Merge pull request #64626 from Blargian/doc_covarXYZ

Document functions `corr`, `covar`, and their variants
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# corr
Syntax: `corr(x, y)`
Calculates the [Pearson correlation coefficient](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient):
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{\sqrt{\Sigma{(x - \bar{x})^2} * \Sigma{(y - \bar{y})^2}}}
$$
Calculates the Pearson correlation coefficient: `Σ((x - x̅)(y - y̅)) / sqrt(Σ((x - x̅)^2) * Σ((y - y̅)^2))`.
:::note
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the `corrStable` function. It works slower but provides a lower computational error.
:::
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the [`corrStable`](../reference/corrstable.md) function. It is slower but provides a more accurate result.
:::
**Syntax**
```sql
corr(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The Pearson correlation coefficient. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series
(
i UInt32,
x_value Float64,
y_value Float64
)
ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6, -4.4),(2, -9.6, 3),(3, -1.3, -4),(4, 5.3, 9.7),(5, 4.4, 0.037),(6, -8.6, -7.8),(7, 5.1, 9.3),(8, 7.9, -3.6),(9, -8.2, 0.62),(10, -3, 7.3);
```
```sql
SELECT corr(x_value, y_value)
FROM series;
```
Result:
```response
┌─corr(x_value, y_value)─┐
│ 0.1730265755453256 │
└────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/corrmatrix
sidebar_position: 108
---
# corrMatrix
Computes the correlation matrix over N variables.
**Syntax**
```sql
corrMatrix(x[, ...])
```
**Arguments**
- `x` — a variable number of parameters. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned value**
- Correlation matrix. [Array](../../data-types/array.md)([Array](../../data-types/array.md)([Float64](../../data-types/float.md))).
**Example**
Query:
```sql
DROP TABLE IF EXISTS test;
CREATE TABLE test
(
a UInt32,
b Float64,
c Float64,
d Float64
)
ENGINE = Memory;
INSERT INTO test(a, b, c, d) VALUES (1, 5.6, -4.4, 2.6), (2, -9.6, 3, 3.3), (3, -1.3, -4, 1.2), (4, 5.3, 9.7, 2.3), (5, 4.4, 0.037, 1.222), (6, -8.6, -7.8, 2.1233), (7, 5.1, 9.3, 8.1222), (8, 7.9, -3.6, 9.837), (9, -8.2, 0.62, 8.43555), (10, -3, 7.3, 6.762);
```
```sql
SELECT arrayMap(x -> round(x, 3), arrayJoin(corrMatrix(a, b, c, d))) AS corrMatrix
FROM test;
```
Result:
```response
┌─corrMatrix─────────────┐
1. │ [1,-0.096,0.243,0.746] │
2. │ [-0.096,1,0.173,0.106] │
3. │ [0.243,0.173,1,0.258] │
4. │ [0.746,0.106,0.258,1] │
└────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/corrstable
sidebar_position: 107
---
# corrStable
Calculates the [Pearson correlation coefficient](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient):
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{\sqrt{\Sigma{(x - \bar{x})^2} * \Sigma{(y - \bar{y})^2}}}
$$
Similar to the [`corr`](../reference/corr.md) function, but uses a numerically stable algorithm. As a result, `corrStable` is slower than `corr` but produces a more accurate result.
**Syntax**
```sql
corrStable(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The Pearson correlation coefficient. [Float64](../../data-types/float.md).
***Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series
(
i UInt32,
x_value Float64,
y_value Float64
)
ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6, -4.4),(2, -9.6, 3),(3, -1.3, -4),(4, 5.3, 9.7),(5, 4.4, 0.037),(6, -8.6, -7.8),(7, 5.1, 9.3),(8, 7.9, -3.6),(9, -8.2, 0.62),(10, -3, 7.3);
```
```sql
SELECT corrStable(x_value, y_value)
FROM series;
```
Result:
```response
┌─corrStable(x_value, y_value)─┐
│ 0.17302657554532558 │
└──────────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/covarpop
sidebar_position: 36
sidebar_position: 37
---
# covarPop
Syntax: `covarPop(x, y)`
Calculates the population covariance:
Calculates the value of `Σ((x - x̅)(y - y̅)) / n`.
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{n}
$$
:::note
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the `covarPopStable` function. It works slower but provides a lower computational error.
:::
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the [`covarPopStable`](../reference/covarpopstable.md) function. It works slower but provides a lower computational error.
:::
**Syntax**
```sql
covarPop(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The population covariance between `x` and `y`. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series(i UInt32, x_value Float64, y_value Float64) ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6, -4.4),(2, -9.6, 3),(3, -1.3, -4),(4, 5.3, 9.7),(5, 4.4, 0.037),(6, -8.6, -7.8),(7, 5.1, 9.3),(8, 7.9, -3.6),(9, -8.2, 0.62),(10, -3, 7.3);
```
```sql
SELECT covarPop(x_value, y_value)
FROM series;
```
Result:
```reference
┌─covarPop(x_value, y_value)─┐
│ 6.485648 │
└────────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/covarpopmatrix
sidebar_position: 36
---
# covarPopMatrix
Returns the population covariance matrix over N variables.
**Syntax**
```sql
covarPopMatrix(x[, ...])
```
**Arguments**
- `x` — a variable number of parameters. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- Population covariance matrix. [Array](../../data-types/array.md)([Array](../../data-types/array.md)([Float64](../../data-types/float.md))).
**Example**
Query:
```sql
DROP TABLE IF EXISTS test;
CREATE TABLE test
(
a UInt32,
b Float64,
c Float64,
d Float64
)
ENGINE = Memory;
INSERT INTO test(a, b, c, d) VALUES (1, 5.6, -4.4, 2.6), (2, -9.6, 3, 3.3), (3, -1.3, -4, 1.2), (4, 5.3, 9.7, 2.3), (5, 4.4, 0.037, 1.222), (6, -8.6, -7.8, 2.1233), (7, 5.1, 9.3, 8.1222), (8, 7.9, -3.6, 9.837), (9, -8.2, 0.62, 8.43555), (10, -3, 7.3, 6.762);
```
```sql
SELECT arrayMap(x -> round(x, 3), arrayJoin(covarPopMatrix(a, b, c, d))) AS covarPopMatrix
FROM test;
```
Result:
```reference
┌─covarPopMatrix────────────┐
1. │ [8.25,-1.76,4.08,6.748] │
2. │ [-1.76,41.07,6.486,2.132] │
3. │ [4.08,6.486,34.21,4.755] │
4. │ [6.748,2.132,4.755,9.93] │
└───────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/covarpopstable
sidebar_position: 36
---
# covarPopStable
Calculates the value of the population covariance:
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{n}
$$
It is similar to the [covarPop](../reference/covarpop.md) function, but uses a numerically stable algorithm. As a result, `covarPopStable` is slower than `covarPop` but produces a more accurate result.
**Syntax**
```sql
covarPop(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The population covariance between `x` and `y`. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series(i UInt32, x_value Float64, y_value Float64) ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6,-4.4),(2, -9.6,3),(3, -1.3,-4),(4, 5.3,9.7),(5, 4.4,0.037),(6, -8.6,-7.8),(7, 5.1,9.3),(8, 7.9,-3.6),(9, -8.2,0.62),(10, -3,7.3);
```
```sql
SELECT covarPopStable(x_value, y_value)
FROM
(
SELECT
x_value,
y_value
FROM series
);
```
Result:
```reference
┌─covarPopStable(x_value, y_value)─┐
│ 6.485648 │
└──────────────────────────────────┘
```

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Calculates the value of `Σ((x - x̅)(y - y̅)) / (n - 1)`.
Returns Float64. When `n <= 1`, returns `nan`.
:::note
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the `covarSampStable` function. It works slower but provides a lower computational error.
This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the [`covarSampStable`](../reference/covarsamp.md) function. It works slower but provides a lower computational error.
:::
**Syntax**
```sql
covarSamp(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The sample covariance between `x` and `y`. For `n <= 1`, `nan` is returned. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series(i UInt32, x_value Float64, y_value Float64) ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6,-4.4),(2, -9.6,3),(3, -1.3,-4),(4, 5.3,9.7),(5, 4.4,0.037),(6, -8.6,-7.8),(7, 5.1,9.3),(8, 7.9,-3.6),(9, -8.2,0.62),(10, -3,7.3);
```
```sql
SELECT covarSamp(x_value, y_value)
FROM
(
SELECT
x_value,
y_value
FROM series
);
```
Result:
```reference
┌─covarSamp(x_value, y_value)─┐
│ 7.206275555555556 │
└─────────────────────────────┘
```
Query:
```sql
SELECT covarSamp(x_value, y_value)
FROM
(
SELECT
x_value,
y_value
FROM series LIMIT 1
);
```
Result:
```reference
┌─covarSamp(x_value, y_value)─┐
│ nan │
└─────────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/covarsampmatrix
sidebar_position: 38
---
# covarSampMatrix
Returns the sample covariance matrix over N variables.
**Syntax**
```sql
covarSampMatrix(x[, ...])
```
**Arguments**
- `x` — a variable number of parameters. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- Sample covariance matrix. [Array](../../data-types/array.md)([Array](../../data-types/array.md)([Float64](../../data-types/float.md))).
**Example**
Query:
```sql
DROP TABLE IF EXISTS test;
CREATE TABLE test
(
a UInt32,
b Float64,
c Float64,
d Float64
)
ENGINE = Memory;
INSERT INTO test(a, b, c, d) VALUES (1, 5.6, -4.4, 2.6), (2, -9.6, 3, 3.3), (3, -1.3, -4, 1.2), (4, 5.3, 9.7, 2.3), (5, 4.4, 0.037, 1.222), (6, -8.6, -7.8, 2.1233), (7, 5.1, 9.3, 8.1222), (8, 7.9, -3.6, 9.837), (9, -8.2, 0.62, 8.43555), (10, -3, 7.3, 6.762);
```
```sql
SELECT arrayMap(x -> round(x, 3), arrayJoin(covarSampMatrix(a, b, c, d))) AS covarSampMatrix
FROM test;
```
Result:
```reference
┌─covarSampMatrix─────────────┐
1. │ [9.167,-1.956,4.534,7.498] │
2. │ [-1.956,45.634,7.206,2.369] │
3. │ [4.534,7.206,38.011,5.283] │
4. │ [7.498,2.369,5.283,11.034] │
└─────────────────────────────┘
```

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---
slug: /en/sql-reference/aggregate-functions/reference/covarsampstable
sidebar_position: 37
---
# covarSampStable
Calculates the value of `Σ((x - x̅)(y - y̅)) / (n - 1)`. Similar to [covarSamp](../reference/covarsamp.md) but works slower while providing a lower computational error.
**Syntax**
```sql
covarSampStable(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The sample covariance between `x` and `y`. For `n <= 1`, `inf` is returned. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series(i UInt32, x_value Float64, y_value Float64) ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6,-4.4),(2, -9.6,3),(3, -1.3,-4),(4, 5.3,9.7),(5, 4.4,0.037),(6, -8.6,-7.8),(7, 5.1,9.3),(8, 7.9,-3.6),(9, -8.2,0.62),(10, -3,7.3);
```
```sql
SELECT covarSampStable(x_value, y_value)
FROM
(
SELECT
x_value,
y_value
FROM series
);
```
Result:
```reference
┌─covarSampStable(x_value, y_value)─┐
│ 7.206275555555556 │
└───────────────────────────────────┘
```
Query:
```sql
SELECT covarSampStable(x_value, y_value)
FROM
(
SELECT
x_value,
y_value
FROM series LIMIT 1
);
```
Result:
```reference
┌─covarSampStable(x_value, y_value)─┐
│ inf │
└───────────────────────────────────┘
```

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Standard aggregate functions:
- [count](/docs/en/sql-reference/aggregate-functions/reference/count.md)
- [min](/docs/en/sql-reference/aggregate-functions/reference/min.md)
- [max](/docs/en/sql-reference/aggregate-functions/reference/max.md)
- [sum](/docs/en/sql-reference/aggregate-functions/reference/sum.md)
- [avg](/docs/en/sql-reference/aggregate-functions/reference/avg.md)
- [any](/docs/en/sql-reference/aggregate-functions/reference/any.md)
- [stddevPop](/docs/en/sql-reference/aggregate-functions/reference/stddevpop.md)
- [stddevPopStable](/docs/en/sql-reference/aggregate-functions/reference/stddevpopstable.md)
- [stddevSamp](/docs/en/sql-reference/aggregate-functions/reference/stddevsamp.md)
- [stddevSampStable](/docs/en/sql-reference/aggregate-functions/reference/stddevsampstable.md)
- [varPop](/docs/en/sql-reference/aggregate-functions/reference/varpop.md)
- [varSamp](/docs/en/sql-reference/aggregate-functions/reference/varsamp.md)
- [corr](./corr.md)
- [covarPop](/docs/en/sql-reference/aggregate-functions/reference/covarpop.md)
- [covarSamp](/docs/en/sql-reference/aggregate-functions/reference/covarsamp.md)
- [entropy](./entropy.md)
- [exponentialMovingAverage](./exponentialmovingaverage.md)
- [intervalLengthSum](./intervalLengthSum.md)
- [kolmogorovSmirnovTest](./kolmogorovsmirnovtest.md)
- [mannwhitneyutest](./mannwhitneyutest.md)
- [median](./median.md)
- [rankCorr](./rankCorr.md)
- [sumKahan](./sumkahan.md)
- [studentTTest](./studentttest.md)
- [welchTTest](./welchttest.md)
- [count](../reference/count.md)
- [min](../reference/min.md)
- [max](../reference/max.md)
- [sum](../reference/sum.md)
- [avg](../reference/avg.md)
- [any](../reference/any.md)
- [stddevPop](../reference/stddevpop.md)
- [stddevPopStable](../reference/stddevpopstable.md)
- [stddevSamp](../reference/stddevsamp.md)
- [stddevSampStable](../reference/stddevsampstable.md)
- [varPop](../reference/varpop.md)
- [varSamp](../reference/varsamp.md)
- [corr](../reference/corr.md)
- [corr](../reference/corrstable.md)
- [corrMatrix](../reference/corrmatrix.md)
- [covarPop](../reference/covarpop.md)
- [covarStable](../reference/covarpopstable.md)
- [covarPopMatrix](../reference/covarpopmatrix.md)
- [covarSamp](../reference/covarsamp.md)
- [covarSampStable](../reference/covarsampstable.md)
- [covarSampMatrix](../reference/covarsampmatrix.md)
- [entropy](../reference/entropy.md)
- [exponentialMovingAverage](../reference/exponentialmovingaverage.md)
- [intervalLengthSum](../reference/intervalLengthSum.md)
- [kolmogorovSmirnovTest](../reference/kolmogorovsmirnovtest.md)
- [mannwhitneyutest](../reference/mannwhitneyutest.md)
- [median](../reference/median.md)
- [rankCorr](../reference/rankCorr.md)
- [sumKahan](../reference/sumkahan.md)
- [studentTTest](../reference/studentttest.md)
- [welchTTest](../reference/welchttest.md)
ClickHouse-specific aggregate functions:
- [analysisOfVariance](/docs/en/sql-reference/aggregate-functions/reference/analysis_of_variance.md)
- [any](/docs/en/sql-reference/aggregate-functions/reference/any_respect_nulls.md)
- [anyHeavy](/docs/en/sql-reference/aggregate-functions/reference/anyheavy.md)
- [anyLast](/docs/en/sql-reference/aggregate-functions/reference/anylast.md)
- [anyLast](/docs/en/sql-reference/aggregate-functions/reference/anylast_respect_nulls.md)
- [boundingRatio](/docs/en/sql-reference/aggregate-functions/reference/boundrat.md)
- [first_value](/docs/en/sql-reference/aggregate-functions/reference/first_value.md)
- [last_value](/docs/en/sql-reference/aggregate-functions/reference/last_value.md)
- [argMin](/docs/en/sql-reference/aggregate-functions/reference/argmin.md)
- [argMax](/docs/en/sql-reference/aggregate-functions/reference/argmax.md)
- [avgWeighted](/docs/en/sql-reference/aggregate-functions/reference/avgweighted.md)
- [topK](/docs/en/sql-reference/aggregate-functions/reference/topk.md)
- [topKWeighted](/docs/en/sql-reference/aggregate-functions/reference/topkweighted.md)
- [deltaSum](./deltasum.md)
- [deltaSumTimestamp](./deltasumtimestamp.md)
- [groupArray](/docs/en/sql-reference/aggregate-functions/reference/grouparray.md)
- [groupArrayLast](/docs/en/sql-reference/aggregate-functions/reference/grouparraylast.md)
- [groupUniqArray](/docs/en/sql-reference/aggregate-functions/reference/groupuniqarray.md)
- [groupArrayInsertAt](/docs/en/sql-reference/aggregate-functions/reference/grouparrayinsertat.md)
- [groupArrayMovingAvg](/docs/en/sql-reference/aggregate-functions/reference/grouparraymovingavg.md)
- [groupArrayMovingSum](/docs/en/sql-reference/aggregate-functions/reference/grouparraymovingsum.md)
- [groupArraySample](./grouparraysample.md)
- [groupArraySorted](/docs/en/sql-reference/aggregate-functions/reference/grouparraysorted.md)
- [groupArrayIntersect](./grouparrayintersect.md)
- [groupBitAnd](/docs/en/sql-reference/aggregate-functions/reference/groupbitand.md)
- [groupBitOr](/docs/en/sql-reference/aggregate-functions/reference/groupbitor.md)
- [groupBitXor](/docs/en/sql-reference/aggregate-functions/reference/groupbitxor.md)
- [groupBitmap](/docs/en/sql-reference/aggregate-functions/reference/groupbitmap.md)
- [groupBitmapAnd](/docs/en/sql-reference/aggregate-functions/reference/groupbitmapand.md)
- [groupBitmapOr](/docs/en/sql-reference/aggregate-functions/reference/groupbitmapor.md)
- [groupBitmapXor](/docs/en/sql-reference/aggregate-functions/reference/groupbitmapxor.md)
- [sumWithOverflow](/docs/en/sql-reference/aggregate-functions/reference/sumwithoverflow.md)
- [sumMap](/docs/en/sql-reference/aggregate-functions/reference/summap.md)
- [sumMapWithOverflow](/docs/en/sql-reference/aggregate-functions/reference/summapwithoverflow.md)
- [sumMapFiltered](/docs/en/sql-reference/aggregate-functions/parametric-functions.md/#summapfiltered)
- [sumMapFilteredWithOverflow](/docs/en/sql-reference/aggregate-functions/parametric-functions.md/#summapfilteredwithoverflow)
- [minMap](/docs/en/sql-reference/aggregate-functions/reference/minmap.md)
- [maxMap](/docs/en/sql-reference/aggregate-functions/reference/maxmap.md)
- [skewSamp](/docs/en/sql-reference/aggregate-functions/reference/skewsamp.md)
- [skewPop](/docs/en/sql-reference/aggregate-functions/reference/skewpop.md)
- [kurtSamp](/docs/en/sql-reference/aggregate-functions/reference/kurtsamp.md)
- [kurtPop](/docs/en/sql-reference/aggregate-functions/reference/kurtpop.md)
- [uniq](/docs/en/sql-reference/aggregate-functions/reference/uniq.md)
- [uniqExact](/docs/en/sql-reference/aggregate-functions/reference/uniqexact.md)
- [uniqCombined](/docs/en/sql-reference/aggregate-functions/reference/uniqcombined.md)
- [uniqCombined64](/docs/en/sql-reference/aggregate-functions/reference/uniqcombined64.md)
- [uniqHLL12](/docs/en/sql-reference/aggregate-functions/reference/uniqhll12.md)
- [uniqTheta](/docs/en/sql-reference/aggregate-functions/reference/uniqthetasketch.md)
- [quantile](/docs/en/sql-reference/aggregate-functions/reference/quantile.md)
- [quantiles](/docs/en/sql-reference/aggregate-functions/reference/quantiles.md)
- [quantileExact](/docs/en/sql-reference/aggregate-functions/reference/quantileexact.md)
- [quantileExactLow](/docs/en/sql-reference/aggregate-functions/reference/quantileexact.md#quantileexactlow)
- [quantileExactHigh](/docs/en/sql-reference/aggregate-functions/reference/quantileexact.md#quantileexacthigh)
- [quantileExactWeighted](/docs/en/sql-reference/aggregate-functions/reference/quantileexactweighted.md)
- [quantileTiming](/docs/en/sql-reference/aggregate-functions/reference/quantiletiming.md)
- [quantileTimingWeighted](/docs/en/sql-reference/aggregate-functions/reference/quantiletimingweighted.md)
- [quantileDeterministic](/docs/en/sql-reference/aggregate-functions/reference/quantiledeterministic.md)
- [quantileTDigest](/docs/en/sql-reference/aggregate-functions/reference/quantiletdigest.md)
- [quantileTDigestWeighted](/docs/en/sql-reference/aggregate-functions/reference/quantiletdigestweighted.md)
- [quantileBFloat16](/docs/en/sql-reference/aggregate-functions/reference/quantilebfloat16.md#quantilebfloat16)
- [quantileBFloat16Weighted](/docs/en/sql-reference/aggregate-functions/reference/quantilebfloat16.md#quantilebfloat16weighted)
- [quantileDD](/docs/en/sql-reference/aggregate-functions/reference/quantileddsketch.md#quantileddsketch)
- [simpleLinearRegression](/docs/en/sql-reference/aggregate-functions/reference/simplelinearregression.md)
- [singleValueOrNull](/docs/en/sql-reference/aggregate-functions/reference/singlevalueornull.md)
- [stochasticLinearRegression](/docs/en/sql-reference/aggregate-functions/reference/stochasticlinearregression.md)
- [stochasticLogisticRegression](/docs/en/sql-reference/aggregate-functions/reference/stochasticlogisticregression.md)
- [categoricalInformationValue](/docs/en/sql-reference/aggregate-functions/reference/categoricalinformationvalue.md)
- [contingency](./contingency.md)
- [cramersV](./cramersv.md)
- [cramersVBiasCorrected](./cramersvbiascorrected.md)
- [theilsU](./theilsu.md)
- [maxIntersections](./maxintersections.md)
- [maxIntersectionsPosition](./maxintersectionsposition.md)
- [meanZTest](./meanztest.md)
- [quantileGK](./quantileGK.md)
- [quantileInterpolatedWeighted](./quantileinterpolatedweighted.md)
- [sparkBar](./sparkbar.md)
- [sumCount](./sumcount.md)
- [largestTriangleThreeBuckets](./largestTriangleThreeBuckets.md)
- [analysisOfVariance](../reference/analysis_of_variance.md)
- [any](../reference/any_respect_nulls.md)
- [anyHeavy](../reference/anyheavy.md)
- [anyLast](../reference/anylast.md)
- [anyLast](../reference/anylast_respect_nulls.md)
- [boundingRatio](../reference/boundrat.md)
- [first_value](../reference/first_value.md)
- [last_value](../reference/last_value.md)
- [argMin](../reference/argmin.md)
- [argMax](../reference/argmax.md)
- [avgWeighted](../reference/avgweighted.md)
- [topK](../reference/topk.md)
- [topKWeighted](../reference/topkweighted.md)
- [deltaSum](../reference/deltasum.md)
- [deltaSumTimestamp](../reference/deltasumtimestamp.md)
- [groupArray](../reference/grouparray.md)
- [groupArrayLast](../reference/grouparraylast.md)
- [groupUniqArray](../reference/groupuniqarray.md)
- [groupArrayInsertAt](../reference/grouparrayinsertat.md)
- [groupArrayMovingAvg](../reference/grouparraymovingavg.md)
- [groupArrayMovingSum](../reference/grouparraymovingsum.md)
- [groupArraySample](../reference/grouparraysample.md)
- [groupArraySorted](../reference/grouparraysorted.md)
- [groupArrayIntersect](../reference/grouparrayintersect.md)
- [groupBitAnd](../reference/groupbitand.md)
- [groupBitOr](../reference/groupbitor.md)
- [groupBitXor](../reference/groupbitxor.md)
- [groupBitmap](../reference/groupbitmap.md)
- [groupBitmapAnd](../reference/groupbitmapand.md)
- [groupBitmapOr](../reference/groupbitmapor.md)
- [groupBitmapXor](../reference/groupbitmapxor.md)
- [sumWithOverflow](../reference/sumwithoverflow.md)
- [sumMap](../reference/summap.md)
- [sumMapWithOverflow](../reference/summapwithoverflow.md)
- [sumMapFiltered](../parametric-functions.md/#summapfiltered)
- [sumMapFilteredWithOverflow](../parametric-functions.md/#summapfilteredwithoverflow)
- [minMap](../reference/minmap.md)
- [maxMap](../reference/maxmap.md)
- [skewSamp](../reference/skewsamp.md)
- [skewPop](../reference/skewpop.md)
- [kurtSamp](../reference/kurtsamp.md)
- [kurtPop](../reference/kurtpop.md)
- [uniq](../reference/uniq.md)
- [uniqExact](../reference/uniqexact.md)
- [uniqCombined](../reference/uniqcombined.md)
- [uniqCombined64](../reference/uniqcombined64.md)
- [uniqHLL12](../reference/uniqhll12.md)
- [uniqTheta](../reference/uniqthetasketch.md)
- [quantile](../reference/quantile.md)
- [quantiles](../reference/quantiles.md)
- [quantileExact](../reference/quantileexact.md)
- [quantileExactLow](../reference/quantileexact.md#quantileexactlow)
- [quantileExactHigh](../reference/quantileexact.md#quantileexacthigh)
- [quantileExactWeighted](../reference/quantileexactweighted.md)
- [quantileTiming](../reference/quantiletiming.md)
- [quantileTimingWeighted](../reference/quantiletimingweighted.md)
- [quantileDeterministic](../reference/quantiledeterministic.md)
- [quantileTDigest](../reference/quantiletdigest.md)
- [quantileTDigestWeighted](../reference/quantiletdigestweighted.md)
- [quantileBFloat16](../reference/quantilebfloat16.md#quantilebfloat16)
- [quantileBFloat16Weighted](../reference/quantilebfloat16.md#quantilebfloat16weighted)
- [quantileDD](../reference/quantileddsketch.md#quantileddsketch)
- [simpleLinearRegression](../reference/simplelinearregression.md)
- [singleValueOrNull](../reference/singlevalueornull.md)
- [stochasticLinearRegression](../reference/stochasticlinearregression.md)
- [stochasticLogisticRegression](../reference/stochasticlogisticregression.md)
- [categoricalInformationValue](../reference/categoricalinformationvalue.md)
- [contingency](../reference/contingency.md)
- [cramersV](../reference/cramersv.md)
- [cramersVBiasCorrected](../reference/cramersvbiascorrected.md)
- [theilsU](../reference/theilsu.md)
- [maxIntersections](../reference/maxintersections.md)
- [maxIntersectionsPosition](../reference/maxintersectionsposition.md)
- [meanZTest](../reference/meanztest.md)
- [quantileGK](../reference/quantileGK.md)
- [quantileInterpolatedWeighted](../reference/quantileinterpolatedweighted.md)
- [sparkBar](../reference/sparkbar.md)
- [sumCount](../reference/sumcount.md)
- [largestTriangleThreeBuckets](../reference/largestTriangleThreeBuckets.md)

View File

@ -989,6 +989,7 @@ URLHash
URLHierarchy
URLPathHierarchy
USearch
UTCTimestamp
UUIDNumToString
UUIDStringToNum
UUIDToNum
@ -1366,6 +1367,10 @@ const
contrib
convertCharset
coroutines
corrMatrix
corrStable
corrmatrix
corrstable
cosineDistance
countDigits
countEqual
@ -1375,10 +1380,19 @@ countSubstrings
countSubstringsCaseInsensitive
countSubstringsCaseInsensitiveUTF
covarPop
covarPopMatrix
covarPopStable
covarSamp
covarSampMatrix
covarSampStable
covarStable
covariates
covarpop
covarpopmatrix
covarpopstable
covarsamp
covarsampmatrix
covarsampstable
covid
cpp
cppkafka
@ -1609,6 +1623,7 @@ formated
formatschema
formatter
formatters
frac
freezed
fromDaysSinceYearZero
fromModifiedJulianDay
@ -1735,8 +1750,8 @@ hdfs
hdfsCluster
heredoc
heredocs
hilbertEncode
hilbertDecode
hilbertEncode
hiveHash
holistics
homebrew
@ -2666,16 +2681,16 @@ toStartOfFiveMinutes
toStartOfHour
toStartOfISOYear
toStartOfInterval
toStartOfMicrosecond
toStartOfMillisecond
toStartOfMinute
toStartOfMonth
toStartOfNanosecond
toStartOfQuarter
toStartOfSecond
toStartOfTenMinutes
toStartOfWeek
toStartOfYear
toStartOfMicrosecond
toStartOfMillisecond
toStartOfNanosecond
toString
toStringCutToZero
toTime
@ -2805,7 +2820,6 @@ urls
usearch
userspace
userver
UTCTimestamp
utils
uuid
uuidv