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70d1adfe4b
* save format string for NetException * format exceptions * format exceptions 2 * format exceptions 3 * format exceptions 4 * format exceptions 5 * format exceptions 6 * fix * format exceptions 7 * format exceptions 8 * Update MergeTreeIndexGin.cpp * Update AggregateFunctionMap.cpp * Update AggregateFunctionMap.cpp * fix
103 lines
2.9 KiB
C++
103 lines
2.9 KiB
C++
#pragma once
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#include <AggregateFunctions/ReservoirSampler.h>
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namespace DB
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{
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struct Settings;
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namespace ErrorCodes
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{
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extern const int NOT_IMPLEMENTED;
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}
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/** Quantile calculation with "reservoir sample" algorithm.
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* It collects pseudorandom subset of limited size from a stream of values,
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* and approximate quantile from it.
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* The result is non-deterministic. Also look at QuantileReservoirSamplerDeterministic.
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*
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* This algorithm is quite inefficient in terms of precision for memory usage,
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* but very efficient in CPU (though less efficient than QuantileTiming and than QuantileExact for small sets).
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*/
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template <typename Value>
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struct QuantileReservoirSampler
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{
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using Data = ReservoirSampler<Value, ReservoirSamplerOnEmpty::RETURN_NAN_OR_ZERO>;
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Data data;
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void add(const Value & x)
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{
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data.insert(x);
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}
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template <typename Weight>
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void add(const Value &, const Weight &)
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{
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throw Exception(ErrorCodes::NOT_IMPLEMENTED, "Method add with weight is not implemented for ReservoirSampler");
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}
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void merge(const QuantileReservoirSampler & rhs)
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{
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data.merge(rhs.data);
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}
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void serialize(WriteBuffer & buf) const
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{
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data.write(buf);
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}
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void deserialize(ReadBuffer & buf)
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{
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data.read(buf);
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}
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/// Get the value of the `level` quantile. The level must be between 0 and 1.
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Value get(Float64 level)
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{
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if (data.empty())
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return {};
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if constexpr (is_decimal<Value>)
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return Value(static_cast<typename Value::NativeType>(data.quantileInterpolated(level)));
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else
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return static_cast<Value>(data.quantileInterpolated(level));
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}
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/// Get the `size` values of `levels` quantiles. Write `size` results starting with `result` address.
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/// indices - an array of index levels such that the corresponding elements will go in ascending order.
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void getMany(const Float64 * levels, const size_t * indices, size_t size, Value * result)
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{
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bool is_empty = data.empty();
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for (size_t i = 0; i < size; ++i)
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{
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if (is_empty)
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{
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result[i] = Value{};
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}
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else
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{
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if constexpr (is_decimal<Value>)
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result[indices[i]] = Value(static_cast<typename Value::NativeType>(data.quantileInterpolated(levels[indices[i]])));
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else
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result[indices[i]] = Value(data.quantileInterpolated(levels[indices[i]]));
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}
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}
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}
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/// The same, but in the case of an empty state, NaN is returned.
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Float64 getFloat(Float64 level)
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{
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return data.quantileInterpolated(level);
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}
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void getManyFloat(const Float64 * levels, const size_t * indices, size_t size, Float64 * result)
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{
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for (size_t i = 0; i < size; ++i)
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result[indices[i]] = data.quantileInterpolated(levels[indices[i]]);
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}
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};
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}
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