---
title: GROUP BY clause
description: Use the GROUP BY clause to group query data by column values.
url: https://docs.influxdata.com/influxdb3/cloud-serverless/reference/sql/group-by/
estimated_tokens: 753
publisher: InfluxData
canonical: https://docs.influxdata.com/influxdb3/cloud-serverless/reference/sql/group-by/
date: '2025-04-03T12:43:17-06:00'
lastmod: '2025-04-03T12:43:17-06:00'
---

Use the `GROUP BY` clause to group data by values.

`GROUP BY` is an optional clause used to group rows that have the same values for all columns and expressions in the list.
To output an aggregation for each group, include an aggregate or selector function in the `SELECT` statement.
When `GROUP BY` appears in a query, the `SELECT` list can only use columns that appear in the `GROUP BY` list
or in aggregate expressions.

#### Group by aliases

* `GROUP BY` can use column aliases that are defined in the `SELECT` clause.
* `GROUP BY` won’t use an aliased value if the alias is the same as the
  original column name. `GROUP BY` uses the original value of the column,
  not the transformed, aliased value. We recommended using column ordinals in
  in the `GROUP BY` clause to group by transformed values and maintain the
  alias identifier.

* [Syntax](#syntax)
* [Examples](#examples)

## Syntax

```sql
SELECT
  AGGREGATE_FN(field1),
  tag1
FROM measurement
GROUP BY tag1
```

## Examples

### Group data by tag values

```sql
SELECT
  AVG(water_level) AS avg_water_level,
  location
FROM h2o_feet
GROUP BY location
```

[](#view-example-results)

View example results

|avg\_water\_level|  location   |
|-----------------|-------------|
|5.359142420303919|coyote\_creek|
|3.530712094245885|santa\_monica|

### Group data into 15 minute time intervals by tag

```
SELECT
  location,
  DATE_BIN(INTERVAL '15 minutes', time) AS time,
  COUNT(water_level) AS count
FROM h2o_feet
WHERE
  time >= timestamp '2019-09-17T00:00:00Z'
  AND time <= timestamp '2019-09-17T01:00:00Z'
GROUP BY 1, location
ORDER BY location, 1
```

[](#view-example-results)

View example results

The query uses the `COUNT()` function to count the number of `water_level` points per 15 minute interval.
Results are then ordered by location and time.

|  location   |        time        |count|
|-------------|--------------------|-----|
|coyote\_creek|2019-09-16T23:45:00Z|  1  |
|coyote\_creek|2019-09-17T00:00:00Z|  2  |
|coyote\_creek|2019-09-17T00:15:00Z|  3  |
|coyote\_creek|2019-09-17T00:30:00Z|  2  |
|coyote\_creek|2019-09-17T00:45:00Z|  3  |
|santa\_monica|2019-09-16T23:45:00Z|  1  |
|santa\_monica|2019-09-17T00:00:00Z|  2  |
|santa\_monica|2019-09-17T00:15:00Z|  3  |
|santa\_monica|2019-09-17T00:30:00Z|  2  |
|santa\_monica|2019-09-17T00:45:00Z|  3  |
| avg_water_level | location |
| --- | --- |
| avg_water_level | location |
| 5.359142420303919 | coyote_creek |
| 3.530712094245885 | santa_monica |

| location | time | count |
| --- | --- | --- |
| location | time | count |
| coyote_creek | 2019-09-16T23:45:00Z | 1 |
| coyote_creek | 2019-09-17T00:00:00Z | 2 |
| coyote_creek | 2019-09-17T00:15:00Z | 3 |
| coyote_creek | 2019-09-17T00:30:00Z | 2 |
| coyote_creek | 2019-09-17T00:45:00Z | 3 |
| santa_monica | 2019-09-16T23:45:00Z | 1 |
| santa_monica | 2019-09-17T00:00:00Z | 2 |
| santa_monica | 2019-09-17T00:15:00Z | 3 |
| santa_monica | 2019-09-17T00:30:00Z | 2 |
| santa_monica | 2019-09-17T00:45:00Z | 3 |