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* Edit and translate to Russian. * v2 27.10 * other-functions * Update docs/ru/sql-reference/functions/other-functions.md Co-authored-by: BayoNet <da-daos@yandex.ru> * Update docs/ru/sql-reference/functions/other-functions.md Co-authored-by: BayoNet <da-daos@yandex.ru> Co-authored-by: Daria Mozhaeva <dmozhaeva@yandex-team.ru> Co-authored-by: BayoNet <da-daos@yandex.ru>
165 lines
7.5 KiB
Markdown
165 lines
7.5 KiB
Markdown
---
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toc_priority: 202
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---
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# quantileExact {#quantileexact}
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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 [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles) function.
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**Syntax**
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``` sql
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quantileExact(level)(expr)
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```
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Alias: `medianExact`.
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**Parameters**
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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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SELECT quantileExact(number) FROM numbers(10)
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```
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Result:
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``` text
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┌─quantileExact(number)─┐
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│ 5 │
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└───────────────────────┘
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```
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# quantileExactLow {#quantileexactlow}
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Similar to `quantileExact`, this computes the exact [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
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To get the exact value, all the passed values are combined into an array, which is then fully sorted. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
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The return value depends on the quantile level and the number of elements in the selection, i.e. if the level is 0.5, then the function returns the lower median value for an even number of elements and the middle median value for an odd number of elements. Median is calculated similarly to the [median_low](https://docs.python.org/3/library/statistics.html#statistics.median_low) implementation which is used in python.
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For all other levels, the element at the index corresponding to the value of `level * size_of_array` is returned. For example:
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``` sql
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SELECT quantileExactLow(0.1)(number) FROM numbers(10)
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┌─quantileExactLow(0.1)(number)─┐
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│ 1 │
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└───────────────────────────────┘
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```
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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 [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles) function.
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**Syntax**
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``` sql
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quantileExact(level)(expr)
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```
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Alias: `medianExactLow`.
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**Parameters**
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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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SELECT quantileExactLow(number) FROM numbers(10)
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```
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Result:
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``` text
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┌─quantileExactLow(number)─┐
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│ 4 │
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└──────────────────────────┘
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```
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# quantileExactHigh {#quantileexacthigh}
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Similar to `quantileExact`, this computes the exact [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
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All the passed values are combined into an array, which is then fully sorted,
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to get the exact value. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
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The return value depends on the quantile level and the number of elements in the selection, i.e. if the level is 0.5, then the function returns the higher median value for an even number of elements and the middle median value for an odd number of elements. Median is calculated similarly to the [median_high](https://docs.python.org/3/library/statistics.html#statistics.median_high) implementation which is used in python. For all other levels, the element at the index corresponding to the value of `level * size_of_array` is returned.
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This implementation behaves exactly similar to the current `quantileExact` implementation.
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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 [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles) function.
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**Syntax**
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``` sql
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quantileExactHigh(level)(expr)
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```
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Alias: `medianExactHigh`.
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**Parameters**
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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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SELECT quantileExactHigh(number) FROM numbers(10)
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```
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Result:
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``` text
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┌─quantileExactHigh(number)─┐
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│ 5 │
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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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- [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles)
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