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Vector Functions | GreptimeDB Documentation

Vector Functions

This page lists all supported vector-related functions in GreptimeDB. Vector functions are primarily used for handling vector operations, such as basic arithmetic, distance calculations, conversion functions, and more.

Basic Operations vec_scalar_add

Adds a scalar to a vector. Each element in the vector is added to the scalar, returning a new vector.

Examples:

SELECT vec_to_string(vec_scalar_add(2.0, parse_vec('[1.0, 2.0, 3.0]')));

+
| vec_to_string(vec_scalar_add(Float64(2),parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [3,4,5]                                                                      |
+

SELECT vec_to_string(vec_scalar_add(2.0, '[1.0, 2.0, 3.0]')); -- Implicitly convert string to vector

+
| vec_to_string(vec_scalar_add(Float64(2),Utf8("[1.0, 2.0, 3.0]"))) |
+
| [3,4,5]                                                           |
+

SELECT vec_to_string(vec_scalar_add(-2.0, parse_vec('[1.0, 2.0, 3.0]'))); -- Subtraction

+
| vec_to_string(vec_scalar_add(Float64(-2),parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [-1,0,1]                                                                      |
+

vec_scalar_mul

Multiplies a vector by a scalar. Each element in the vector is multiplied by the scalar, returning a new vector.

Examples:

SELECT vec_to_string(vec_scalar_mul(2.0, parse_vec('[1.0, 2.0, 3.0]')));

+
| vec_to_string(vec_scalar_mul(Float64(2),parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [2,4,6]                                                                      |
+

SELECT vec_to_string(vec_scalar_mul(2.0, '[1.0, 2.0, 3.0]'));

+
| vec_to_string(vec_scalar_mul(Float64(2),parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [2,4,6]                                                                      |
+

SELECT vec_to_string(vec_scalar_mul(1.0/2.0, parse_vec('[1.0, 2.0, 3.0]')));

+
| vec_to_string(vec_scalar_mul(Float64(1) / Float64(2),parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [0.5,1,1.5]                                                                               |
+

vec_add

Adds two vectors element-wise. Returns a new vector where each element is the sum of corresponding elements in the input vectors.

Examples:

SELECT vec_to_string(vec_add(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]')));

+
| vec_to_string(vec_add(parse_vec(Utf8("[1.0, 2.0, 3.0]")),parse_vec(Utf8("[2.0, 1.0, 4.0]")))) |
+
| [3,3,7]                                                                                       |
+

SELECT vec_to_string(vec_add('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]'));

+
| vec_to_string(vec_add(Utf8("[1.0, 2.0, 3.0]"),Utf8("[2.0, 1.0, 4.0]"))) |
+
| [3,3,7]                                                                 |
+

vec_sub

Subtracts two vectors element-wise. Returns a new vector where each element is the difference of corresponding elements in the input vectors.

Examples:

SELECT vec_to_string(vec_sub(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]')));

+
| vec_to_string(vec_sub(parse_vec(Utf8("[1.0, 2.0, 3.0]")),parse_vec(Utf8("[2.0, 1.0, 4.0]")))) |
+
| [-1,1,-1]                                                                                     |
+

SELECT vec_to_string(vec_sub('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]'));

+
| vec_to_string(vec_sub(Utf8("[1.0, 2.0, 3.0]"),Utf8("[2.0, 1.0, 4.0]"))) |
+
| [-1,1,-1]                                                               |
+

vec_mul

Multiplies two vectors element-wise. Returns a new vector where each element is the product of corresponding elements in the input vectors.

Examples:

SELECT vec_to_string(vec_mul(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]')));

+
| vec_to_string(vec_mul(parse_vec(Utf8("[1.0, 2.0, 3.0]")),parse_vec(Utf8("[2.0, 1.0, 4.0]")))) |
+
| [2,2,12]                                                                                      |
+

SELECT vec_to_string(vec_mul('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]'));

+
| vec_to_string(vec_mul(Utf8("[1.0, 2.0, 3.0]"),Utf8("[2.0, 1.0, 4.0]"))) |
+
| [2,2,12]                                                                |
+

vec_div

Divides two vectors element-wise. Returns a new vector where each element is the quotient of corresponding elements in the input vectors.

Examples:

SELECT vec_to_string(vec_div(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]')));

+
| vec_to_string(vec_div(parse_vec(Utf8("[1.0, 2.0, 3.0]")),parse_vec(Utf8("[2.0, 1.0, 4.0]")))) |
+
| [0.5,2,0.75]                                                                                  |
+

SELECT vec_to_string(vec_div('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]'));

+
| vec_to_string(vec_div(Utf8("[1.0, 2.0, 3.0]"),Utf8("[2.0, 1.0, 4.0]"))) |
+
| [0.5,2,0.75]                                                            |
+

vec_elem_sum

Sums all elements of a vector, returning a scalar value.

Examples:

SELECT vec_elem_sum(parse_vec('[1.0, 2.0, 3.0]'));

+
| vec_elem_sum(parse_vec(Utf8("[1.0, 2.0, 3.0]"))) |
+
|                                                6 |
+

SELECT vec_elem_sum('[1.0, 2.0, 3.0]');

+
| vec_elem_sum(Utf8("[1.0, 2.0, 3.0]")) |
+
|                                     6 |
+

vec_elem_product

Computes the product of all elements in a vector, returning a scalar value.

Examples:

SELECT vec_elem_product(parse_vec('[1.0, 2.0, 3.0]'));

+
| vec_elem_product(parse_vec(Utf8("[1.0, 2.0, 3.0]"))) |
+
|                                                    6 |
+

SELECT vec_elem_product('[1.0, 2.0, 3.0]');

+
| vec_elem_product(Utf8("[1.0, 2.0, 3.0]")) |
+
|                                         6 |
+

vec_norm

Normalizes a vector. Divides each element of the vector by the L2 norm of the vector, returning a new unit vector.

Equivalent to vec_scalar_mul(1.0 / sqrt(vec_elem_sum(vec_mul(vec, vec))), vec).

Examples:

SELECT vec_to_string(vec_norm(parse_vec('[1.0, 2.0, 3.0]')));

+
| vec_to_string(vec_norm(parse_vec(Utf8("[1.0, 2.0, 3.0]")))) |
+
| [0.26726124,0.5345225,0.8017837]                            |
+

SELECT vec_to_string(vec_norm('[1.0, 2.0, 3.0]'));

+
| vec_to_string(vec_norm(Utf8("[1.0, 2.0, 3.0]"))) |
+
| [0.26726124,0.5345225,0.8017837]                 |
+

Aggregate Functions vec_sum

Sums all vectors in a vector column element-wise, returning a new vector.

Examples:

CREATE TABLE vectors (
    ts TIMESTAMP TIME INDEX,
    vec_col VECTOR(3),
);

INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:01', '[1.0, 2.0, 3.0]');
INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:02', '[2.0, 1.0, 4.0]');
INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:03', '[3.0, 3.0, 3.0]');

SELECT vec_to_string(vec_sum(vec_col)) FROM vectors;

+
| vec_to_string(vec_sum(vectors.vec_col)) |
+
| [6,6,10]                                |
+

vec_product

Multiplies all vectors in a vector column element-wise, returning a new vector.

Examples:

CREATE TABLE vectors (
    ts TIMESTAMP TIME INDEX,
    vec_col VECTOR(3),
);

INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:01', '[1.0, 2.0, 3.0]');
INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:02', '[2.0, 1.0, 4.0]');
INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:03', '[3.0, 3.0, 3.0]');

SELECT vec_to_string(vec_product(vec_col)) FROM vectors;

+
| vec_to_string(vec_product(vectors.vec_col)) |
+
| [6,6,36]                                    |
+

Distance Calculations

vec_l2sq_distance(vec1, vec2): Computes the squared L2 distance between two vectors.
vec_cos_distance(vec1, vec2): Computes the cosine distance between two vectors.
vec_dot_product(vec1, vec2): Computes the dot product of two vectors.

These functions accept vector values as parameters. You can use the parse_vec function to convert a string into a vector value, such as parse_vec('[1.0, 2.0, 3.0]'). Also, vector strings (e.g., [1.0, 2.0, 3.0]) can be used directly and will be automatically converted. Regardless of the method used, the dimensionality of the vectors must remain consistent.

vec_l2sq_distance

Calculates the squared Euclidean distance (squared L2 distance) between two vectors. L2 distance is the straight-line distance between two points in geometric space. This function returns the squared value to improve computational efficiency.

Example:

SELECT vec_l2sq_distance(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]'));

SELECT vec_l2sq_distance('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]');

Details:

Parameters are two vectors with consistent dimensions.
Output: A scalar value of type Float32.

vec_cos_distance

Calculates the cosine distance between two vectors. Cosine distance measures the cosine of the angle between two vectors and is used to quantify similarity.

Example:

SELECT vec_cos_distance(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]'));

SELECT vec_cos_distance('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]');

Details:

Parameters are two vectors with consistent dimensions.
Output: A scalar value of type Float32.

vec_dot_product

Computes the dot product of two vectors. The dot product is the sum of the element-wise multiplications of two vectors. It is commonly used to measure similarity or for linear transformations in machine learning.

Example:

SELECT vec_dot_product(parse_vec('[1.0, 2.0, 3.0]'), parse_vec('[2.0, 1.0, 4.0]'));

SELECT vec_dot_product('[1.0, 2.0, 3.0]', '[2.0, 1.0, 4.0]');

Details:

Parameters are two vectors with consistent dimensions.
Output: A scalar value of type Float32.

Conversion Functions

When dealing with vector data in the database, GreptimeDB provides convenient functions for converting between strings and vector values.

parse_vec

Converts a string to a vector value. The string must be enclosed in square brackets [] and contain elements of type Float32, separated by commas.

Example:

CREATE TABLE vectors (
    ts TIMESTAMP,
    vec_col VECTOR(3)
);

INSERT INTO vectors (ts, vec_col) VALUES ('2024-11-18 00:00:01', parse_vec('[1.0, 2.0, 3.0]'));

vec_to_string

Converts a vector object to a string. The converted string format is [<float32>, <float32>, ...].

Example:

SELECT vec_to_string(vec_col) FROM vectors;

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