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title seotitle description menu weight influxdb/cloud-iox/tags related list_code_example
Aggregate or apply selector functions to data Perform a basic SQL query in InfluxDB Cloud Use aggregate and selector functions to perform aggregate operations on your time series data.
influxdb_cloud_iox
name parent identifier
Aggregate data Query with SQL query-sql-aggregate
203
query
sql
/influxdb/cloud-iox/reference/sql/functions/aggregate/
/influxdb/cloud-iox/reference/sql/functions/selector/
##### Aggregate fields by groups ```sql SELECT mean(field1) AS mean, selector_first(field2)['value'] as first, tag1 FROM home GROUP BY tag ``` ##### Aggregate by time-based intervals ```sql SELECT DATE_BIN(INTERVAL '1 hour', time, '2022-01-01T00:00:00Z'::TIMESTAMP) AS time, mean(field1), sum(field2), tag1 FROM home GROUP BY time, tag1 ```

A SQL query that aggregates data includes the following clauses:

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

  • {{< req "*">}} SELECT: Identify specific fields and tags to query from a measurement or use the wild card alias (*) to select all fields and tags from a measurement. Include any columns you want to group by in the SELECT clause.
  • {{< req "*">}} FROM: Identify the measurement to query data from.
  • WHERE: Only return data that meets defined conditions such as falling within a time range, containing specific tag values, etc.
  • GROUP BY: Group data into SQL partitions by specific columns and apply an aggregate or selector function to each group.

{{% note %}} For simplicity, the term "aggregate" in this guide refers to applying both aggregate and selector functions to a dataset. {{% /note %}}

Learn how to apply aggregate operations to your queried data:

Aggregate and selector functions

Both aggregate and selector functions return a single row from each SQL partition or 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.

View aggregate functions

Basic aggregate query
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.

View selector functions

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
{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 to populate the column value:

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

Example aggregate queries

{{% note %}}

Sample data

The following examples use the sample data written in the Get started writing data guide. To run the example queries and return results, write the sample data to your InfluxDB Cloud bucket before running the example queries. {{% /note %}}

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
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 data grouped:

  • 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 to group by
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 DATE_BIN to calculate windows of time based on a specified interval and update the timestamp in the time column based on the start boundary of the window that the original timestamp is in.
      For example, if you use DATE_BIN to window data into one day intervals, {{% influxdb/custom-timestamps-span %}}2022-01-01T12:34:56Z{{% /influxdb/custom-timestamps-span %}} will be updated to {{% influxdb/custom-timestamps-span %}}2022-01-01T00:00:00Z{{% /influxdb/custom-timestamps-span %}}.

    • Use aggregate or selector functions on specified columns.

    • Include columns to group by.

  • Include a GROUP BY clause with time and other columns to group by.

SELECT
  DATE_BIN(INTERVAL '2 hours', time, '1970-01-01T00:00:00Z'::TIMESTAMP) 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

{{< 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 >}}

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.

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 >}}