# `arrayConcat`

## Description

Returns a new array by concatenating the elements of two arrays into a single array.

- Both arrays must be of the same element type.
- Supported element types include `string`, `bool`, `number`, `interval`, `timestamp`, `regexp`, and `enum`.

## Syntax

Like many functions in DataPrime, `arrayConcat` 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
arrayConcat(array1: array<T>, array2: array<T>): array<T>
```

```dataprime
(array1: array<T>).arrayConcat(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 job queues into a single view**

Suppose you want to view both processing and loading jobs in a single list. Consider the following input:

```json
{
    "processing_jobs_waiting": ["job1", "job2", "job3"],
    "loading_jobs_waiting": ["loading_job1", "loading_job2", "loading_job3"]
}
```

By concatenating the arrays, you can see all jobs together in one array for simplified analysis.

### Example query

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

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

### Example output

The result will combine both arrays:

```json
{
    "processing_jobs_waiting": ["job1", "job2", "job3"],
    "loading_jobs_waiting": ["loading_job1", "loading_job2", "loading_job3"],
    "all_jobs": ["job1", "job2", "job3", "loading_job1", "loading_job2", "loading_job3"]
}
```