---
title: SELECT statements
description: Query syntax for data transformation in Cloudflare Pipelines SQL
image: https://developers.cloudflare.com/dev-products-preview.png
---

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# SELECT statements

SELECT statements are used to transform data in Cloudflare Pipelines. The general form is:

```
[WITH with_query [, ...]]SELECT select_expr [, ...]FROM from_item[WHERE condition]
```

A pipeline runs one or more `INSERT INTO sink SELECT ... FROM stream` statements. To write to multiple sinks from the same pipeline, separate the statements with semicolons. See [Multiple statements](#multiple-statements).

## WITH clause

The WITH clause allows you to define named subqueries that can be referenced in the main query. This can improve query readability by breaking down complex transformations.

Syntax:

```
WITH query_name AS (subquery) [, ...]
```

Simple example:

```
WITH filtered_events AS    (SELECT user_id, event_type, amount        FROM user_events WHERE amount > 50)SELECT user_id, amount * 1.1 as amount_with_taxFROM filtered_eventsWHERE event_type = 'purchase';
```

## SELECT clause

The SELECT clause is a comma-separated list of expressions, with optional aliases. Column names must be unique.

```
SELECT select_expr [, ...]
```

Examples:

```
-- Select specific columnsSELECT user_id, event_type, amount FROM events
-- Use expressions and aliasesSELECT    user_id,    amount * 1.1 as amount_with_tax,    UPPER(event_type) as event_type_upperFROM events
-- Select all columnsSELECT * FROM events
```

## FROM clause

The FROM clause specifies the data source for the query. It will be either a table name or subquery. The table name can be either a stream name or a table created in the WITH clause.

```
FROM from_item
```

Tables can be given aliases:

```
SELECT e.user_id, e.amountFROM user_events eWHERE e.event_type = 'purchase'
```

## WHERE clause

The WHERE clause filters data using boolean conditions. Predicates are applied to input rows.

```
WHERE condition
```

Examples:

```
-- Filter by field valueSELECT * FROM events WHERE event_type = 'purchase'
-- Multiple conditionsSELECT * FROM eventsWHERE event_type = 'purchase' AND amount > 50
-- String operationsSELECT * FROM eventsWHERE user_id LIKE 'user_%'
-- Null checksSELECT * FROM eventsWHERE description IS NOT NULL
```

## UNNEST operator

The UNNEST operator converts arrays into multiple rows. This is useful for processing list data types.

UNNEST restrictions:

* May only appear in the SELECT clause
* Only one array may be unnested per SELECT statement

Example:

```
SELECT    UNNEST([1, 2, 3]) as numbersFROM events;
```

This will produce:

```
+---------+| numbers |+---------+|       1 ||       2 ||       3 |+---------+
```

## Multiple statements

A pipeline can contain multiple `INSERT` statements, separated by semicolons. Each statement reads from a stream and writes to a sink. Use multiple statements to route events from a single stream into several sinks based on their content.

```
INSERT INTO purchases_sinkSELECT user_id, product_id, amount FROM eventsWHERE event_type = 'purchase';
INSERT INTO signups_sinkSELECT user_id, created_at FROM eventsWHERE event_type = 'signup';
```

To provide multiple statements with the Wrangler CLI, pass a file with the `--sql-file` flag:

Terminal window

```
npx wrangler pipelines create my-pipeline --sql-file pipeline.sql
```

For a worked example, refer to [Fan out a stream to multiple Iceberg tables](https://developers.cloudflare.com/pipelines/examples/bluesky-firehose-fanout/).

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