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173 lines
7.3 KiB
Markdown
173 lines
7.3 KiB
Markdown
---
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slug: /en/sql-reference/aggregate-functions/reference/quantiles
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sidebar_position: 201
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---
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# quantiles Functions
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## quantiles
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Syntax: `quantiles(level1, level2, …)(x)`
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All the quantile functions also have corresponding quantiles functions: `quantiles`, `quantilesDeterministic`, `quantilesTiming`, `quantilesTimingWeighted`, `quantilesExact`, `quantilesExactWeighted`, `quantileInterpolatedWeighted`, `quantilesTDigest`, `quantilesBFloat16`. These functions calculate all the quantiles of the listed levels in one pass, and return an array of the resulting values.
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## quantilesExactExclusive
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Exactly computes the [quantiles](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
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To get exact value, all the passed values are combined into an array, which is then partially sorted. Therefore, the function consumes `O(n)` memory, where `n` is a number of values that were passed. However, for a small number of values, the function is very effective.
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This function is equivalent to [PERCENTILE.EXC](https://support.microsoft.com/en-us/office/percentile-exc-function-bbaa7204-e9e1-4010-85bf-c31dc5dce4ba) Excel function, ([type R6](https://en.wikipedia.org/wiki/Quantile#Estimating_quantiles_from_a_sample)).
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Works more efficiently with sets of levels than [quantileExactExclusive](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantileexactexclusive).
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**Syntax**
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``` sql
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quantilesExactExclusive(level1, level2, ...)(expr)
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```
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**Arguments**
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- `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).
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**Parameters**
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- `level` — Levels of quantiles. Possible values: (0, 1) — bounds not included. [Float](../../../sql-reference/data-types/float.md).
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**Returned value**
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- [Array](../../../sql-reference/data-types/array.md) of quantiles of the specified levels.
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Type of array values:
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- [Float64](../../../sql-reference/data-types/float.md) for numeric data type input.
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- [Date](../../../sql-reference/data-types/date.md) if input values have the `Date` type.
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- [DateTime](../../../sql-reference/data-types/datetime.md) if input values have the `DateTime` type.
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**Example**
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Query:
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``` sql
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CREATE TABLE num AS numbers(1000);
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SELECT quantilesExactExclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x) FROM (SELECT number AS x FROM num);
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```
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Result:
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``` text
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┌─quantilesExactExclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x)─┐
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│ [249.25,499.5,749.75,899.9,949.9499999999999,989.99,998.999] │
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└─────────────────────────────────────────────────────────────────────┘
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```
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## quantilesExactInclusive
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Exactly computes the [quantiles](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
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To get exact value, all the passed values are combined into an array, which is then partially sorted. Therefore, the function consumes `O(n)` memory, where `n` is a number of values that were passed. However, for a small number of values, the function is very effective.
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This function is equivalent to [PERCENTILE.INC](https://support.microsoft.com/en-us/office/percentile-inc-function-680f9539-45eb-410b-9a5e-c1355e5fe2ed) Excel function, ([type R7](https://en.wikipedia.org/wiki/Quantile#Estimating_quantiles_from_a_sample)).
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Works more efficiently with sets of levels than [quantileExactInclusive](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantileexactinclusive).
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**Syntax**
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``` sql
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quantilesExactInclusive(level1, level2, ...)(expr)
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```
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**Arguments**
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- `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).
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**Parameters**
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- `level` — Levels of quantiles. Possible values: [0, 1] — bounds included. [Float](../../../sql-reference/data-types/float.md).
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**Returned value**
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- [Array](../../../sql-reference/data-types/array.md) of quantiles of the specified levels.
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Type of array values:
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- [Float64](../../../sql-reference/data-types/float.md) for numeric data type input.
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- [Date](../../../sql-reference/data-types/date.md) if input values have the `Date` type.
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- [DateTime](../../../sql-reference/data-types/datetime.md) if input values have the `DateTime` type.
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**Example**
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Query:
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``` sql
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CREATE TABLE num AS numbers(1000);
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SELECT quantilesExactInclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x) FROM (SELECT number AS x FROM num);
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```
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Result:
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``` text
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┌─quantilesExactInclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x)─┐
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│ [249.75,499.5,749.25,899.1,949.05,989.01,998.001] │
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└─────────────────────────────────────────────────────────────────────┘
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```
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## quantilesApprox
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`quantilesApprox` works similarly with `quantileApprox` but allows us to calculate quantities at different levels simultaneously and returns an array.
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**Syntax**
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``` sql
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quantilesApprox(accuracy, level1, level2, ...)(expr)
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```
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**Returned value**
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- [Array](../../../sql-reference/data-types/array.md) of quantiles of the specified levels.
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Type of array values:
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- [Float64](../../../sql-reference/data-types/float.md) for numeric data type input.
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- [Date](../../../sql-reference/data-types/date.md) if input values have the `Date` type.
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- [DateTime](../../../sql-reference/data-types/datetime.md) if input values have the `DateTime` type.
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**Example**
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Query:
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``` sql
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SELECT quantilesApprox(1, 0.25, 0.5, 0.75)(number + 1)
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FROM numbers(1000)
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┌─quantilesApprox(1, 0.25, 0.5, 0.75)(plus(number, 1))─┐
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│ [1,1,1] │
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└──────────────────────────────────────────────────────┘
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SELECT quantilesApprox(10, 0.25, 0.5, 0.75)(number + 1)
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FROM numbers(1000)
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┌─quantilesApprox(10, 0.25, 0.5, 0.75)(plus(number, 1))─┐
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│ [156,413,659] │
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└───────────────────────────────────────────────────────┘
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SELECT quantilesApprox(100, 0.25, 0.5, 0.75)(number + 1)
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FROM numbers(1000)
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┌─quantilesApprox(100, 0.25, 0.5, 0.75)(plus(number, 1))─┐
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│ [251,498,741] │
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└────────────────────────────────────────────────────────┘
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SELECT quantilesApprox(1000, 0.25, 0.5, 0.75)(number + 1)
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FROM numbers(1000)
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┌─quantilesApprox(1000, 0.25, 0.5, 0.75)(plus(number, 1))─┐
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│ [249,499,749] │
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└─────────────────────────────────────────────────────────┘
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```
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