2015-11-15 03:11:24 +00:00
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#pragma once
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#include <DB/Common/PODArray.h>
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#include <DB/IO/WriteHelpers.h>
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#include <DB/IO/ReadHelpers.h>
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#include <DB/DataTypes/DataTypesNumberFixed.h>
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#include <DB/DataTypes/DataTypeArray.h>
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#include <DB/AggregateFunctions/IUnaryAggregateFunction.h>
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2015-11-23 21:33:43 +00:00
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#include <DB/AggregateFunctions/QuantilesCommon.h>
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2015-11-15 03:11:24 +00:00
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#include <DB/Columns/ColumnArray.h>
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namespace DB
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{
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/** В качестве состояния используется массив, в который складываются все значения.
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* NOTE Если различных значений мало, то это не оптимально.
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* Для 8 и 16-битных значений возможно, было бы лучше использовать lookup-таблицу.
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*/
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template <typename T>
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struct AggregateFunctionQuantileExactData
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{
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2015-11-15 03:20:29 +00:00
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/// Сразу будет выделена память на несколько элементов так, чтобы состояние занимало 64 байта.
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static constexpr size_t bytes_in_arena = 64 - sizeof(PODArray<T>);
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2016-04-15 16:07:58 +00:00
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using Array = PODArray<T, bytes_in_arena, AllocatorWithStackMemory<Allocator<false>, bytes_in_arena>>;
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2015-11-15 03:11:24 +00:00
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Array array;
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};
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/** Точно вычисляет квантиль.
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* В качестве типа аргумента может быть только числовой тип (в том числе, дата и дата-с-временем).
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* Тип результата совпадает с типом аргумента.
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*/
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template <typename T>
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class AggregateFunctionQuantileExact final
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: public IUnaryAggregateFunction<AggregateFunctionQuantileExactData<T>, AggregateFunctionQuantileExact<T>>
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{
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private:
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double level;
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DataTypePtr type;
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public:
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AggregateFunctionQuantileExact(double level_ = 0.5) : level(level_) {}
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String getName() const override { return "quantileExact"; }
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DataTypePtr getReturnType() const override
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{
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return type;
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}
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2015-11-15 08:31:08 +00:00
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void setArgument(const DataTypePtr & argument)
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{
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type = argument;
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}
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void setParameters(const Array & params) override
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{
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if (params.size() != 1)
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throw Exception("Aggregate function " + getName() + " requires exactly one parameter.", ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH);
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level = apply_visitor(FieldVisitorConvertToNumber<Float64>(), params[0]);
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}
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2016-09-19 22:30:40 +00:00
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void addImpl(AggregateDataPtr place, const IColumn & column, size_t row_num, Arena *) const
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{
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this->data(place).array.push_back(static_cast<const ColumnVector<T> &>(column).getData()[row_num]);
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}
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2016-09-23 23:33:17 +00:00
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void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
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{
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this->data(place).array.insert(this->data(rhs).array.begin(), this->data(rhs).array.end());
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}
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void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
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{
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const auto & array = this->data(place).array;
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size_t size = array.size();
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writeVarUInt(size, buf);
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buf.write(reinterpret_cast<const char *>(&array[0]), size * sizeof(array[0]));
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}
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2016-09-22 23:26:08 +00:00
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void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
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2015-11-15 03:11:24 +00:00
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{
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auto & array = this->data(place).array;
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size_t size = 0;
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readVarUInt(size, buf);
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array.resize(size);
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buf.read(reinterpret_cast<char *>(&array[0]), size * sizeof(array[0]));
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2015-11-15 03:11:24 +00:00
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}
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void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override
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{
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/// Сортировка массива не будет считаться нарушением константности.
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auto & array = const_cast<typename AggregateFunctionQuantileExactData<T>::Array &>(this->data(place).array);
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T quantile = T();
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if (!array.empty())
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{
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size_t n = level < 1
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? level * array.size()
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: (array.size() - 1);
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std::nth_element(array.begin(), array.begin() + n, array.end()); /// NOTE Можно придумать алгоритм radix-select.
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quantile = array[n];
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}
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static_cast<ColumnVector<T> &>(to).getData().push_back(quantile);
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}
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};
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/** То же самое, но позволяет вычислить сразу несколько квантилей.
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* Для этого, принимает в качестве параметров несколько уровней. Пример: quantilesExact(0.5, 0.8, 0.9, 0.95)(ConnectTiming).
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* Возвращает массив результатов.
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*/
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template <typename T>
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class AggregateFunctionQuantilesExact final
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: public IUnaryAggregateFunction<AggregateFunctionQuantileExactData<T>, AggregateFunctionQuantilesExact<T>>
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{
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private:
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QuantileLevels<double> levels;
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DataTypePtr type;
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public:
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String getName() const override { return "quantilesExact"; }
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DataTypePtr getReturnType() const override
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{
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2016-05-28 07:48:40 +00:00
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return std::make_shared<DataTypeArray>(type);
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2015-11-15 03:11:24 +00:00
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}
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2015-11-15 08:31:08 +00:00
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void setArgument(const DataTypePtr & argument)
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{
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type = argument;
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}
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void setParameters(const Array & params) override
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{
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levels.set(params);
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2015-11-15 03:11:24 +00:00
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}
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2016-09-19 22:30:40 +00:00
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void addImpl(AggregateDataPtr place, const IColumn & column, size_t row_num, Arena *) const
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{
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this->data(place).array.push_back(static_cast<const ColumnVector<T> &>(column).getData()[row_num]);
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}
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2016-09-23 23:33:17 +00:00
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void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
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{
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this->data(place).array.insert(this->data(rhs).array.begin(), this->data(rhs).array.end());
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}
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void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
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{
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const auto & array = this->data(place).array;
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size_t size = array.size();
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writeVarUInt(size, buf);
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buf.write(reinterpret_cast<const char *>(&array[0]), size * sizeof(array[0]));
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}
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2016-09-22 23:26:08 +00:00
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void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
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2015-11-15 03:11:24 +00:00
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{
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auto & array = this->data(place).array;
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size_t size = 0;
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readVarUInt(size, buf);
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array.resize(size);
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buf.read(reinterpret_cast<char *>(&array[0]), size * sizeof(array[0]));
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}
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void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override
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{
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/// Сортировка массива не будет считаться нарушением константности.
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auto & array = const_cast<typename AggregateFunctionQuantileExactData<T>::Array &>(this->data(place).array);
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ColumnArray & arr_to = static_cast<ColumnArray &>(to);
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ColumnArray::Offsets_t & offsets_to = arr_to.getOffsets();
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size_t num_levels = levels.size();
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offsets_to.push_back((offsets_to.size() == 0 ? 0 : offsets_to.back()) + num_levels);
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typename ColumnVector<T>::Container_t & data_to = static_cast<ColumnVector<T> &>(arr_to.getData()).getData();
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size_t old_size = data_to.size();
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data_to.resize(old_size + num_levels);
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2015-11-15 03:11:24 +00:00
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if (!array.empty())
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{
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size_t prev_n = 0;
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for (auto level_index : levels.permutation)
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{
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auto level = levels.levels[level_index];
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2015-11-15 03:11:24 +00:00
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size_t n = level < 1
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? level * array.size()
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: (array.size() - 1);
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std::nth_element(array.begin() + prev_n, array.begin() + n, array.end());
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2015-11-23 21:33:43 +00:00
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data_to[old_size + level_index] = array[n];
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prev_n = n;
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}
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}
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else
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{
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for (size_t i = 0; i < num_levels; ++i)
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data_to[old_size + i] = T();
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}
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}
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};
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}
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