ClickHouse/src/AggregateFunctions/AggregateFunctionRankCorrelation.h

#pragma once

#include <AggregateFunctions/IAggregateFunction.h>
#include <AggregateFunctions/StatCommon.h>
#include <Columns/ColumnArray.h>
#include <Columns/ColumnVector.h>
#include <Columns/ColumnTuple.h>
#include <Common/assert_cast.h>
#include <Common/PODArray_fwd.h>
#include <common/types.h>
#include <DataTypes/DataTypesDecimal.h>
#include <DataTypes/DataTypeNullable.h>
#include <DataTypes/DataTypesNumber.h>
#include <DataTypes/DataTypeTuple.h>
#include <DataTypes/DataTypeArray.h>

#include <Common/ArenaAllocator.h>

namespace DB
{


struct RankCorrelationData : public StatisticalSample<Float64, Float64>
{
    Float64 getResult()
    {
        RanksArray ranks_x;
        std::tie(ranks_x, std::ignore) = computeRanksAndTieCorrection(this->x);

        RanksArray ranks_y;
        std::tie(ranks_y, std::ignore) = computeRanksAndTieCorrection(this->y);

        /// In our case sizes of both samples are equal.
        const auto size = this->size_x;

        /// Count d^2 sum
        Float64 answer = 0;
        for (size_t j = 0; j < size; ++j)
            answer += (ranks_x[j] - ranks_y[j]) * (ranks_x[j] - ranks_y[j]);

        answer *= 6;
        answer /= size * (size * size - 1);
        answer = 1 - answer;
        return answer;
    }
};

class AggregateFunctionRankCorrelation :
    public IAggregateFunctionDataHelper<RankCorrelationData, AggregateFunctionRankCorrelation>
{
public:
    explicit AggregateFunctionRankCorrelation(const DataTypes & arguments)
        :IAggregateFunctionDataHelper<RankCorrelationData, AggregateFunctionRankCorrelation> ({arguments}, {})
    {}

    String getName() const override
    {
        return "rankCorr";
    }

    DataTypePtr getReturnType() const override
    {
        return std::make_shared<DataTypeNumber<Float64>>();
    }

    void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
    {
        Float64 new_x = columns[0]->getFloat64(row_num);
        Float64 new_y = columns[1]->getFloat64(row_num);
        this->data(place).addX(new_x, arena);
        this->data(place).addY(new_y, arena);
    }

    void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
    {
        auto & a = this->data(place);
        auto & b = this->data(rhs);

        a.merge(b, arena);
    }

    void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
    {
        this->data(place).write(buf);
    }

    void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
    {
        this->data(place).read(buf, arena);
    }

    void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
    {
        auto answer = this->data(place).getResult();

        auto & column = static_cast<ColumnVector<Float64> &>(to);
        column.getData().push_back(answer);
    }

};

};