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@ -0,0 +1,77 @@
---
slug: /en/sql-reference/aggregate-functions/reference/quantileExactWeightedInterpolated
sidebar_position: 176
---
# quantileExactWeightedInterpolated
Computes [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence using linear interpolation, taking into account the weight of each element.
To get the interpolated value, all the passed values are combined into an array, which are then sorted by their corresponding weights. Quantile interpolation is then performed using the [weighted percentile method](https://en.wikipedia.org/wiki/Percentile#The_weighted_percentile_method) by building a cumulative distribution based on weights and then a linear interpolation is performed using the weights and the values to compute the quantiles.
When using multiple `quantile*` functions with different levels in a query, the internal states are not combined (that is, the query works less efficiently than it could). In this case, use the [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles) function.
We strongly recommend using `quantileExactWeightedInterpolated` instead of `quantileInterpolatedWeighted` because `quantileExactWeightedInterpolated` is more accurate than `quantileInterpolatedWeighted`. Here is an example:
``` sql
SELECT
quantileExactWeightedInterpolated(0.99)(number, 1),
quantile(0.99)(number),
quantileInterpolatedWeighted(0.99)(number, 1)
FROM numbers(9)
┌─quantileExactWeightedInterpolated(0.99)(number, 1)─┬─quantile(0.99)(number)─┬─quantileInterpolatedWeighted(0.99)(number, 1)─┐
│ 7.92 │ 7.92 │ 8 │
└────────────────────────────────────────────────────┴────────────────────────┴───────────────────────────────────────────────┘
```
**Syntax**
``` sql
quantileExactWeightedInterpolated(level)(expr, weight)
```
Alias: `medianExactWeightedInterpolated`.
**Arguments**
- `level` — Level of quantile. Optional parameter. Constant floating-point number from 0 to 1. We recommend using a `level` value in the range of `[0.01, 0.99]`. Default value: 0.5. At `level=0.5` the function calculates [median](https://en.wikipedia.org/wiki/Median).
- `expr` — Expression over the column values resulting in numeric [data types](../../../sql-reference/data-types/index.md#data_types), [Date](../../../sql-reference/data-types/date.md) or [DateTime](../../../sql-reference/data-types/datetime.md).
- `weight` — Column with weights of sequence members. Weight is a number of value occurrences.
**Returned value**
- Quantile of the specified level.
Type:
- [Float64](../../../sql-reference/data-types/float.md) for numeric data type input.
- [Date](../../../sql-reference/data-types/date.md) if input values have the `Date` type.
- [DateTime](../../../sql-reference/data-types/datetime.md) if input values have the `DateTime` type.
**Example**
Input table:
``` text
┌─n─┬─val─┐
│ 0 │ 3 │
│ 1 │ 2 │
│ 2 │ 1 │
│ 5 │ 4 │
└───┴─────┘
```
Result:
``` text
┌─quantileExactWeightedInterpolated(n, val)─┐
│ 1.5 │
└───────────────────────────────────────────┘
```
**See Also**
- [median](../../../sql-reference/aggregate-functions/reference/median.md#median)
- [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles)

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@ -9,7 +9,7 @@ sidebar_position: 177
Syntax: `quantiles(level1, level2, ...)(x)`
All the quantile functions also have corresponding quantiles functions: `quantiles`, `quantilesDeterministic`, `quantilesTiming`, `quantilesTimingWeighted`, `quantilesExact`, `quantilesExactWeighted`, `quantileInterpolatedWeighted`, `quantilesTDigest`, `quantilesBFloat16`, `quantilesDD`. These functions calculate all the quantiles of the listed levels in one pass, and return an array of the resulting values.
All the quantile functions also have corresponding quantiles functions: `quantiles`, `quantilesDeterministic`, `quantilesTiming`, `quantilesTimingWeighted`, `quantilesExact`, `quantilesExactWeighted`, `quantileExactWeightedInterpolated`, `quantileInterpolatedWeighted`, `quantilesTDigest`, `quantilesBFloat16`, `quantilesDD`. These functions calculate all the quantiles of the listed levels in one pass, and return an array of the resulting values.
## quantilesExactExclusive

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@ -312,6 +312,9 @@ struct NameQuantilesExactInclusive { static constexpr auto name = "quantilesExac
struct NameQuantileExactWeighted { static constexpr auto name = "quantileExactWeighted"; };
struct NameQuantilesExactWeighted { static constexpr auto name = "quantilesExactWeighted"; };
struct NameQuantileExactWeightedInterpolated { static constexpr auto name = "quantileExactWeightedInterpolated"; };
struct NameQuantilesExactWeightedInterpolated { static constexpr auto name = "quantilesExactWeightedInterpolated"; };
struct NameQuantileInterpolatedWeighted { static constexpr auto name = "quantileInterpolatedWeighted"; };
struct NameQuantilesInterpolatedWeighted { static constexpr auto name = "quantilesInterpolatedWeighted"; };

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@ -29,7 +29,7 @@ namespace
* It uses O(distinct(N)) memory. Can be naturally applied for values with weight.
* In case of many identical values, it can be more efficient than QuantileExact even when weight is not used.
*/
template <typename Value>
template <typename Value, bool interpolated>
struct QuantileExactWeighted
{
struct Int128Hash
@ -46,6 +46,7 @@ struct QuantileExactWeighted
/// When creating, the hash table must be small.
using Map = HashMapWithStackMemory<UnderlyingType, Weight, Hasher, 4>;
using Pair = typename Map::value_type;
Map map;
@ -85,6 +86,42 @@ struct QuantileExactWeighted
/// Get the value of the `level` quantile. The level must be between 0 and 1.
Value get(Float64 level) const
{
if constexpr (interpolated)
return getInterpolatedImpl(level);
else
return getImpl(level);
}
/// Get the `size` values of `levels` quantiles. Write `size` results starting with `result` address.
/// indices - an array of index levels such that the corresponding elements will go in ascending order.
void getMany(const Float64 * levels, const size_t * indices, size_t num_levels, Value * result) const
{
if constexpr (interpolated)
getManyInterpolatedImpl(levels, indices, num_levels, result);
else
getManyImpl(levels, indices, num_levels, result);
}
Float64 getFloat(Float64 level) const
{
if constexpr (interpolated)
return getFloatInterpolatedImpl(level);
else
return getFloatImpl(level);
}
void getManyFloat(const Float64 * levels, const size_t * indices, size_t num_levels, Float64 * result) const
{
if constexpr (interpolated)
getManyFloatInterpolatedImpl(levels, indices, num_levels, result);
else
getManyFloatImpl(levels, indices, num_levels, result);
}
private:
/// get implementation without interpolation
Value getImpl(Float64 level) const
{
size_t size = map.size();
@ -92,7 +129,6 @@ struct QuantileExactWeighted
return std::numeric_limits<Value>::quiet_NaN();
/// Copy the data to a temporary array to get the element you need in order.
using Pair = typename Map::value_type;
std::unique_ptr<Pair[]> array_holder(new Pair[size]);
Pair * array = array_holder.get();
@ -135,9 +171,8 @@ struct QuantileExactWeighted
return it->first;
}
/// Get the `size` values of `levels` quantiles. Write `size` results starting with `result` address.
/// indices - an array of index levels such that the corresponding elements will go in ascending order.
void getMany(const Float64 * levels, const size_t * indices, size_t num_levels, Value * result) const
/// getMany implementation without interpolation
void getManyImpl(const Float64 * levels, const size_t * indices, size_t num_levels, Value * result) const
{
size_t size = map.size();
@ -149,7 +184,6 @@ struct QuantileExactWeighted
}
/// Copy the data to a temporary array to get the element you need in order.
using Pair = typename Map::value_type;
std::unique_ptr<Pair[]> array_holder(new Pair[size]);
Pair * array = array_holder.get();
@ -197,23 +231,167 @@ struct QuantileExactWeighted
}
}
/// The same, but in the case of an empty state, NaN is returned.
Float64 getFloat(Float64) const
/// getFloat implementation without interpolation
Float64 getFloatImpl(Float64) const
{
throw Exception(ErrorCodes::NOT_IMPLEMENTED, "Method getFloat is not implemented for QuantileExact");
}
void getManyFloat(const Float64 *, const size_t *, size_t, Float64 *) const
/// getManyFloat implementation without interpolation
void getManyFloatImpl(const Float64 *, const size_t *, size_t, Float64 *) const
{
throw Exception(ErrorCodes::NOT_IMPLEMENTED, "Method getManyFloat is not implemented for QuantileExact");
}
/// get implementation with interpolation
Value getInterpolatedImpl(Float64 level) const
{
size_t size = map.size();
if (0 == size)
return std::numeric_limits<Value>::quiet_NaN();
Float64 res = getFloatInterpolatedImpl(level);
if constexpr (is_decimal<Value>)
return Value(static_cast<typename Value::NativeType>(res));
else
return static_cast<Value>(res);
}
/// getMany implementation with interpolation
void getManyInterpolatedImpl(const Float64 * levels, const size_t * indices, size_t num_levels, Value * result) const
{
size_t size = map.size();
if (0 == size)
{
for (size_t i = 0; i < num_levels; ++i)
result[i] = Value();
return;
}
std::unique_ptr<Float64 []> res_holder(new Float64[num_levels]);
Float64 * res = res_holder.get();
getManyFloatInterpolatedImpl(levels, indices, num_levels, res);
for (size_t i = 0; i < num_levels; ++i)
{
if constexpr (is_decimal<Value>)
result[i] = Value(static_cast<typename Value::NativeType>(res[i]));
else
result[i] = Value(res[i]);
}
}
/// getFloat implementation with interpolation
Float64 getFloatInterpolatedImpl(Float64 level) const
{
size_t size = map.size();
if (0 == size)
return std::numeric_limits<Float64>::quiet_NaN();
/// Copy the data to a temporary array to get the element you need in order.
std::unique_ptr<Pair[]> array_holder(new Pair[size]);
Pair * array = array_holder.get();
size_t i = 0;
for (const auto & pair : map)
{
array[i] = pair.getValue();
++i;
}
::sort(array, array + size, [](const Pair & a, const Pair & b) { return a.first < b.first; });
std::partial_sum(array, array + size, array, [](const Pair & acc, const Pair & p) { return Pair(p.first, acc.second + p.second); });
Weight max_position = array[size - 1].second - 1;
Float64 position = max_position * level;
return quantileInterpolated(array, size, position);
}
/// getManyFloat implementation with interpolation
void getManyFloatInterpolatedImpl(const Float64 * levels, const size_t * indices, size_t num_levels, Float64 * result) const
{
size_t size = map.size();
if (0 == size)
{
for (size_t i = 0; i < num_levels; ++i)
result[i] = std::numeric_limits<Float64>::quiet_NaN();
return;
}
/// Copy the data to a temporary array to get the element you need in order.
std::unique_ptr<Pair[]> array_holder(new Pair[size]);
Pair * array = array_holder.get();
size_t i = 0;
for (const auto & pair : map)
{
array[i] = pair.getValue();
++i;
}
::sort(array, array + size, [](const Pair & a, const Pair & b) { return a.first < b.first; });
std::partial_sum(array, array + size, array, [](Pair acc, Pair & p) { return Pair(p.first, acc.second + p.second); });
Weight max_position = array[size - 1].second - 1;
for (size_t j = 0; j < num_levels; ++j)
{
Float64 position = max_position * levels[indices[j]];
result[indices[j]] = quantileInterpolated(array, size, position);
}
}
/// Calculate quantile, using linear interpolation between two closest values
Float64 NO_SANITIZE_UNDEFINED quantileInterpolated(const Pair * array, size_t size, Float64 position) const
{
/*
for (size_t i = 0; i < size; ++i)
std::cout << "array[" << i << "]: " << toString(Field(array[i].first)) << ", " << array[i].second << std::endl;
std::cout << "position: " << position << std::endl;
*/
size_t lower = static_cast<size_t>(std::floor(position));
size_t higher = static_cast<size_t>(std::ceil(position));
// std::cout << "lower: " << lower << ", higher: " << higher << std::endl;
const auto * lower_it = std::lower_bound(array, array + size, lower + 1, [](const Pair & a, size_t b) { return a.second < b; });
const auto * higher_it = std::lower_bound(array, array + size, higher + 1, [](const Pair & a, size_t b) { return a.second < b; });
if (lower_it == array + size)
lower_it = array + size - 1;
if (higher_it == array + size)
higher_it = array + size - 1;
// std::cout << "lower_index:" << lower_it - array << ", higher_index:" << higher_it - array << std::endl;
UnderlyingType lower_key = lower_it->first;
UnderlyingType higher_key = higher_it->first;
if (lower == higher)
return static_cast<Float64>(lower_key);
if (lower_key == higher_key)
return static_cast<Float64>(lower_key);
return (static_cast<Float64>(higher) - position) * lower_key + (position - static_cast<Float64>(lower)) * higher_key;
}
};
template <typename Value, bool _> using FuncQuantileExactWeighted = AggregateFunctionQuantile<Value, QuantileExactWeighted<Value>, NameQuantileExactWeighted, true, void, false, false>;
template <typename Value, bool _> using FuncQuantilesExactWeighted = AggregateFunctionQuantile<Value, QuantileExactWeighted<Value>, NameQuantilesExactWeighted, true, void, true, false>;
template <typename Value, bool return_float, bool interpolated>
using FuncQuantileExactWeighted = AggregateFunctionQuantile<
Value,
QuantileExactWeighted<Value, interpolated>,
NameQuantileExactWeighted,
true,
std::conditional_t<return_float, Float64, void>,
false,
false>;
template <typename Value, bool return_float, bool interpolated>
using FuncQuantilesExactWeighted = AggregateFunctionQuantile<
Value,
QuantileExactWeighted<Value, interpolated>,
NameQuantilesExactWeighted,
true,
std::conditional_t<return_float, Float64, void>,
true,
false>;
template <template <typename, bool> class Function>
template <template <typename, bool, bool> class Function, bool interpolated>
AggregateFunctionPtr createAggregateFunctionQuantile(
const std::string & name, const DataTypes & argument_types, const Array & params, const Settings *)
{
@ -224,22 +402,23 @@ AggregateFunctionPtr createAggregateFunctionQuantile(
WhichDataType which(argument_type);
#define DISPATCH(TYPE) \
if (which.idx == TypeIndex::TYPE) return std::make_shared<Function<TYPE, true>>(argument_types, params);
if (which.idx == TypeIndex::TYPE) \
return std::make_shared<Function<TYPE, interpolated, interpolated>>(argument_types, params);
FOR_BASIC_NUMERIC_TYPES(DISPATCH)
#undef DISPATCH
if (which.idx == TypeIndex::Date) return std::make_shared<Function<DataTypeDate::FieldType, false>>(argument_types, params);
if (which.idx == TypeIndex::DateTime) return std::make_shared<Function<DataTypeDateTime::FieldType, false>>(argument_types, params);
if (which.idx == TypeIndex::Date) return std::make_shared<Function<DataTypeDate::FieldType, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::DateTime) return std::make_shared<Function<DataTypeDateTime::FieldType, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Decimal32) return std::make_shared<Function<Decimal32, false>>(argument_types, params);
if (which.idx == TypeIndex::Decimal64) return std::make_shared<Function<Decimal64, false>>(argument_types, params);
if (which.idx == TypeIndex::Decimal128) return std::make_shared<Function<Decimal128, false>>(argument_types, params);
if (which.idx == TypeIndex::Decimal256) return std::make_shared<Function<Decimal256, false>>(argument_types, params);
if (which.idx == TypeIndex::DateTime64) return std::make_shared<Function<DateTime64, false>>(argument_types, params);
if (which.idx == TypeIndex::Decimal32) return std::make_shared<Function<Decimal32, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Decimal64) return std::make_shared<Function<Decimal64, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Decimal128) return std::make_shared<Function<Decimal128, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Decimal256) return std::make_shared<Function<Decimal256, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::DateTime64) return std::make_shared<Function<DateTime64, false, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Int128) return std::make_shared<Function<Int128, true>>(argument_types, params);
if (which.idx == TypeIndex::UInt128) return std::make_shared<Function<UInt128, true>>(argument_types, params);
if (which.idx == TypeIndex::Int256) return std::make_shared<Function<Int256, true>>(argument_types, params);
if (which.idx == TypeIndex::UInt256) return std::make_shared<Function<UInt256, true>>(argument_types, params);
if (which.idx == TypeIndex::Int128) return std::make_shared<Function<Int128, interpolated, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::UInt128) return std::make_shared<Function<UInt128, interpolated, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::Int256) return std::make_shared<Function<Int256, interpolated, interpolated>>(argument_types, params);
if (which.idx == TypeIndex::UInt256) return std::make_shared<Function<UInt256, interpolated, interpolated>>(argument_types, params);
throw Exception(ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT, "Illegal type {} of argument for aggregate function {}",
argument_type->getName(), name);
@ -252,11 +431,17 @@ void registerAggregateFunctionsQuantileExactWeighted(AggregateFunctionFactory &
/// For aggregate functions returning array we cannot return NULL on empty set.
AggregateFunctionProperties properties = { .returns_default_when_only_null = true };
factory.registerFunction(NameQuantileExactWeighted::name, createAggregateFunctionQuantile<FuncQuantileExactWeighted>);
factory.registerFunction(NameQuantilesExactWeighted::name, { createAggregateFunctionQuantile<FuncQuantilesExactWeighted>, properties });
factory.registerFunction(NameQuantileExactWeighted::name, createAggregateFunctionQuantile<FuncQuantileExactWeighted, false>);
factory.registerFunction(
NameQuantilesExactWeighted::name, {createAggregateFunctionQuantile<FuncQuantilesExactWeighted, false>, properties});
factory.registerFunction(NameQuantileExactWeightedInterpolated::name, createAggregateFunctionQuantile<FuncQuantileExactWeighted, true>);
factory.registerFunction(
NameQuantilesExactWeightedInterpolated::name, {createAggregateFunctionQuantile<FuncQuantilesExactWeighted, true>, properties});
/// 'median' is an alias for 'quantile'
factory.registerAlias("medianExactWeighted", NameQuantileExactWeighted::name);
factory.registerAlias("medianExactWeightedInterpolated", NameQuantileExactWeightedInterpolated::name);
}
}

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@ -1,4 +1,6 @@
10 [1,1,1,1,10,10,10,10,100,100,100]
10 [1,1,2,4,7,10,35,61,87,100,100]
10 [1,1,1,7.299999999999997,10,10,10,36.999999999999986,100,100,100]
10 [1,1,1,7.299999999999997,10,10,10,36.999999999999986,100,100,100]
100 100
61 61

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@ -1,4 +1,6 @@
SELECT quantileExactWeighted(0.5)(x, 1) AS q5, quantilesExactWeighted(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1)(x, 1) AS qs FROM (SELECT arrayJoin([1, 1, 1, 10, 10, 10, 10, 100, 100, 100]) AS x);
SELECT quantileInterpolatedWeighted(0.5)(x, 1) AS q5, quantilesInterpolatedWeighted(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1)(x, 1) AS qs FROM (SELECT arrayJoin([1, 1, 1, 10, 10, 10, 10, 100, 100, 100]) AS x);
SELECT quantileExactWeightedInterpolated(0.5)(x, 1) AS q5, quantilesExactWeightedInterpolated(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1)(x, 1) AS qs FROM (SELECT arrayJoin([1, 1, 1, 10, 10, 10, 10, 100, 100, 100]) AS x);
SELECT quantile(0.5)(x) AS q5, quantiles(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1)(x) AS qs FROM (SELECT arrayJoin([1, 1, 1, 10, 10, 10, 10, 100, 100, 100]) AS x);
SELECT quantileExact(0)(x), quantileTiming(0)(x) FROM (SELECT number + 100 AS x FROM system.numbers LIMIT 10000);
SELECT quantileExact(x), quantileTiming(x) FROM (SELECT number % 123 AS x FROM system.numbers LIMIT 10000);

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@ -8,6 +8,8 @@
['2016-06-15 23:00:00']
2016-06-15 23:00:00
['2016-06-15 23:00:00']
2016-06-15 23:00:00
['2016-06-15 23:00:00']
30000
[30000]
30000

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@ -18,6 +18,9 @@ SELECT quantilesExactWeighted(0.2)(d, 1) FROM datetime;
SELECT quantileInterpolatedWeighted(0.2)(d, 1) FROM datetime;
SELECT quantilesInterpolatedWeighted(0.2)(d, 1) FROM datetime;
SELECT quantileExactWeightedInterpolated(0.2)(d, 1) FROM datetime;
SELECT quantilesExactWeightedInterpolated(0.2)(d, 1) FROM datetime;
SELECT quantileTiming(0.2)(d) FROM datetime;
SELECT quantilesTiming(0.2)(d) FROM datetime;

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@ -10,3 +10,15 @@ quantileInterpolatedWeighted
[-50,-40.4,-30.3,-20.2,-10.1,0,10.1,20.2,30.3,40.4,50]
[-16.66666666,-13.46666666,-10.09999999,-6.73333332,-3.36666666,0,3.36666666,6.73333332,10.09999999,13.46666666,16.66666666]
[-10,-8.08,-6.06,-4.04,-2.02,0,2.02,4.04,6.06,8.08,10]
quantileExactWeightedInterpolated
0 0 0 Decimal(38, 8)
-25.5 -8.49999999 -5.1 Decimal(38, 8)
0 0 0
10 3.33333333 2
20 6.66666666 4
30 10 6
40 13.33333333 8
50 16.66666666 10
[-50,-40,-30,-20,-10,0,10,20,30,40,50]
[-16.66666666,-13.33333333,-10,-6.66666666,-3.33333333,0,3.33333333,6.66666666,10,13.33333333,16.66666666]
[-10,-8,-6,-4,-2,0,2,4,6,8,10]

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@ -24,4 +24,17 @@ SELECT quantilesInterpolatedWeighted(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8
SELECT quantilesInterpolatedWeighted(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)(b, 2) FROM decimal;
SELECT quantilesInterpolatedWeighted(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)(c, 3) FROM decimal;
SELECT 'quantileExactWeightedInterpolated';
SELECT medianExactWeightedInterpolated(a, 1), medianExactWeightedInterpolated(b, 2), medianExactWeightedInterpolated(c, 3) as x, toTypeName(x) FROM decimal;
SELECT quantileExactWeightedInterpolated(a, 1), quantileExactWeightedInterpolated(b, 2), quantileExactWeightedInterpolated(c, 3) as x, toTypeName(x) FROM decimal WHERE a < 0;
SELECT quantileExactWeightedInterpolated(0.0)(a, 1), quantileExactWeightedInterpolated(0.0)(b, 2), quantileExactWeightedInterpolated(0.0)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantileExactWeightedInterpolated(0.2)(a, 1), quantileExactWeightedInterpolated(0.2)(b, 2), quantileExactWeightedInterpolated(0.2)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantileExactWeightedInterpolated(0.4)(a, 1), quantileExactWeightedInterpolated(0.4)(b, 2), quantileExactWeightedInterpolated(0.4)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantileExactWeightedInterpolated(0.6)(a, 1), quantileExactWeightedInterpolated(0.6)(b, 2), quantileExactWeightedInterpolated(0.6)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantileExactWeightedInterpolated(0.8)(a, 1), quantileExactWeightedInterpolated(0.8)(b, 2), quantileExactWeightedInterpolated(0.8)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantileExactWeightedInterpolated(1.0)(a, 1), quantileExactWeightedInterpolated(1.0)(b, 2), quantileExactWeightedInterpolated(1.0)(c, 3) FROM decimal WHERE a >= 0;
SELECT quantilesExactWeightedInterpolated(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)(a, 1) FROM decimal;
SELECT quantilesExactWeightedInterpolated(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)(b, 2) FROM decimal;
SELECT quantilesExactWeightedInterpolated(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)(c, 3) FROM decimal;
DROP TABLE IF EXISTS decimal;

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@ -1,4 +1,4 @@
personal_ws-1.1 en 2983
personal_ws-1.1 en 3036
AArch
ACLs
ALTERs
@ -24,7 +24,6 @@ Aggregatefunction
AggregatingMergeTree
AggregatorThreads
AggregatorThreadsActive
AzureQueue
Akka
AlertManager
Alexey
@ -48,6 +47,7 @@ AutoFDO
AutoML
Autocompletion
AvroConfluent
AzureQueue
BIGINT
BIGSERIAL
BORO
@ -115,13 +115,13 @@ CESU
CIDR
CIDRToRange
CKMAN
CKibana
CLOB
CLion
CMPLNT
CMake
CMakeLists
CODECS
CountMin
COVID
CPUFrequencyMHz
CPUs
@ -153,7 +153,6 @@ ChannelID
Cidr
Ciphertext
CityHash
CKibana
Clangd
ClickBench
ClickCat
@ -186,6 +185,7 @@ ConnectionDetails
Const
ContextLockWait
Contrib
CountMin
Covid
Cramer's
Criteo
@ -250,12 +250,12 @@ DoubleDelta
Doxygen
Durre
ECMA
ElasticSearch
ETag
Ecto
EdgeAngle
EdgeLengthKm
EdgeLengthM
ElasticSearch
EmbeddedRocksDB
Embeddings
Encodings
@ -423,9 +423,9 @@ JSONCompactStrings
JSONCompactStringsEachRow
JSONCompactStringsEachRowWithNames
JSONCompactStringsEachRowWithNamesAndTypes
JSONCompactWithProgress
JSONDynamicPaths
JSONDynamicPathsWithTypes
JSONCompactWithProgress
JSONEachRow
JSONEachRowWithProgress
JSONExtract
@ -442,11 +442,11 @@ JSONExtractUInt
JSONHas
JSONLength
JSONObjectEachRow
JSONSharedDataPaths
JSONSharedDataPathsWithTypes
JSONStrings
JSONStringsEachRow
JSONStringsEachRowWithProgress
JSONSharedDataPaths
JSONSharedDataPathsWithTypes
JSONType
JSONs
Jaeger
@ -981,8 +981,8 @@ ThreadPoolRemoteFSReaderThreads
ThreadPoolRemoteFSReaderThreadsActive
ThreadsActive
ThreadsInOvercommitTracker
TimescaleDB's
TimeSeries
TimescaleDB's
Timeunit
TinyLog
Tkachenko
@ -1547,6 +1547,7 @@ dequeues
deserialization
deserialized
deserializing
dest
destructor
destructors
detectCharset
@ -1572,12 +1573,12 @@ disjunction
disjunctions
displayName
displaySecretsInShowAndSelect
distro
distinctdynamictypes
distinctDynamicTypes
distinctjsonpaths
distinctJSONPaths
distinctJSONPathsAndTypes
distinctdynamictypes
distinctjsonpaths
distro
divideDecimal
dmesg
doesnt
@ -2361,6 +2362,7 @@ quantileExactHigh
quantileExactInclusive
quantileExactLow
quantileExactWeighted
quantileExactWeightedInterpolated
quantileGK
quantileInterpolatedWeighted
quantileTDigest
@ -2372,6 +2374,7 @@ quantileddsketch
quantiledeterministic
quantileexact
quantileexactweighted
quantileexactweightedInterpolated
quantiles
quantilesExactExclusive
quantilesExactInclusive
@ -2592,7 +2595,6 @@ sqlinsert
sqlite
sqrt
src
dest
srcReplicas
sshkey
stackoverflow