ClickHouse/src/AggregateFunctions/ReservoirSamplerDeterministic.h
2020-11-10 21:22:26 +03:00

227 lines
6.5 KiB
C++

#pragma once
#include <limits>
#include <algorithm>
#include <climits>
#include <AggregateFunctions/ReservoirSampler.h>
#include <common/types.h>
#include <Common/HashTable/Hash.h>
#include <IO/ReadBuffer.h>
#include <IO/ReadHelpers.h>
#include <IO/WriteHelpers.h>
#include <Common/PODArray.h>
#include <Common/NaNUtils.h>
#include <Poco/Exception.h>
namespace DB
{
namespace ErrorCodes
{
extern const int LOGICAL_ERROR;
}
}
/// 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_MAX_SAMPLE_SIZE = 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 max_sample_size_ = detail::DEFAULT_MAX_SAMPLE_SIZE)
: max_sample_size{max_sample_size_}
{
}
void clear()
{
samples.clear();
sorted = false;
total_values = 0;
}
void insert(const T & v, const UInt64 determinator)
{
if (isNaN(v))
return;
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 static_cast<double>(samples[left_index].first);
const double left_coef = right_index - index;
const double right_coef = index - left_index;
return static_cast<double>(samples[left_index].first) * left_coef + static_cast<double>(samples[right_index].first) * right_coef;
}
void merge(const ReservoirSamplerDeterministic & b)
{
if (max_sample_size != b.max_sample_size)
throw Poco::Exception("Cannot merge ReservoirSamplerDeterministic's with different max sample size");
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)
{
size_t size = 0;
DB::readIntBinary<size_t>(size, buf);
DB::readIntBinary<size_t>(total_values, buf);
/// Compatibility with old versions.
if (size > total_values)
size = total_values;
samples.resize(size);
for (size_t i = 0; i < size; ++i)
DB::readPODBinary(samples[i], buf);
sorted = false;
}
void write(DB::WriteBuffer & buf) const
{
size_t size = samples.size();
DB::writeIntBinary<size_t>(size, buf);
DB::writeIntBinary<size_t>(total_values, buf);
for (size_t i = 0; i < size; ++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.
using Element = std::pair<T, UInt32>;
using Array = DB::PODArray<Element, 64>;
const size_t max_sample_size; /// Maximum amount of stored values.
size_t total_values = 0; /// How many values were inserted (regardless if they remain in sample or not).
bool sorted = false;
Array samples;
UInt8 skip_degree = 0; /// The number N determining that we save only one per 2^N elements in average.
void insertImpl(const T & v, const UInt32 hash)
{
/// Make a room for plus one element.
while (samples.size() >= max_sample_size)
{
++skip_degree;
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()
{
samples.resize(std::distance(samples.begin(),
std::remove_if(samples.begin(), samples.end(), [this](const auto & elem){ return !good(elem.second); })));
sorted = false;
}
void sortIfNeeded()
{
if (sorted)
return;
std::sort(samples.begin(), samples.end(), [](const auto & lhs, const auto & rhs) { return lhs.first < rhs.first; });
sorted = true;
}
template <typename ResultType>
ResultType onEmpty() const
{
if (OnEmpty == ReservoirSamplerDeterministicOnEmpty::THROW)
throw DB::Exception(DB::ErrorCodes::LOGICAL_ERROR, "Quantile of empty ReservoirSamplerDeterministic");
else
return NanLikeValueConstructor<ResultType, std::is_floating_point_v<ResultType>>::getValue();
}
};