Query data with SQL
Learn to query data stored in InfluxDB using SQL.
- Explore your schema with SQL
- Perform a basic SQL query
- Aggregate or apply selector functions to data
- Cast values to different types
- Fill gaps in data
Explore your schema with SQL
When working with InfluxDB’s implementation of SQL, a measurement is structured as a table, and time, fields, and tags are structured as columns.
List measurements
SHOW TABLES
List columns in a measurement
SHOW COLUMNS IN measurement
Perform a basic SQL query
A basic SQL query that queries data from InfluxDB most commonly includes SELECT, FROM, and WHERE clauses.
SELECT temp, room FROM home WHERE time >= now() - INTERVAL '1 day'
Aggregate or apply selector functions to data
Use aggregate and selector functions to perform aggregate operations on your time series data.
Aggregate fields by groups
SELECT
mean(field1) AS mean,
selector_first(field2)['value'] as first,
tag1
FROM home
GROUP BY tag
Aggregate by time-based intervals
SELECT
DATE_BIN(INTERVAL '1 hour', time, '2022-01-01T00:00:00Z'::TIMESTAMP) AS time,
mean(field1),
sum(field2),
tag1
FROM home
GROUP BY
DATE_BIN(INTERVAL '1 hour', time, '2022-01-01T00:00:00Z'::TIMESTAMP),
tag1
Cast values to different types
Use the CAST function or double-colon :: casting shorthand syntax to cast a value to a specific type.
-- CAST clause
SELECT CAST(1234.5 AS BIGINT)
-- Double-colon casting shorthand
SELECT 1234.5::BIGINT
Fill gaps in data
Use date_bin_gapfill with interpolate or locf to fill gaps of time where no data is returned.
SELECT
date_bin_gapfill(INTERVAL '30 minutes', time) as _time,
room,
interpolate(avg(temp))
FROM home
WHERE
time >= '2022-01-01T08:00:00Z'
AND time <= '2022-01-01T10:00:00Z'
GROUP BY _time, room
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Support and feedback
Thank you for being part of our community! We welcome and encourage your feedback and bug reports for InfluxDB and this documentation. To find support, use the following resources:
InfluxDB Cloud and InfluxDB Enterprise customers can contact InfluxData Support.