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First draft
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George
parent
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@ -158,6 +158,101 @@ Result:
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│ 5 │
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└───────────────────────────┘
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```
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## quantileExactExclusive {#quantileexactexclusive}
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Exactly computes the [quantile](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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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 [quantilesExactExclusive](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantilesexactexclusive) function.
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**Syntax**
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``` sql
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quantileExactExclusive(level)(expr)
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```
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**Arguments**
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- `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).
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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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**Returned value**
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- Quantile of the specified level.
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Type:
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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 quantileExactExclusive(0.6)(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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┌─quantileExactExclusive(0.6)(x)─┐
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│ 599.6 │
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└────────────────────────────────┘
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```
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## quantileExactInclusive {#quantileexactinclusive}
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Exactly computes the [quantile](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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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 [quantilesExactInclusive](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantilesexactexclusive) function.
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**Syntax**
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``` sql
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quantileExactInclusive(level)(expr)
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```
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**Arguments**
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- `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).
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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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**Returned value**
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- Quantile of the specified level.
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Type:
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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 quantileExactInclusive(0.6)(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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┌─quantileExactInclusive(0.6)(x)─┐
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│ 599.4 │
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└────────────────────────────────┘
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```
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**See Also**
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- [median](../../../sql-reference/aggregate-functions/reference/median.md#median)
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@ -7,3 +7,98 @@ toc_priority: 201
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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`, `quantilesTDigest`. 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 {#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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Works more efficiently with sets of levels than [quantilesExactExclusive](../../../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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- `level` — Leveles of quantiles. Constant floating-point numbers from 0 to 1. We recommend using a `level` values in the range of `[0.01, 0.99]`.
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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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**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 {#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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Works more efficiently with sets of levels than [quantilesExactInclusive](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantilesexactinclusive).
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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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- `level` — Leveles of quantiles. Constant floating-point numbers from 0 to 1. We recommend using a `level` values in the range of `[0.01, 0.99]`.
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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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**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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