Query InfluxDB with Flux
This guide walks through the basics of using Flux to query data from InfluxDB. Every Flux query needs the following:
1. Define your data source
2. Specify a time range
Flux requires a time range when querying time series data. “Unbounded” queries are very resource-intensive and as a protective measure, Flux will not query the database without a specified range.
Use the pipe-forward operator (
|>) to pipe data from your data source into the
function, which specifies a time range for your query.
It accepts two properties:
Ranges can be relative using negative durations
or absolute using timestamps.
Example relative time ranges
// Relative time range with start only. Stop defaults to now. from(bucket:"example-bucket") |> range(start: -1h) // Relative time range with start and stop from(bucket:"example-bucket") |> range(start: -1h, stop: -10m)
Relative ranges are relative to “now.”
Example absolute time range
from(bucket:"example-bucket") |> range(start: 2018-11-05T23:30:00Z, stop: 2018-11-06T00:00:00Z)
Use the following:
For this guide, use the relative time range,
-15m, to limit query results to data from the last 15 minutes:
from(bucket:"example-bucket") |> range(start: -15m)
3. Filter your data
Pass your ranged data into the
filter() function to narrow results based on data attributes or columns.
filter() function has one parameter,
fn, which expects an anonymous function
with logic that filters data based on columns or attributes.
Records or rows are passed into the
filter() function as an object (
The anonymous function takes the object and evaluates it to see if it matches the defined filters.
and relational operator to chain multiple filters.
// Pattern (r) => (r.objectProperty comparisonOperator comparisonExpression) // Example with single filter (r) => (r._measurement == "cpu") // Example with multiple filters (r) => (r._measurement == "cpu") and (r._field != "usage_system" )
Use the following:
For this example, filter by the
cpu measurement, the
usage_system field, and the
cpu-total tag value:
from(bucket:"example-bucket") |> range(start: -15m) |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system" and r.cpu == "cpu-total" )
4. Yield your queried data
yield() function to output the filtered tables as the result of the query.
from(bucket:"example-bucket") |> range(start: -15m) |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system" and r.cpu == "cpu-total" ) |> yield()
Flux automatically assume a
yield() function at
the end of each script in order to output and visualize the data.
yield() is only necessary when including multiple queries in the same Flux query.
Each set of returned data needs to be named using the
You have now queried data from InfluxDB using Flux. This is a barebones query that can be transformed in other ways.
Bug Reports and Feedback
Thank you for being willing to help test InfluxDB v2.0 alpha! Feedback and bug reports are welcome and encouraged both for InfluxDB and this documentation.