> For the complete documentation index, see [llms.txt](https://docs.lenses.io/latest/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lenses.io/latest/user-guide/6.2-user-guide/using/using-sql-to-query-kafka/arrays.md).

# Arrays

Understand querying arrays in Kafka topic data with Lenses SQL Snapshot concepts engine for Apache Kafka

#### Create an array field

You can create array fields using the `..[]` syntax:

```sql
CREATE TABLE table(
    _key INT,
    , fialdA INT[]            -- Simple array
    , fieldB.fieldC STRING[]) -- Array in a subfield
    , fieldD INT[][]          -- Nested array
FORMAT(avro, avro);
```

#### Select an array field

Tables can store data containing arrays. Here is a SQL statement for querying an array item:

```sql
SELECT
    fieldA[1]
     , fieldB.fieldC[2].x
FROM table
WHERE fieldA[1] LIKE '%Lenses%'
```

When working with arrays is good to check the array bounds. See the `SIZEOF` function in the list of supported functions.

#### Query for array size

Sometimes you want to find out how many items are in your array. To do so you can run:

{% code overflow="wrap" %}

```sql
SELECT
    SIZEOF(arrayFieldA)
FROM table
```

{% endcode %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.lenses.io/latest/user-guide/6.2-user-guide/using/using-sql-to-query-kafka/arrays.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.