#pragma once #include #include #include #include #include #include #include #include namespace DB { /** The state is an array, into which all values are added. * NOTE If there are few different values then this is not optimal. * For 8 and 16-bit values it might be better to use a lookup table. */ template struct AggregateFunctionQuantileExactData { /// The memory will be allocated to several elements at once, so that the state occupies 64 bytes. static constexpr size_t bytes_in_arena = 64 - sizeof(PODArray); using Array = PODArray, bytes_in_arena>>; Array array; }; /** Exactly calculates the quantile. * The argument type can only be a numeric type (including date and date-time). * The result type is the same as the argument type. */ template class AggregateFunctionQuantileExact final : public IUnaryAggregateFunction, AggregateFunctionQuantileExact> { private: double level; DataTypePtr type; public: AggregateFunctionQuantileExact(double level_ = 0.5) : level(level_) {} String getName() const override { return "quantileExact"; } DataTypePtr getReturnType() const override { return type; } void setArgument(const DataTypePtr & argument) { type = argument; } void setParameters(const Array & params) override { if (params.size() != 1) throw Exception("Aggregate function " + getName() + " requires exactly one parameter.", ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH); level = applyVisitor(FieldVisitorConvertToNumber(), params[0]); } void addImpl(AggregateDataPtr place, const IColumn & column, size_t row_num, Arena *) const { this->data(place).array.push_back(static_cast &>(column).getData()[row_num]); } void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override { this->data(place).array.insert(this->data(rhs).array.begin(), this->data(rhs).array.end()); } void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override { const auto & array = this->data(place).array; size_t size = array.size(); writeVarUInt(size, buf); buf.write(reinterpret_cast(&array[0]), size * sizeof(array[0])); } void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override { auto & array = this->data(place).array; size_t size = 0; readVarUInt(size, buf); array.resize(size); buf.read(reinterpret_cast(&array[0]), size * sizeof(array[0])); } void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override { /// Sorting an array will not be considered a violation of constancy. auto & array = const_cast::Array &>(this->data(place).array); T quantile = T(); if (!array.empty()) { size_t n = level < 1 ? level * array.size() : (array.size() - 1); std::nth_element(array.begin(), array.begin() + n, array.end()); /// NOTE You can think of the radix-select algorithm. quantile = array[n]; } static_cast &>(to).getData().push_back(quantile); } const char * getHeaderFilePath() const override { return __FILE__; } }; /** The same, but allows you to calculate several quantiles at once. * To do this, takes several levels as parameters. Example: quantilesExact(0.5, 0.8, 0.9, 0.95)(ConnectTiming). * Returns an array of results. */ template class AggregateFunctionQuantilesExact final : public IUnaryAggregateFunction, AggregateFunctionQuantilesExact> { private: QuantileLevels levels; DataTypePtr type; public: String getName() const override { return "quantilesExact"; } DataTypePtr getReturnType() const override { return std::make_shared(type); } void setArgument(const DataTypePtr & argument) { type = argument; } void setParameters(const Array & params) override { levels.set(params); } void addImpl(AggregateDataPtr place, const IColumn & column, size_t row_num, Arena *) const { this->data(place).array.push_back(static_cast &>(column).getData()[row_num]); } void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override { this->data(place).array.insert(this->data(rhs).array.begin(), this->data(rhs).array.end()); } void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override { const auto & array = this->data(place).array; size_t size = array.size(); writeVarUInt(size, buf); buf.write(reinterpret_cast(&array[0]), size * sizeof(array[0])); } void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override { auto & array = this->data(place).array; size_t size = 0; readVarUInt(size, buf); array.resize(size); buf.read(reinterpret_cast(&array[0]), size * sizeof(array[0])); } void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override { /// Sorting an array will not be considered a violation of constancy. auto & array = const_cast::Array &>(this->data(place).array); ColumnArray & arr_to = static_cast(to); ColumnArray::Offsets_t & offsets_to = arr_to.getOffsets(); size_t num_levels = levels.size(); offsets_to.push_back((offsets_to.size() == 0 ? 0 : offsets_to.back()) + num_levels); typename ColumnVector::Container_t & data_to = static_cast &>(arr_to.getData()).getData(); size_t old_size = data_to.size(); data_to.resize(old_size + num_levels); if (!array.empty()) { size_t prev_n = 0; for (auto level_index : levels.permutation) { auto level = levels.levels[level_index]; size_t n = level < 1 ? level * array.size() : (array.size() - 1); std::nth_element(array.begin() + prev_n, array.begin() + n, array.end()); data_to[old_size + level_index] = array[n]; prev_n = n; } } else { for (size_t i = 0; i < num_levels; ++i) data_to[old_size + i] = T(); } } const char * getHeaderFilePath() const override { return __FILE__; } }; }