ClickHouse/src/AggregateFunctions/AggregateFunctionSparkbar.h

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#pragma once
#include <DataTypes/DataTypeString.h>
#include <AggregateFunctions/IAggregateFunction.h>
#include <common/range.h>
#include <IO/ReadHelpers.h>
#include <IO/WriteHelpers.h>
#include <Columns/ColumnString.h>
#include <common/logger_useful.h>
#include <IO/ReadBufferFromString.h>
#include <Common/HashTable/HashMap.h>
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namespace DB
{
template<typename X, typename Y>
struct AggregateFunctionSparkbarData
{
using Points = HashMap<X, Y>;
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Points points;
X min_x = std::numeric_limits<X>::max();
X max_x = std::numeric_limits<X>::lowest();
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Y min_y = std::numeric_limits<Y>::max();
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Y max_y = std::numeric_limits<Y>::lowest();
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void insert(const X & x, const Y & y)
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{
auto result = points.insert({x, y});
if (!result.second)
result.first->getMapped() += y;
}
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void add(X x, Y y)
{
insert(x, y);
min_x = std::min(x, min_x);
max_x = std::max(x, max_x);
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min_y = std::min(y, min_y);
max_y = std::max(y, max_y);
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}
void merge(const AggregateFunctionSparkbarData & other)
{
if (other.points.empty())
return;
for (auto & point : other.points)
insert(point.getKey(), point.getMapped());
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min_x = std::min(other.min_x, min_x);
max_x = std::max(other.max_x, max_x);
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min_y = std::min(other.min_y, min_y);
max_y = std::max(other.max_y, max_y);
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}
void serialize(WriteBuffer & buf) const
{
writeBinary(min_x, buf);
writeBinary(max_x, buf);
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writeBinary(min_y, buf);
writeBinary(max_y, buf);
writeVarUInt(points.size(), buf);
for (const auto & elem : points)
{
writeBinary(elem.getKey(), buf);
writeBinary(elem.getMapped(), buf);
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}
}
void deserialize(ReadBuffer & buf)
{
readBinary(min_x, buf);
readBinary(max_x, buf);
readBinary(min_y, buf);
readBinary(max_y, buf);
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size_t size;
readVarUInt(size, buf);
/// TODO Protection against huge size
X x;
Y y;
for (size_t i = 0; i < size; ++i)
{
readBinary(x, buf);
readBinary(y, buf);
insert(x, y);
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}
}
};
template<typename X, typename Y>
class AggregateFunctionSparkbar final
: public IAggregateFunctionDataHelper<AggregateFunctionSparkbarData<X, Y>, AggregateFunctionSparkbar<X, Y>>
{
private:
size_t width;
X min_x;
X max_x;
String getBar(const UInt8 value) const
{
// ▁▂▃▄▅▆▇█
switch (value)
{
case 1: return "";
case 2: return "";
case 3: return "";
case 4: return "";
case 5: return "";
case 6: return "";
case 7: return "";
case 8: return "";
}
return " ";
}
/**
* The minimum value of y is rendered as the lowest height "",
* the maximum value of y is rendered as the highest height "", and the middle value will be rendered proportionally.
* If a bucket has no y value, it will be rendered as " ".
* If the actual number of buckets is greater than the specified bucket, it will be compressed by width.
* For example, there are actually 11 buckets, specify 10 buckets, and divide the 11 buckets as follows (11/10):
* 0.0-1.1, 1.1-2.2, 2.2-3.3, 3.3-4.4, 4.4-5.5, 5.5-6.6, 6.6-7.7, 7.7-8.8, 8.8-9.9, 9.9-11.
* The y value of the first bucket will be calculated as follows:
* the actual y value of the first position + the actual second position y*0.1, and the remaining y*0.9 is reserved for the next bucket.
* The next bucket will use the last y*0.9 + the actual third position y*0.2, and the remaining y*0.8 will be reserved for the next bucket. And so on.
*/
String render(const AggregateFunctionSparkbarData<X, Y> & data) const
{
String value;
if (data.points.empty() || !width)
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return value;
X local_min_x = data.min_x;
X local_max_x = data.max_x;
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size_t diff_x = local_max_x - local_min_x;
if ((diff_x + 1) <= width)
{
Y min_y = data.min_y;
Y max_y = data.max_y;
Float64 diff_y = max_y - min_y;
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if (diff_y)
{
for (size_t i = 0; i <= diff_x; ++i)
{
auto it = data.points.find(local_min_x + i);
bool found = it != data.points.end();
value += getBar(found ? std::round(((it->getMapped() - min_y) / diff_y) * 7) + 1 : 0);
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}
}
else
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{
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for (size_t i = 0; i <= diff_x; ++i)
value += getBar(data.points.has(local_min_x + i) ? 1 : 0);
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}
}
else
{
// begin reshapes to width buckets
Float64 multiple_d = (diff_x + 1) / static_cast<Float64>(width);
std::optional<Float64> min_y;
std::optional<Float64> max_y;
std::optional<Float64> new_y;
std::map<size_t, std::optional<Float64>> newPoints;
std::pair<size_t, Float64> bound{0, 0.0};
size_t cur_bucket_num = 0;
// upper bound for bucket
auto upperBound = [&](size_t bucket_num)
{
bound.second = (bucket_num + 1) * multiple_d;
bound.first = std::floor(bound.second);
};
upperBound(cur_bucket_num);
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for (size_t i = 0; i <= (diff_x + 1); ++i)
{
if (i == bound.first) // is bound
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{
Float64 proportion = bound.second - bound.first;
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auto it = data.points.find(local_min_x + i);
bool found = (it != data.points.end());
if (found)
new_y = new_y.value_or(0) + it->getMapped() * proportion;
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if (new_y)
{
Float64 avg_y = new_y.value() / multiple_d;
newPoints.template emplace(cur_bucket_num, avg_y);
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if (!min_y || avg_y < min_y)
min_y = avg_y;
if (!max_y || avg_y > max_y)
max_y = avg_y;
}
else
{
newPoints.template emplace(cur_bucket_num, std::optional<Float64>());
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}
// next bucket
new_y = found ? ((1 - proportion) * it->getMapped()) : std::optional<Float64>();
upperBound(++cur_bucket_num);
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}
else
{
auto it = data.points.find(local_min_x + i);
if (it != data.points.end())
new_y = new_y.value_or(0) + it->getMapped();
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}
}
if (!min_y || !max_y)
return {};
Float64 diff_y = max_y.value() - min_y.value();
auto getBars = [&] (const std::pair<size_t, std::optional<Float64>> & point)
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{
value += getBar(point.second ? std::round(((point.second.value() - min_y.value()) / diff_y) * 7) + 1 : 0);
};
auto getBarsForConstant = [&] (const std::pair<size_t, std::optional<Float64>> & point)
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{
value += getBar(point.second ? 1 : 0);
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};
if (diff_y)
std::for_each(newPoints.begin(), newPoints.end(), getBars);
else
std::for_each(newPoints.begin(), newPoints.end(), getBarsForConstant);
}
return value;
}
public:
AggregateFunctionSparkbar(const DataTypes & arguments, const Array & params)
: IAggregateFunctionDataHelper<AggregateFunctionSparkbarData<X, Y>, AggregateFunctionSparkbar>(
arguments, params)
{
width = params.at(0).safeGet<UInt64>();
if (params.size() == 3)
{
min_x = params.at(1).safeGet<X>();
max_x = params.at(2).safeGet<X>();
}
else
{
min_x = std::numeric_limits<X>::min();
max_x = std::numeric_limits<X>::max();
}
}
String getName() const override
{
return "sparkbar";
}
DataTypePtr getReturnType() const override
{
return std::make_shared<DataTypeString>();
}
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * /*arena*/) const override
{
X x = assert_cast<const ColumnVector<X> *>(columns[0])->getData()[row_num];
if (min_x <= x && x <= max_x)
{
Y y = assert_cast<const ColumnVector<Y> *>(columns[1])->getData()[row_num];
this->data(place).add(x, y);
}
}
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * /*arena*/) const override
{
this->data(place).merge(this->data(rhs));
}
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
{
this->data(place).serialize(buf);
}
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
{
this->data(place).deserialize(buf);
}
bool allocatesMemoryInArena() const override { return false; }
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena * /*arena*/) const override
{
auto & to_column = assert_cast<ColumnString &>(to);
const auto & data = this->data(place);
const String & value = render(data);
to_column.insertData(value.data(), value.size());
}
};
}