2017-12-22 22:23:03 +00:00
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#pragma once
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#include <cmath>
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2018-09-13 18:36:47 +00:00
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#include <common/arithmeticOverflow.h>
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2017-12-22 22:23:03 +00:00
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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 <DataTypes/DataTypesNumber.h>
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2018-09-13 18:36:47 +00:00
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#include <DataTypes/DataTypesDecimal.h>
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2017-12-26 19:00:20 +00:00
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#include <Columns/ColumnVector.h>
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2018-09-13 18:36:47 +00:00
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#include <Columns/ColumnDecimal.h>
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2017-12-22 22:23:03 +00:00
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2017-12-22 23:08:57 +00:00
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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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2017-12-22 22:23:03 +00:00
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namespace DB
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{
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2018-09-13 18:36:47 +00:00
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namespace ErrorCodes
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2017-12-22 22:23:03 +00:00
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{
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2018-09-13 18:36:47 +00:00
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extern const int DECIMAL_OVERFLOW;
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}
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2017-12-22 22:23:03 +00:00
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template <typename T>
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struct VarMoments
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{
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T m0{};
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T m1{};
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T m2{};
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void add(T x)
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{
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++m0;
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m1 += x;
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m2 += x * x;
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}
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void merge(const VarMoments & rhs)
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{
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m0 += rhs.m0;
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m1 += rhs.m1;
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m2 += rhs.m2;
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}
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void write(WriteBuffer & buf) const
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{
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writePODBinary(*this, buf);
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}
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void read(ReadBuffer & buf)
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{
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readPODBinary(*this, buf);
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}
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2018-12-27 01:03:16 +00:00
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T NO_SANITIZE_UNDEFINED getPopulation() const
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2018-09-13 18:36:47 +00:00
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{
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return (m2 - m1 * m1 / m0) / m0;
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}
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2018-12-27 01:03:16 +00:00
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T NO_SANITIZE_UNDEFINED getSample() const
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2018-09-13 18:36:47 +00:00
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{
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if (m0 == 0)
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return std::numeric_limits<T>::quiet_NaN();
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return (m2 - m1 * m1 / m0) / (m0 - 1);
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}
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};
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template <typename T>
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struct VarMomentsDecimal
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{
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using NativeType = typename T::NativeType;
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UInt64 m0{};
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NativeType m1{};
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NativeType m2{};
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void add(NativeType x)
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{
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++m0;
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m1 += x;
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NativeType tmp; /// scale' = 2 * scale
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if (common::mulOverflow(x, x, tmp) || common::addOverflow(m2, tmp, m2))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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}
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void merge(const VarMomentsDecimal & rhs)
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{
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m0 += rhs.m0;
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m1 += rhs.m1;
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if (common::addOverflow(m2, rhs.m2, m2))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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}
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void write(WriteBuffer & buf) const { writePODBinary(*this, buf); }
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void read(ReadBuffer & buf) { readPODBinary(*this, buf); }
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Float64 getPopulation(UInt32 scale) const
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{
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2018-09-26 12:38:36 +00:00
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if (m0 == 0)
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return std::numeric_limits<Float64>::infinity();
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2018-09-13 18:36:47 +00:00
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NativeType tmp;
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if (common::mulOverflow(m1, m1, tmp) ||
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2018-09-26 12:38:36 +00:00
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common::subOverflow(m2, NativeType(tmp / m0), tmp))
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2018-09-13 18:36:47 +00:00
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / m0, scale);
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}
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Float64 getSample(UInt32 scale) const
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2017-12-22 22:23:03 +00:00
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{
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2018-09-13 18:36:47 +00:00
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if (m0 == 0)
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2018-09-26 12:38:36 +00:00
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return std::numeric_limits<Float64>::quiet_NaN();
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if (m0 == 1)
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return std::numeric_limits<Float64>::infinity();
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2017-12-22 22:23:03 +00:00
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2018-09-13 18:36:47 +00:00
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NativeType tmp;
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if (common::mulOverflow(m1, m1, tmp) ||
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2018-09-26 12:38:36 +00:00
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common::subOverflow(m2, NativeType(tmp / m0), tmp))
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2018-09-13 18:36:47 +00:00
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / (m0 - 1), scale);
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2017-12-22 22:23:03 +00:00
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}
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2019-05-06 03:49:14 +00:00
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};
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template <typename T, size_t _level>
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struct HighOrderMoments
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{
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T m0{};
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T m1{};
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T m2{};
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T m3{};
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T m4{};
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void add(T x)
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{
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++m0;
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m1 += x;
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m2 += x * x;
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if constexpr (_level >= 3) m3 += x * x * x;
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if constexpr (_level >= 4) m4 += x * x * x * x;
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}
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void merge(const HighOrderMoments & rhs)
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{
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m0 += rhs.m0;
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m1 += rhs.m1;
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m2 += rhs.m2;
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if constexpr (_level >= 3) m3 += rhs.m3;
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if constexpr (_level >= 4) m4 += rhs.m4;
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}
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void write(WriteBuffer & buf) const
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{
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writePODBinary(*this, buf);
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}
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void read(ReadBuffer & buf)
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{
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readPODBinary(*this, buf);
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}
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T NO_SANITIZE_UNDEFINED getPopulation() const
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{
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return (m2 - m1 * m1 / m0) / m0;
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}
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T NO_SANITIZE_UNDEFINED getSample() const
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{
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if (m0 == 0)
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return std::numeric_limits<T>::quiet_NaN();
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return (m2 - m1 * m1 / m0) / (m0 - 1);
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}
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T NO_SANITIZE_UNDEFINED getMoment3() const
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{
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2019-05-06 04:08:54 +00:00
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// to avoid accuracy problem
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if (m0 == 1)
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return 0;
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2019-05-06 03:49:14 +00:00
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return (m3
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- (3 * m2
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- 2 * m1 * m1 / m0
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) * m1 / m0
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) / m0;
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}
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T NO_SANITIZE_UNDEFINED getMoment4() const
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{
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2019-05-06 04:08:54 +00:00
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// to avoid accuracy problem
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if (m0 == 1)
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return 0;
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2019-05-06 03:49:14 +00:00
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return (m4
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- (4 * m3
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- (6 * m2
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- 3 * m1 * m1 / m0
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) * m1 / m0
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) * m1 / m0
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) / m0;
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}
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};
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template <typename T, size_t _level>
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struct HighOrderMomentsDecimal
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{
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using NativeType = typename T::NativeType;
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UInt64 m0{};
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NativeType m1{};
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NativeType m2{};
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NativeType m3{};
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NativeType m4{};
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void add(NativeType x)
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{
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++m0;
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m1 += x;
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NativeType tmp;
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if (common::mulOverflow(x, x, tmp) || common::addOverflow(m2, tmp, m2))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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if constexpr (_level >= 3) if (common::mulOverflow(tmp, x, tmp) || common::addOverflow(m3, tmp, m3))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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if constexpr (_level >= 4) if (common::mulOverflow(tmp, x, tmp) || common::addOverflow(m4, tmp, m4))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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}
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void merge(const HighOrderMomentsDecimal & rhs)
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{
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m0 += rhs.m0;
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m1 += rhs.m1;
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if (common::addOverflow(m2, rhs.m2, m2))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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if constexpr (_level >= 3) if (common::addOverflow(m3, rhs.m3, m3))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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if constexpr (_level >= 4) if (common::addOverflow(m4, rhs.m4, m4))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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}
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void write(WriteBuffer & buf) const { writePODBinary(*this, buf); }
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void read(ReadBuffer & buf) { readPODBinary(*this, buf); }
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Float64 getPopulation(UInt32 scale) const
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{
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if (m0 == 0)
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return std::numeric_limits<Float64>::infinity();
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NativeType tmp;
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if (common::mulOverflow(m1, m1, tmp) ||
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common::subOverflow(m2, NativeType(tmp / m0), tmp))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / m0, scale);
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}
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Float64 getSample(UInt32 scale) const
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{
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if (m0 == 0)
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return std::numeric_limits<Float64>::quiet_NaN();
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if (m0 == 1)
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return std::numeric_limits<Float64>::infinity();
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NativeType tmp;
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if (common::mulOverflow(m1, m1, tmp) ||
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common::subOverflow(m2, NativeType(tmp / m0), tmp))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / (m0 - 1), scale);
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}
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Float64 getMoment3(UInt32 scale) const
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{
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if (m0 == 0)
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return std::numeric_limits<Float64>::infinity();
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NativeType tmp;
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if (common::mulOverflow(2 * m1, m1, tmp) ||
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common::subOverflow(3 * m2, NativeType(tmp / m0), tmp) ||
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common::mulOverflow(tmp, m1, tmp) ||
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common::subOverflow(m3, NativeType(tmp / m0), tmp))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / m0, scale);
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}
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Float64 getMoment4(UInt32 scale) const
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{
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if (m0 == 0)
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return std::numeric_limits<Float64>::infinity();
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2018-09-13 18:36:47 +00:00
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2019-05-06 03:49:14 +00:00
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NativeType tmp;
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if (common::mulOverflow(3 * m1, m1, tmp) ||
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common::subOverflow(6 * m2, NativeType(tmp / m0), tmp) ||
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common::mulOverflow(tmp, m1, tmp) ||
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common::subOverflow(4 * m3, NativeType(tmp / m0), tmp) ||
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common::mulOverflow(tmp, m1, tmp) ||
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common::subOverflow(m4, NativeType(tmp / m0), tmp))
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throw Exception("Decimal math overflow", ErrorCodes::DECIMAL_OVERFLOW);
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return convertFromDecimal<DataTypeDecimal<T>, DataTypeNumber<Float64>>(tmp / m0, scale);
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}
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2017-12-22 22:23:03 +00:00
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};
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template <typename T>
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struct CovarMoments
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{
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T m0{};
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T x1{};
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T y1{};
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T xy{};
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void add(T x, T y)
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{
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++m0;
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x1 += x;
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y1 += y;
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xy += x * y;
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}
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void merge(const CovarMoments & rhs)
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{
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m0 += rhs.m0;
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x1 += rhs.x1;
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y1 += rhs.y1;
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xy += rhs.xy;
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}
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void write(WriteBuffer & buf) const
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{
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writePODBinary(*this, buf);
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}
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void read(ReadBuffer & buf)
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{
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readPODBinary(*this, buf);
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}
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2018-12-27 01:03:16 +00:00
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T NO_SANITIZE_UNDEFINED getPopulation() const
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2017-12-22 22:23:03 +00:00
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{
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2018-09-13 18:36:47 +00:00
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return (xy - x1 * y1 / m0) / m0;
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}
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2017-12-22 22:23:03 +00:00
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2018-12-27 01:03:16 +00:00
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T NO_SANITIZE_UNDEFINED getSample() const
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2018-09-13 18:36:47 +00:00
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{
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if (m0 == 0)
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return std::numeric_limits<T>::quiet_NaN();
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return (xy - x1 * y1 / m0) / (m0 - 1);
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2017-12-22 22:23:03 +00:00
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}
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|
|
};
|
|
|
|
|
|
|
|
template <typename T>
|
|
|
|
struct CorrMoments
|
|
|
|
{
|
|
|
|
T m0{};
|
|
|
|
T x1{};
|
|
|
|
T y1{};
|
|
|
|
T xy{};
|
|
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|
T x2{};
|
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|
|
T y2{};
|
|
|
|
|
|
|
|
void add(T x, T y)
|
|
|
|
{
|
|
|
|
++m0;
|
|
|
|
x1 += x;
|
|
|
|
y1 += y;
|
|
|
|
xy += x * y;
|
|
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|
x2 += x * x;
|
|
|
|
y2 += y * y;
|
|
|
|
}
|
|
|
|
|
|
|
|
void merge(const CorrMoments & rhs)
|
|
|
|
{
|
|
|
|
m0 += rhs.m0;
|
|
|
|
x1 += rhs.x1;
|
|
|
|
y1 += rhs.y1;
|
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|
xy += rhs.xy;
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|
|
|
x2 += rhs.x2;
|
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|
y2 += rhs.y2;
|
|
|
|
}
|
|
|
|
|
|
|
|
void write(WriteBuffer & buf) const
|
|
|
|
{
|
|
|
|
writePODBinary(*this, buf);
|
|
|
|
}
|
|
|
|
|
|
|
|
void read(ReadBuffer & buf)
|
|
|
|
{
|
|
|
|
readPODBinary(*this, buf);
|
|
|
|
}
|
|
|
|
|
2018-12-27 01:03:16 +00:00
|
|
|
T NO_SANITIZE_UNDEFINED get() const
|
2017-12-22 22:23:03 +00:00
|
|
|
{
|
|
|
|
return (m0 * xy - x1 * y1) / sqrt((m0 * x2 - x1 * x1) * (m0 * y2 - y1 * y1));
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
enum class StatisticsFunctionKind
|
|
|
|
{
|
|
|
|
varPop, varSamp,
|
|
|
|
stddevPop, stddevSamp,
|
2019-05-06 03:49:14 +00:00
|
|
|
skewPop, skewSamp,
|
|
|
|
kurtPop, kurtSamp,
|
2017-12-22 22:23:03 +00:00
|
|
|
covarPop, covarSamp,
|
|
|
|
corr
|
|
|
|
};
|
|
|
|
|
|
|
|
|
2019-05-06 03:49:14 +00:00
|
|
|
template <typename T, StatisticsFunctionKind _kind, size_t _level>
|
2018-09-13 18:36:47 +00:00
|
|
|
struct StatFuncOneArg
|
|
|
|
{
|
|
|
|
using Type1 = T;
|
|
|
|
using Type2 = T;
|
|
|
|
using ResultType = std::conditional_t<std::is_same_v<T, Float32>, Float32, Float64>;
|
2019-05-06 03:49:14 +00:00
|
|
|
using Data = std::conditional_t<
|
|
|
|
_level <= 2,
|
|
|
|
std::conditional_t<IsDecimalNumber<T>, VarMomentsDecimal<Decimal128>, VarMoments<ResultType>>,
|
|
|
|
std::conditional_t<IsDecimalNumber<T>, HighOrderMomentsDecimal<Decimal128, _level>, HighOrderMoments<ResultType, _level>>
|
|
|
|
>;
|
2017-12-22 22:59:45 +00:00
|
|
|
|
2018-09-13 18:36:47 +00:00
|
|
|
static constexpr StatisticsFunctionKind kind = _kind;
|
|
|
|
static constexpr UInt32 num_args = 1;
|
|
|
|
};
|
2017-12-22 22:59:45 +00:00
|
|
|
|
2018-09-13 18:36:47 +00:00
|
|
|
template <typename T1, typename T2, StatisticsFunctionKind _kind>
|
|
|
|
struct StatFuncTwoArg
|
2017-12-22 22:23:03 +00:00
|
|
|
{
|
2018-09-13 18:36:47 +00:00
|
|
|
using Type1 = T1;
|
|
|
|
using Type2 = T2;
|
|
|
|
using ResultType = std::conditional_t<std::is_same_v<T1, T2> && std::is_same_v<T1, Float32>, Float32, Float64>;
|
|
|
|
using Data = std::conditional_t<_kind == StatisticsFunctionKind::corr, CorrMoments<ResultType>, CovarMoments<ResultType>>;
|
2017-12-22 22:59:45 +00:00
|
|
|
|
2018-09-13 18:36:47 +00:00
|
|
|
static constexpr StatisticsFunctionKind kind = _kind;
|
|
|
|
static constexpr UInt32 num_args = 2;
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
template <typename StatFunc>
|
|
|
|
class AggregateFunctionVarianceSimple final
|
|
|
|
: public IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>
|
|
|
|
{
|
2017-12-22 22:23:03 +00:00
|
|
|
public:
|
2018-09-13 18:36:47 +00:00
|
|
|
using T1 = typename StatFunc::Type1;
|
|
|
|
using T2 = typename StatFunc::Type2;
|
|
|
|
using ColVecT1 = std::conditional_t<IsDecimalNumber<T1>, ColumnDecimal<T1>, ColumnVector<T1>>;
|
|
|
|
using ColVecT2 = std::conditional_t<IsDecimalNumber<T2>, ColumnDecimal<T2>, ColumnVector<T2>>;
|
|
|
|
using ResultType = typename StatFunc::ResultType;
|
|
|
|
using ColVecResult = ColumnVector<ResultType>;
|
|
|
|
|
2019-02-13 11:50:41 +00:00
|
|
|
AggregateFunctionVarianceSimple(const DataTypes & argument_types_)
|
|
|
|
: IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>(argument_types_, {})
|
2019-02-11 19:26:32 +00:00
|
|
|
, src_scale(0)
|
2018-09-13 18:36:47 +00:00
|
|
|
{}
|
|
|
|
|
2019-02-13 11:50:41 +00:00
|
|
|
AggregateFunctionVarianceSimple(const IDataType & data_type, const DataTypes & argument_types_)
|
|
|
|
: IAggregateFunctionDataHelper<typename StatFunc::Data, AggregateFunctionVarianceSimple<StatFunc>>(argument_types_, {})
|
2019-02-11 19:26:32 +00:00
|
|
|
, src_scale(getDecimalScale(data_type))
|
2018-09-13 18:36:47 +00:00
|
|
|
{}
|
|
|
|
|
2017-12-22 22:23:03 +00:00
|
|
|
String getName() const override
|
|
|
|
{
|
2019-05-06 03:49:14 +00:00
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
|
|
|
|
return "varPop";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
|
|
|
|
return "varSamp";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
|
|
|
|
return "stddevPop";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
|
|
|
|
return "stddevSamp";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
|
|
|
|
return "skewPop";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
|
|
|
|
return "skewSamp";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
|
|
|
|
return "kurtPop";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
|
|
|
|
return "kurtSamp";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::covarPop)
|
|
|
|
return "covarPop";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::covarSamp)
|
|
|
|
return "covarSamp";
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::corr)
|
|
|
|
return "corr";
|
2017-12-22 22:23:03 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
DataTypePtr getReturnType() const override
|
|
|
|
{
|
2017-12-22 22:59:45 +00:00
|
|
|
return std::make_shared<DataTypeNumber<ResultType>>();
|
2017-12-22 22:23:03 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
|
|
|
{
|
2018-09-13 18:36:47 +00:00
|
|
|
if constexpr (StatFunc::num_args == 2)
|
2017-12-22 22:23:03 +00:00
|
|
|
this->data(place).add(
|
2018-09-13 18:36:47 +00:00
|
|
|
static_cast<const ColVecT1 &>(*columns[0]).getData()[row_num],
|
|
|
|
static_cast<const ColVecT2 &>(*columns[1]).getData()[row_num]);
|
2017-12-22 22:23:03 +00:00
|
|
|
else
|
|
|
|
this->data(place).add(
|
2018-09-13 18:36:47 +00:00
|
|
|
static_cast<const ColVecT1 &>(*columns[0]).getData()[row_num]);
|
2017-12-22 22:23:03 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
|
|
|
{
|
|
|
|
this->data(place).merge(this->data(rhs));
|
|
|
|
}
|
|
|
|
|
|
|
|
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
|
|
|
{
|
|
|
|
this->data(place).write(buf);
|
|
|
|
}
|
|
|
|
|
|
|
|
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
|
|
|
{
|
|
|
|
this->data(place).read(buf);
|
|
|
|
}
|
|
|
|
|
|
|
|
void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override
|
|
|
|
{
|
|
|
|
const auto & data = this->data(place);
|
2018-09-13 18:36:47 +00:00
|
|
|
auto & dst = static_cast<ColVecResult &>(to).getData();
|
|
|
|
|
|
|
|
if constexpr (IsDecimalNumber<T1>)
|
|
|
|
{
|
2019-05-06 03:49:14 +00:00
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
|
|
|
|
dst.push_back(data.getPopulation(src_scale * 2));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
|
|
|
|
dst.push_back(data.getSample(src_scale * 2));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
|
|
|
|
dst.push_back(sqrt(data.getPopulation(src_scale * 2)));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
|
|
|
|
dst.push_back(sqrt(data.getSample(src_scale * 2)));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
|
|
|
|
dst.push_back(data.getMoment3(src_scale * 3) / pow(data.getPopulation(src_scale * 2), 1.5));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
|
|
|
|
dst.push_back(data.getMoment3(src_scale * 3) / pow(data.getSample(src_scale * 2), 1.5));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
|
|
|
|
dst.push_back(data.getMoment4(src_scale * 4) / pow(data.getPopulation(src_scale * 2), 2));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
|
|
|
|
dst.push_back(data.getMoment4(src_scale * 4) / pow(data.getSample(src_scale * 2), 2));
|
2018-09-13 18:36:47 +00:00
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
2019-05-06 03:49:14 +00:00
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varPop)
|
|
|
|
dst.push_back(data.getPopulation());
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::varSamp)
|
|
|
|
dst.push_back(data.getSample());
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevPop)
|
|
|
|
dst.push_back(sqrt(data.getPopulation()));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::stddevSamp)
|
|
|
|
dst.push_back(sqrt(data.getSample()));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewPop)
|
|
|
|
dst.push_back(data.getMoment3() / pow(data.getPopulation(), 1.5));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::skewSamp)
|
|
|
|
dst.push_back(data.getMoment3() / pow(data.getSample(), 1.5));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtPop)
|
|
|
|
dst.push_back(data.getMoment4() / pow(data.getPopulation(), 2));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::kurtSamp)
|
|
|
|
dst.push_back(data.getMoment4() / pow(data.getSample(), 2));
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::covarPop)
|
|
|
|
dst.push_back(data.getPopulation());
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::covarSamp)
|
|
|
|
dst.push_back(data.getSample());
|
|
|
|
if constexpr (StatFunc::kind == StatisticsFunctionKind::corr)
|
|
|
|
dst.push_back(data.get());
|
2018-09-13 18:36:47 +00:00
|
|
|
}
|
2017-12-22 22:23:03 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
const char * getHeaderFilePath() const override { return __FILE__; }
|
2018-09-13 18:36:47 +00:00
|
|
|
|
|
|
|
private:
|
|
|
|
UInt32 src_scale;
|
2017-12-22 22:23:03 +00:00
|
|
|
};
|
|
|
|
|
|
|
|
|
2019-05-06 03:49:14 +00:00
|
|
|
template <typename T> using AggregateFunctionVarPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::varPop, 2>>;
|
|
|
|
template <typename T> using AggregateFunctionVarSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::varSamp, 2>>;
|
|
|
|
template <typename T> using AggregateFunctionStddevPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::stddevPop, 2>>;
|
|
|
|
template <typename T> using AggregateFunctionStddevSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::stddevSamp, 2>>;
|
|
|
|
template <typename T> using AggregateFunctionSkewPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::skewPop, 3>>;
|
|
|
|
template <typename T> using AggregateFunctionSkewSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::skewSamp, 3>>;
|
|
|
|
template <typename T> using AggregateFunctionKurtPopSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::kurtPop, 4>>;
|
|
|
|
template <typename T> using AggregateFunctionKurtSampSimple = AggregateFunctionVarianceSimple<StatFuncOneArg<T, StatisticsFunctionKind::kurtSamp, 4>>;
|
2018-09-13 18:36:47 +00:00
|
|
|
template <typename T1, typename T2> using AggregateFunctionCovarPopSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::covarPop>>;
|
|
|
|
template <typename T1, typename T2> using AggregateFunctionCovarSampSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::covarSamp>>;
|
|
|
|
template <typename T1, typename T2> using AggregateFunctionCorrSimple = AggregateFunctionVarianceSimple<StatFuncTwoArg<T1, T2, StatisticsFunctionKind::corr>>;
|
2017-12-22 22:23:03 +00:00
|
|
|
|
|
|
|
}
|