# `COSINE_SIMILARITY`

**Applies to:** ✅ Data 360 SQL ✅ Tableau Hyper API

Computes the cosine similarity between two vectors, measuring directional alignment.

## Syntax

```sql
cosine_similarity(<array1>, <array2>)
```

## Arguments

### Required

- `<array1>`: The first vector (`array(real)` or `array(double-precision)`).
- `<array2>`: The second vector (`array(real)` or `array(double-precision)`).

## Returns

Returns a double-precision value between -1 and 1, where 1 indicates identical direction, 0 indicates orthogonal, and -1 indicates opposite direction.

## Considerations

- Both input arrays must be of the same element type and length.
- If any element is NULL, the result is NULL.
- Zero vectors cause division by zero.
- For optimal performance, use array definitions with non-nullable elements.

## Examples

### Calculate Cosine Similarity

Compute the cosine similarity between two vectors.

```sql
SELECT cosine_similarity(array[1, 2, 3], array[-1, 2, -3]) AS result;
```

Returns approximately `-0.42857`, indicating the vectors are somewhat opposed in direction.

## Related Documentation

- [Array Data Type](/docs/data/data-cloud-query-guide/references/dc-sql-reference/array.md)