ClickHouse/dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h

#pragma once

#include <limits>
#include <algorithm>
#include <climits>
#include <sstream>
#include <DB/AggregateFunctions/ReservoirSampler.h>
#include <common/Common.h>
#include <DB/Common/HashTable/Hash.h>
#include <DB/IO/ReadBuffer.h>
#include <DB/IO/ReadHelpers.h>
#include <DB/IO/WriteHelpers.h>
#include <DB/Common/PODArray.h>
#include <Poco/Exception.h>
#include <boost/random.hpp>


 /// Implementation of Reservoir Sampling algorithm. Incrementally selects from the added objects a random subset of the `sample_count` size.
 /// Can approximately get quantiles.
 /// The `quantile` call takes O(sample_count log sample_count), if after the previous call `quantile` there was at least one call to insert. Otherwise, O(1).
 /// That is, it makes sense to first add, then get quantiles without adding.


namespace DB
{
namespace ErrorCodes
{
	extern const int MEMORY_LIMIT_EXCEEDED;
}
}


namespace detail
{
const size_t DEFAULT_SAMPLE_COUNT = 8192;
const auto MAX_SKIP_DEGREE = sizeof(UInt32) * 8;
}

/// What if there is not a single value - throw an exception, or return 0 or NaN in the case of double?
enum class ReservoirSamplerDeterministicOnEmpty
{
	THROW,
	RETURN_NAN_OR_ZERO,
};

template <typename T,
	ReservoirSamplerDeterministicOnEmpty OnEmpty = ReservoirSamplerDeterministicOnEmpty::THROW>
class ReservoirSamplerDeterministic
{
	bool good(const UInt32 hash)
	{
		return hash == ((hash >> skip_degree) << skip_degree);
	}

public:
	ReservoirSamplerDeterministic(const size_t sample_count = DEFAULT_SAMPLE_COUNT)
		: sample_count{sample_count}
	{
	}

	void clear()
	{
		samples.clear();
		sorted = false;
		total_values = 0;
	}

	void insert(const T & v, const UInt64 determinator)
	{
		const UInt32 hash = intHash64(determinator);
		if (!good(hash))
			return;

		insertImpl(v, hash);
		sorted = false;
		++total_values;
	}

	size_t size() const
	{
		return total_values;
	}

	T quantileNearest(double level)
	{
		if (samples.empty())
			return onEmpty<T>();

		sortIfNeeded();

		double index = level * (samples.size() - 1);
		size_t int_index = static_cast<size_t>(index + 0.5);
		int_index = std::max(0LU, std::min(samples.size() - 1, int_index));
		return samples[int_index].first;
	}

	/** If T is not a numeric type, using this method causes a compilation error,
	  *  but use of error class does not cause. SFINAE.
	  *  Not SFINAE. Functions members of type templates are simply not checked until they are used.
	  */
	double quantileInterpolated(double level)
	{
		if (samples.empty())
			return onEmpty<double>();

		sortIfNeeded();

		const double index = std::max(0., std::min(samples.size() - 1., level * (samples.size() - 1)));

		/// To get a value from a fractional index, we linearly interpolate between adjacent values.
		size_t left_index = static_cast<size_t>(index);
		size_t right_index = left_index + 1;
		if (right_index == samples.size())
			return samples[left_index].first;

		const double left_coef = right_index - index;
		const double right_coef = index - left_index;

		return samples[left_index].first * left_coef + samples[right_index].first * right_coef;
	}

	void merge(const ReservoirSamplerDeterministic & b)
	{
		if (sample_count != b.sample_count)
			throw Poco::Exception("Cannot merge ReservoirSamplerDeterministic's with different sample_count");
		sorted = false;

		if (b.skip_degree > skip_degree)
		{
			skip_degree = b.skip_degree;
			thinOut();
		}

		for (const auto & sample : b.samples)
			if (good(sample.second))
				insertImpl(sample.first, sample.second);

		total_values += b.total_values;
	}

	void read(DB::ReadBuffer & buf)
	{
		DB::readIntBinary<size_t>(sample_count, buf);
		DB::readIntBinary<size_t>(total_values, buf);
		samples.resize(std::min(total_values, sample_count));

		for (size_t i = 0; i < samples.size(); ++i)
			DB::readPODBinary(samples[i], buf);

		sorted = false;
	}

	void write(DB::WriteBuffer & buf) const
	{
		DB::writeIntBinary<size_t>(sample_count, buf);
		DB::writeIntBinary<size_t>(total_values, buf);

		for (size_t i = 0; i < std::min(sample_count, total_values); ++i)
			DB::writePODBinary(samples[i], buf);
	}

private:
	/// We allocate some memory on the stack to avoid allocations when there are many objects with a small number of elements.
	static constexpr size_t bytes_on_stack = 64;
	using Element = std::pair<T, UInt32>;
	using Array = DB::PODArray<Element, bytes_on_stack / sizeof(Element), AllocatorWithStackMemory<Allocator<false>, bytes_on_stack>>;

	size_t sample_count;
	size_t total_values{};
	bool sorted{};
	Array samples;
	UInt8 skip_degree{};

	void insertImpl(const T & v, const UInt32 hash)
	{
		/// @todo why + 1? I don't quite recall
		while (samples.size() + 1 >= sample_count)
		{
			if (++skip_degree > detail::MAX_SKIP_DEGREE)
				throw DB::Exception{"skip_degree exceeds maximum value", DB::ErrorCodes::MEMORY_LIMIT_EXCEEDED};
			thinOut();
		}

		samples.emplace_back(v, hash);
	}

	void thinOut()
	{
		auto size = samples.size();
		for (size_t i = 0; i < size;)
		{
			if (!good(samples[i].second))
			{
				/// swap current element with the last one
				std::swap(samples[size - 1], samples[i]);
				--size;
			}
			else
				++i;
		}

		if (size != samples.size())
		{
			samples.resize(size);
			sorted = false;
		}
	}

	void sortIfNeeded()
	{
		if (sorted)
			return;
		sorted = true;
		std::sort(samples.begin(), samples.end(), [] (const std::pair<T, UInt32> & lhs, const std::pair<T, UInt32> & rhs) {
			return lhs.first < rhs.first;
		});
	}

	template <typename ResultType>
	ResultType onEmpty() const
	{
		if (OnEmpty == ReservoirSamplerDeterministicOnEmpty::THROW)
			throw Poco::Exception("Quantile of empty ReservoirSamplerDeterministic");
		else
			return NanLikeValueConstructor<ResultType, std::is_floating_point<ResultType>::value>::getValue();
	}
};