The Axiom Processing Language (APL) is a query language that’s perfect for getting deeper insights from your data. Whether logs, events, analytics, or similar, APL provides the flexibility to filter, manipulate, and summarize your data exactly the way you need it.

​
Prerequisites

​
Build an APL query

APL queries consist of the following:
  • Data source: The most common data source is one of your Axiom datasets.
  • Operators: Operators filter, manipulate, and summarize your data.
Delimit operators with the pipe character (|). A typical APL query has the following structure: 
DatasetName
| Operator ...
| Operator ...
  • DatasetName is the name of the dataset you want to query.
  • Operator is an operation you apply to the data.
Apart from Axiom datasets, you can use other data sources:
  • External data sources using the externaldata operator.
  • Specify a data table in the APL query itself using the let statement.

​
Example query

['github-issue-comment-event']
| extend isBot = actor contains '-bot' or actor contains '[bot]'
| where isBot == true
| summarize count() by bin_auto(_time), actor
Run in Playground The query above uses a dataset called github-issue-comment-event as its data source. It uses the following operators:
  • extend adds a new field isBot to the query results. It sets the values of the new field to true if the values of the actor field in the original dataset contain -bot or [bot].
  • where filters for the values of the isBot field. It only returns rows where the value is true.
  • summarize aggregates the data and produces a chart.
Each operator is separated using the pipe character (|).

​
Example result

As a result, the query returns a chart and a table. The table counts the different values of the actor field where isBot is true, and the chart displays the distribution of these counts over time.
actorcount_
github-actions[bot]487
sonarqubecloud[bot]208
dependabot[bot]148
vercel[bot]91
codecov[bot]63
openshift-ci[bot]52
coderabbitai[bot]43
netlify[bot]37
The query results are a representation of your data based on your request. The query doesn’t change the original dataset.

​
Quote dataset and field names

If the name of a dataset or field contains at least one of the following special characters, quote the name in your APL query:
  • Space ( )
  • Dot (.)
  • Dash (-)
To quote the dataset or field in your APL query, enclose its name with quotation marks (' or ") and square brackets ([]). For example, ['my-field']. For more information on rules about naming and quoting entities, see Entity names.

​
What’s next

Check out the list of sample queries or explore the supported operators and functions: