# `setUnion`

## Description

Returns the union of two arrays, producing a new array that contains all unique elements from both.

- Both arrays are treated as sets:
- Duplicates are removed
- Order is not preserved in the result
- `null` is treated as an empty set
- Supported element types include `string`, `bool`, `number`, `interval`, `timestamp`, `regexp`, and `enum`.

## Syntax

Like many functions in DataPrime, `setUnion` supports [two notations](https://coralogix.com/docs/dataprime/language-reference/functions-reference/index.md), **function** and **method** notation. These interchangeable forms allow flexibility in how you structure expressions.

```dataprime
setUnion(array1: array<T>, array2: array<T>): array<T>
```

```dataprime
(array1: array<T>).setUnion(array2: array<T>): array<T>
```

## Arguments

| Name   | Type  | Required | Description                 |
| ------ | ----- | -------- | --------------------------- |
| array1 | array | **true** | The first array to combine  |
| array2 | array | **true** | The second array to combine |

## Example

**Use case: Combine processing and loading jobs into a unique set**

Suppose you have arrays of processing and loading jobs. Consider the following input:

```json
{
    "processing_jobs_waiting": ["job1", "job2", "job3", "job4"],
    "loading_jobs_waiting": ["job1", "job2", "job3"]
}
```

By applying `setUnion`, you can merge the two arrays and keep only unique jobs.

### Example query

```dataprime
create all_jobs from setUnion(processing_jobs_waiting, loading_jobs_waiting)
```

```dataprime
create all_jobs from processing_jobs_waiting.setUnion(loading_jobs_waiting)
```

### Example output

The result will include a new field `all_jobs` containing unique values from both arrays:

```json
{
    "processing_jobs_waiting": ["job1", "job2", "job3"],
    "loading_jobs_waiting": ["job1", "job2", "job3"],
    "all_jobs": ["job1", "job2", "job3", "job4"]
}
```