64>::quiet_NaN());
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}
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}
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else
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{
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
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dst.push_back(data.getPopulation());
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if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
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dst.push_back(data.getSample());
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
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dst.push_back(sqrt(data.getPopulation()));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
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dst.push_back(sqrt(data.getSample()));
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
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{
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ResultType var_value = data.getPopulation();
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if (var_value > 0)
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dst.push_back(data.getMoment3() / pow(var_value, 1.5));
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else
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dst.push_back(std::numeric_limits<ResultType>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
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{
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ResultType var_value = data.getSample();
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if (var_value > 0)
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dst.push_back(data.getMoment3() / pow(var_value, 1.5));
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else
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dst.push_back(std::numeric_limits<ResultType>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
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{
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ResultType var_value = data.getPopulation();
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if (var_value > 0)
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dst.push_back(data.getMoment4() / pow(var_value, 2));
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else
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dst.push_back(std::numeric_limits<ResultType>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
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{
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ResultType var_value = data.getSample();
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if (var_value > 0)
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dst.push_back(data.getMoment4() / pow(var_value, 2));
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else
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dst.push_back(std::numeric_limits<ResultType>::quiet_NaN());
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}
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if constexpr (StatFunc::kind == StatisticsFunctionKind::covarPop)
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dst.push_back(data.getPopulation());
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if constexpr (StatFunc::kind == StatisticsFunctionKind::covarSamp)
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dst.push_back(data.getSample());
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if constexpr (StatFunc::kind == StatisticsFunctionKind::corr)
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dst.push_back(data.get());
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}
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}
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private:
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UInt32 src_scale;
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};
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template <typename T> using AggregateFunctionVarPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::varPop, 2>>;
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template <typename T> using AggregateFunctionVarSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::varSamp, 2>>;
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template <typename T> using AggregateFunctionStddevPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::stddevPop, 2>>;
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template <typename T> using AggregateFunctionStddevSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::stddevSamp, 2>>;
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template <typename T> using AggregateFunctionSkewPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::skewPop, 3>>;
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template <typename T> using AggregateFunctionSkewSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::skewSamp, 3>>;
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template <typename T> using AggregateFunctionKurtPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::kurtPop, 4>>;
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template <typename T> using AggregateFunctionKurtSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::kurtSamp, 4>>;
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template <typename T1, typename T2> using AggregateFunctionCovarPopSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::covarPop>>;
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template <typename T1, typename T2> using AggregateFunctionCovarSampSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::covarSamp>>;
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template <typename T1, typename T2> using AggregateFunctionCorrSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::corr>>;
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}
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