mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-22 07:31:57 +00:00
First draft
This commit is contained in:
parent
de115cfc8c
commit
190b443518
@ -158,6 +158,101 @@ Result:
|
||||
│ 5 │
|
||||
└───────────────────────────┘
|
||||
```
|
||||
|
||||
## quantileExactExclusive {#quantileexactexclusive}
|
||||
|
||||
Exactly computes the [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
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.
|
||||
|
||||
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.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
quantileExactExclusive(level)(expr)
|
||||
```
|
||||
|
||||
**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).
|
||||
|
||||
**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**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE num AS numbers(1000);
|
||||
|
||||
SELECT quantileExactExclusive(0.6)(x) FROM (SELECT number AS x FROM num);
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─quantileExactExclusive(0.6)(x)─┐
|
||||
│ 599.6 │
|
||||
└────────────────────────────────┘
|
||||
```
|
||||
|
||||
## quantileExactInclusive {#quantileexactinclusive}
|
||||
|
||||
Exactly computes the [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
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.
|
||||
|
||||
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.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
quantileExactInclusive(level)(expr)
|
||||
```
|
||||
|
||||
**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).
|
||||
|
||||
**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**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE num AS numbers(1000);
|
||||
|
||||
SELECT quantileExactInclusive(0.6)(x) FROM (SELECT number AS x FROM num);
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─quantileExactInclusive(0.6)(x)─┐
|
||||
│ 599.4 │
|
||||
└────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [median](../../../sql-reference/aggregate-functions/reference/median.md#median)
|
||||
|
@ -7,3 +7,98 @@ toc_priority: 201
|
||||
Syntax: `quantiles(level1, level2, …)(x)`
|
||||
|
||||
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.
|
||||
|
||||
## quantilesExactExclusive {#quantilesexactexclusive}
|
||||
|
||||
Exactly computes the [quantiles](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
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.
|
||||
|
||||
Works more efficiently with sets of levels than [quantilesExactExclusive](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantileexactexclusive).
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
quantilesExactExclusive(level1, level2, ...)(expr)
|
||||
```
|
||||
|
||||
**Arguments**
|
||||
|
||||
- `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]`.
|
||||
- `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).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- [Array](../../../sql-reference/data-types/array.md) of quantiles of the specified levels.
|
||||
|
||||
Type of array values:
|
||||
|
||||
- [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**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE num AS numbers(1000);
|
||||
|
||||
SELECT quantilesExactExclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x) FROM (SELECT number AS x FROM num);
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─quantilesExactExclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x)─┐
|
||||
│ [249.25,499.5,749.75,899.9,949.9499999999999,989.99,998.999] │
|
||||
└─────────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## quantilesExactInclusive {#quantilesexactinclusive}
|
||||
|
||||
Exactly computes the [quantiles](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
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.
|
||||
|
||||
Works more efficiently with sets of levels than [quantilesExactInclusive](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantilesexactinclusive).
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
quantilesExactInclusive(level1, level2, ...)(expr)
|
||||
```
|
||||
|
||||
**Arguments**
|
||||
|
||||
- `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]`.
|
||||
- `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).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- [Array](../../../sql-reference/data-types/array.md) of quantiles of the specified levels.
|
||||
|
||||
Type of array values:
|
||||
|
||||
- [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**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE num AS numbers(1000);
|
||||
|
||||
SELECT quantilesExactInclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x) FROM (SELECT number AS x FROM num);
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─quantilesExactInclusive(0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.999)(x)─┐
|
||||
│ [249.75,499.5,749.25,899.1,949.05,989.01,998.001] │
|
||||
└─────────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
Loading…
Reference in New Issue
Block a user