Calculates the sum of absolute values of a vector.
**Syntax**
```sql
L1Norm(vector)
```
Alias: `normL1`.
**Arguments**
-`vector` — [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
**Returned value**
- L1-norm or [taxicab geometry](https://en.wikipedia.org/wiki/Taxicab_geometry) distance.
Type: [UInt](../../sql-reference/data-types/int-uint.md), [Float](../../sql-reference/data-types/float.md) or [Decimal](../../sql-reference/data-types/decimal.md).
**Examples**
Query:
```sql
SELECT L1Norm((1, 2));
```
Result:
```text
┌─L1Norm((1, 2))─┐
│ 3 │
└────────────────┘
```
## L2Norm
Calculates the square root of the sum of the squares of the vector values.
**Syntax**
```sql
L2Norm(vector)
```
Alias: `normL2`.
**Arguments**
-`vector` — [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
**Returned value**
- L2-norm or [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance).
Calculates the root of `p`-th power of the sum of the absolute values of a vector in the power of `p`.
**Syntax**
```sql
LpNorm(vector, p)
```
Alias: `normLp`.
**Arguments**
-`vector` — [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`p` — The power. Possible values: real number in `[1; inf)`. [UInt](../../sql-reference/data-types/int-uint.md) or [Float](../../sql-reference/data-types/float.md).
Calculates the distance between two points (the values of the vectors are the coordinates) in `L1` space (1-norm ([taxicab geometry](https://en.wikipedia.org/wiki/Taxicab_geometry) distance)).
**Syntax**
```sql
L1Distance(vector1, vector2)
```
Alias: `distanceL1`.
**Arguments**
-`vector1` — First vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`vector2` — Second vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
Calculates the distance between two points (the values of the vectors are the coordinates) in Euclidean space ([Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)).
**Syntax**
```sql
L2Distance(vector1, vector2)
```
Alias: `distanceL2`.
**Arguments**
-`vector1` — First vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`vector2` — Second vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
Calculates the distance between two points (the values of the vectors are the coordinates) in `L_{inf}` space ([maximum norm](https://en.wikipedia.org/wiki/Norm_(mathematics)#Maximum_norm_(special_case_of:_infinity_norm,_uniform_norm,_or_supremum_norm))).
**Syntax**
```sql
LinfDistance(vector1, vector2)
```
Alias: `distanceLinf`.
**Arguments**
-`vector1` — First vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`vector1` — Second vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
Calculates the distance between two points (the values of the vectors are the coordinates) in `Lp` space ([p-norm distance](https://en.wikipedia.org/wiki/Norm_(mathematics)#p-norm)).
**Syntax**
```sql
LpDistance(vector1, vector2, p)
```
Alias: `distanceLp`.
**Arguments**
-`vector1` — First vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`vector2` — Second vector. [Tuple](../../sql-reference/data-types/tuple.md) or [Array](../../sql-reference/data-types/array.md).
-`p` — The power. Possible values: real number from `[1; inf)`. [UInt](../../sql-reference/data-types/int-uint.md) or [Float](../../sql-reference/data-types/float.md).
Calculates the unit vector of a given vector (the values of the tuple are the coordinates) in `L1` space ([taxicab geometry](https://en.wikipedia.org/wiki/Taxicab_geometry)).
Type: [Tuple](../../sql-reference/data-types/tuple.md) of [Float](../../sql-reference/data-types/float.md).
**Example**
Query:
```sql
SELECT L1Normalize((1, 2));
```
Result:
```text
┌─L1Normalize((1, 2))─────────────────────┐
│ (0.3333333333333333,0.6666666666666666) │
└─────────────────────────────────────────┘
```
## L2Normalize
Calculates the unit vector of a given vector (the values of the tuple are the coordinates) in Euclidean space (using [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)).
Type: [Tuple](../../sql-reference/data-types/tuple.md) of [Float](../../sql-reference/data-types/float.md).
**Example**
Query:
```sql
SELECT L2Normalize((3, 4));
```
Result:
```text
┌─L2Normalize((3, 4))─┐
│ (0.6,0.8) │
└─────────────────────┘
```
## LinfNormalize
Calculates the unit vector of a given vector (the values of the tuple are the coordinates) in `L_{inf}` space (using [maximum norm](https://en.wikipedia.org/wiki/Norm_(mathematics)#Maximum_norm_(special_case_of:_infinity_norm,_uniform_norm,_or_supremum_norm))).
Type: [Tuple](../../sql-reference/data-types/tuple.md) of [Float](../../sql-reference/data-types/float.md).
**Example**
Query:
```sql
SELECT LinfNormalize((3, 4));
```
Result:
```text
┌─LinfNormalize((3, 4))─┐
│ (0.75,1) │
└───────────────────────┘
```
## LpNormalize
Calculates the unit vector of a given vector (the values of the tuple are the coordinates) in `Lp` space (using [p-norm](https://en.wikipedia.org/wiki/Norm_(mathematics)#p-norm)).
-`p` — The power. Possible values: any number from [1;inf). [UInt](../../sql-reference/data-types/int-uint.md) or [Float](../../sql-reference/data-types/float.md).
**Returned value**
- Unit vector.
Type: [Tuple](../../sql-reference/data-types/tuple.md) of [Float](../../sql-reference/data-types/float.md).
**Example**
Query:
```sql
SELECT LpNormalize((3, 4),5);
```
Result:
```text
┌─LpNormalize((3, 4), 5)──────────────────┐
│ (0.7187302630182624,0.9583070173576831) │
└─────────────────────────────────────────┘
```
## cosineDistance
Calculates the cosine distance between two vectors (the values of the tuples are the coordinates). The less the returned value is, the more similar are the vectors.