ClickHouse/src/AggregateFunctions/AggregateFunctionSum.h

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#pragma once
#include <type_traits>
#include <IO/WriteHelpers.h>
#include <IO/ReadHelpers.h>
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#include <DataTypes/DataTypesNumber.h>
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#include <DataTypes/DataTypesDecimal.h>
#include <Columns/ColumnVector.h>
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#include <AggregateFunctions/IAggregateFunction.h>
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namespace DB
{
template <typename T>
struct AggregateFunctionSumData
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{
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T sum{};
void add(T value)
{
sum += value;
}
void merge(const AggregateFunctionSumData & rhs)
{
sum += rhs.sum;
}
void write(WriteBuffer & buf) const
{
writeBinary(sum, buf);
}
void read(ReadBuffer & buf)
{
readBinary(sum, buf);
}
T get() const
{
return sum;
}
};
template <typename T>
struct AggregateFunctionSumKahanData
{
static_assert(std::is_floating_point_v<T>,
"It doesn't make sense to use Kahan Summation algorithm for non floating point types");
T sum{};
T compensation{};
void add(T value)
{
auto compensated_value = value - compensation;
auto new_sum = sum + compensated_value;
compensation = (new_sum - sum) - compensated_value;
sum = new_sum;
}
void merge(const AggregateFunctionSumKahanData & rhs)
{
auto raw_sum = sum + rhs.sum;
auto rhs_compensated = raw_sum - sum;
auto compensations = ((rhs.sum - rhs_compensated) + (sum - (raw_sum - rhs_compensated))) + compensation + rhs.compensation;
sum = raw_sum + compensations;
compensation = compensations - (sum - raw_sum);
}
void write(WriteBuffer & buf) const
{
writeBinary(sum, buf);
writeBinary(compensation, buf);
}
void read(ReadBuffer & buf)
{
readBinary(sum, buf);
readBinary(compensation, buf);
}
T get() const
{
return sum;
}
};
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enum AggregateFunctionSumType
{
AggregateFunctionTypeSum,
AggregateFunctionTypeSumWithOverflow,
AggregateFunctionTypeSumKahan,
};
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/// Counts the sum of the numbers.
template <typename T, typename TResult, typename Data, AggregateFunctionSumType Type>
class AggregateFunctionSum final : public IAggregateFunctionDataHelper<Data, AggregateFunctionSum<T, TResult, Data, Type>>
{
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public:
using ResultDataType = std::conditional_t<IsDecimalNumber<T>, DataTypeDecimal<TResult>, DataTypeNumber<TResult>>;
using ColVecType = std::conditional_t<IsDecimalNumber<T>, ColumnDecimal<T>, ColumnVector<T>>;
using ColVecResult = std::conditional_t<IsDecimalNumber<T>, ColumnDecimal<TResult>, ColumnVector<TResult>>;
String getName() const override
{
if constexpr (Type == AggregateFunctionTypeSum)
return "sum";
else if constexpr (Type == AggregateFunctionTypeSumWithOverflow)
return "sumWithOverflow";
else if constexpr (Type == AggregateFunctionTypeSumKahan)
return "sumKahan";
__builtin_unreachable();
}
AggregateFunctionSum(const DataTypes & argument_types_)
: IAggregateFunctionDataHelper<Data, AggregateFunctionSum<T, TResult, Data, Type>>(argument_types_, {})
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, scale(0)
{}
AggregateFunctionSum(const IDataType & data_type, const DataTypes & argument_types_)
: IAggregateFunctionDataHelper<Data, AggregateFunctionSum<T, TResult, Data, Type>>(argument_types_, {})
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, scale(getDecimalScale(data_type))
{}
DataTypePtr getReturnType() const override
{
if constexpr (IsDecimalNumber<T>)
return std::make_shared<ResultDataType>(ResultDataType::maxPrecision(), scale);
else
return std::make_shared<ResultDataType>();
}
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
{
const auto & column = static_cast<const ColVecType &>(*columns[0]);
this->data(place).add(column.getData()[row_num]);
}
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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
{
auto & column = static_cast<ColVecResult &>(to);
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column.getData().push_back(this->data(place).get());
}
private:
UInt32 scale;
};
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}