An SQL query that aggregates data includes the following clauses:

{{< req type="key" >}}

- {{< req "\*">}} `SELECT`: Specify fields, tags, and calculations to output from a
  table or use the wildcard alias (`*`) to select all fields and tags
  from a table.
- {{< req "\*">}} `FROM`: Specify the table to query data from.
- `WHERE`: Only return rows that meets the specified conditions--for example,
  the time is within a time range, a tag has a specific value, or a field value
  is above or below a specified threshold.
- `GROUP BY`: Group data that have the same values for specified columns and
  expressions (for example, an aggregate function result).

> [!Note]
> For simplicity, the verb, **"aggregate,"** in this guide refers to applying
> both aggregate and selector functions to a dataset.

Learn how to apply aggregate operations to your queried data:

- [Aggregate and selector functions](#aggregate-and-selector-functions)
  - [Aggregate functions](#aggregate-functions)
  - [Selector functions](#selector-functions)
- [Example aggregate queries](#example-aggregate-queries)

## Aggregate and selector functions

Both aggregate and selector functions return a single row from each SQL group.
For example, if you `GROUP BY room` and perform an aggregate operation
in your `SELECT` clause, results include an aggregate value for each unique
value of `room`.

### Aggregate functions

Use **aggregate functions** to aggregate values in a specified column for each
group and return a single row per group containing the aggregate value.

<a href="/influxdb3/version/reference/sql/functions/aggregate/" class="btn small">View SQL aggregate functions</a>

##### Basic aggregate query

```sql
SELECT AVG(co) from home
```

### Selector functions

Use **selector functions** to "select" a value from a specified column.
The available selector functions are designed to work with time series data.

<a href="/influxdb3/version/reference/sql/functions/selector/" class="btn small">View SQL selector functions</a>

Each selector function returns a Rust _struct_ (similar to a JSON object)
representing a single time and value from the specified column in the each group.
What time and value get returned depend on the logic in the selector function.
For example, `selector_first` returns the value of specified column in the first
row of the group. `selector_max` returns the maximum value of the specified
column in the group.

#### Selector struct schema

The struct returned from a selector function has two properties:

- **time**: `time` value in the selected row
- **value**: value of the specified column in the selected row

```js
{time: 2023-01-01T00:00:00Z, value: 72.1}
```

#### Use selector functions

Each selector function has two arguments:

- The first is the column to operate on.
- The second is the time column to use in the selection logic.

In your `SELECT` statement, execute a selector function and use bracket notation
to reference properties of the [returned struct](#selector-struct-schema) to
populate the column value:

```sql
SELECT
  selector_first(temp, time)['time'] AS time,
  selector_first(temp, time)['value'] AS temp,
  room
FROM home
GROUP BY room
```

## Example aggregate queries

- [Perform an ungrouped aggregation](#perform-an-ungrouped-aggregation)
- [Group and aggregate data](#group-and-aggregate-data)
  - [Downsample data by applying interval-based aggregates](#downsample-data-by-applying-interval-based-aggregates)
- [Query rows based on aggregate values](#query-rows-based-on-aggregate-values)

> [!Note]
> #### Sample data
> 
> The following examples use the
> [Home sensor sample data](/influxdb3/version/reference/sample-data/#home-sensor-data).
> To run the example queries and return results,
> [write the sample data](/influxdb3/version/reference/sample-data/#write-home-sensor-data-to-influxdb)
> to your {{% product-name %}} database before running the example queries.

### Perform an ungrouped aggregation

To aggregate _all_ queried values in a specified column:

- Use aggregate or selector functions in your `SELECT` statement.
- Do not include a `GROUP BY` clause to leave your data ungrouped.

```sql
SELECT avg(co) AS 'average co' from home
```

{{< expand-wrapper >}}
{{% expand "View example results" %}}
|    average co     |
| :---------------: |
| 5.269230769230769 |
{{% /expand %}}
{{< /expand-wrapper >}}

### Group and aggregate data

To apply aggregate or selector functions to grouped data:

- Use aggregate or selector functions in your `SELECT` statement.
- Include columns to group by in your `SELECT` statement.
- Include a `GROUP BY` clause with a comma-delimited list of columns and
  expressions to group by.

Keep the following in mind when using `GROUP BY`:

- `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` will use the original value of the column, not the
  transformed, aliased value.

```sql
SELECT
  room,
  avg(temp) AS 'average temp'
FROM home
GROUP BY room
```

{{< expand-wrapper >}}
{{% expand "View example results" %}}
| room        |       average temp |
| :---------- | -----------------: |
| Living Room |  22.16923076923077 |
| Kitchen     | 22.623076923076926 |
{{% /expand %}}
{{< /expand-wrapper >}}

#### Downsample data by applying interval-based aggregates

A common use case when querying time series is downsampling data by applying
aggregates to time-based groups. To group and aggregate data into time-based
groups:

- In your `SELECT` clause:

  - Use the [`DATE_BIN` function](/influxdb3/version/reference/sql/functions/time-and-date/#date_bin)
    to calculate time intervals and output a column that contains the start of
    the interval nearest to the `time` timestamp in each row--for example, the
    following clause calculates two-hour intervals (originating at the Unix epoch)
    and returns a new `time` column that contains the start of the interval
    nearest to `home.time`:
    
    ```sql
    SELECT
      DATE_BIN(INTERVAL '2 hours', time) AS time
    FROM home
    ...
    ```
    
    Given a `time` value
    {{% influxdb/custom-timestamps-span %}}`2022-01-01T13:00:50.000Z`{{% /influxdb/custom-timestamps-span %}},
    the output `time` column contains
    {{% influxdb/custom-timestamps-span %}}`2022-01-01T12:00:00.000Z`{{% /influxdb/custom-timestamps-span %}}.

  - Use [aggregate](/influxdb3/version/reference/sql/functions/aggregate/) or
    [selector](/influxdb3/version/reference/sql/functions/selector/) functions on
    specified columns.

- In your `GROUP BY` clause:
 
  - Specify the `DATE_BIN(...)` column ordinal reference (`1`).
    This lets you group by the transformed `time` value and maintain the `time`
    column name.
  - Specify other columns (for example, `room`) that are specified in the
    `SELECT` clause and aren't used in a selector function.

  ```sql
  SELECT
    DATE_BIN(INTERVAL '2 hours', time) AS time
  ...
  GROUP BY 1, room
  ...
  ```

  To reference the `DATE_BIN(...)` result column by _name_ in the `GROUP BY`
  clause, assign an alias other than "time" in the `SELECT` clause--for example:

  ```sql
  SELECT
    DATE_BIN(INTERVAL '2 hours', time) AS _time
  FROM home
  ...
  GROUP BY _time, room
  ```

- Include an `ORDER BY` clause with columns to sort by.

The following example retrieves unique combinations of time intervals and rooms
with their minimum, maximum, and average temperatures:

```sql
SELECT
  DATE_BIN(INTERVAL '2 hours', time) AS time,
  room,
  selector_max(temp, time)['value'] AS 'max temp',
  selector_min(temp, time)['value'] AS 'min temp',
  avg(temp) AS 'average temp'
FROM home
GROUP BY 1, room
ORDER BY room, 1
```

{{< expand-wrapper >}}
{{% expand "View example results" %}}
{{% influxdb/custom-timestamps %}}
| time                 | room        | max temp | min temp |       average temp |
| :------------------- | :---------- | -------: | -------: | -----------------: |
| 2022-01-01T08:00:00Z | Kitchen     |       23 |       21 |                 22 |
| 2022-01-01T10:00:00Z | Kitchen     |     22.7 |     22.4 | 22.549999999999997 |
| 2022-01-01T12:00:00Z | Kitchen     |     22.8 |     22.5 |              22.65 |
| 2022-01-01T14:00:00Z | Kitchen     |     22.8 |     22.7 |              22.75 |
| 2022-01-01T16:00:00Z | Kitchen     |     22.7 |     22.4 | 22.549999999999997 |
| 2022-01-01T18:00:00Z | Kitchen     |     23.3 |     23.1 | 23.200000000000003 |
| 2022-01-01T20:00:00Z | Kitchen     |     22.7 |     22.7 |               22.7 |
| 2022-01-01T08:00:00Z | Living Room |     21.4 |     21.1 |              21.25 |
| 2022-01-01T10:00:00Z | Living Room |     22.2 |     21.8 |                 22 |
| 2022-01-01T12:00:00Z | Living Room |     22.4 |     22.2 | 22.299999999999997 |
| 2022-01-01T14:00:00Z | Living Room |     22.3 |     22.3 |               22.3 |
| 2022-01-01T16:00:00Z | Living Room |     22.6 |     22.4 |               22.5 |
| 2022-01-01T18:00:00Z | Living Room |     22.8 |     22.5 |              22.65 |
| 2022-01-01T20:00:00Z | Living Room |     22.2 |     22.2 |               22.2 |
{{% /influxdb/custom-timestamps %}}
{{% /expand %}}
{{< /expand-wrapper >}}

> [!Note]
>
> #### GROUP BY time
> 
> In the `GROUP BY` clause, the name "time" always refers to the `time` column
> in the source table. If you want to reference a calculated time column by name,
> use an alias different from "time" or use the column ordinal--for example:
> 
> {{< code-tabs-wrapper >}}
{{% code-tabs %}}
[Column alias](#)
[Column ordinal](#)
{{% /code-tabs %}}
{{% code-tab-content %}}
```sql
SELECT
  DATE_BIN(INTERVAL '2 hours', time) AS _time,
  room,
  selector_max(temp, time)['value'] AS 'max temp',
  selector_min(temp, time)['value'] AS 'min temp',
  avg(temp) AS 'average temp'
FROM home
GROUP BY _time, room
ORDER BY room, _time
```
{{% /code-tab-content %}}
{{% code-tab-content %}}
```sql
SELECT
  DATE_BIN(INTERVAL '2 hours', time) AS time,
  room,
  selector_max(temp, time)['value'] AS 'max temp',
  selector_min(temp, time)['value'] AS 'min temp',
  avg(temp) AS 'average temp'
FROM home
GROUP BY 1, room
ORDER BY room, 1
```
{{% /code-tab-content %}}
{{< /code-tabs-wrapper >}}

### Query rows based on aggregate values

To query data based on values after an aggregate operation, include a `HAVING`
clause with defined predicate conditions such as a value threshold.
Predicates in the `WHERE` clause are applied _before_ data is aggregated.
Predicates in the `HAVING` clause are applied _after_ data is aggregated.

```sql
SELECT
  room,
  avg(co) AS 'average co'
FROM home
GROUP BY room
HAVING "average co" > 5
```

{{< expand-wrapper >}}
{{% expand "View example results" %}}
| room    |         average co |
| :------ | -----------------: |
| Kitchen | 6.6923076923076925 |
{{% /expand %}}
{{< /expand-wrapper >}}