How to write a Lucene query in Grafana?

@reagan_barton 

To write a Lucene query in Grafana, you can use the "Lucene Query" option in the query editor. Here is an example of how to use it:

1. In the Grafana interface, click on the "Explore" tab.
2. In the "Data source" dropdown, select the data source that you want to query.
3. In the "Metric" dropdown, select the metric that you want to query.
4. In the "Lucene Query" field, enter your Lucene query using the appropriate syntax.
5. Click the "Run Query" button to execute the query and display the results.

Here is an example of a simple Lucene query that searches for metrics with the term "request":

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request

You can also use advanced Lucene query syntax to specify multiple search terms, wildcards, and other search options. For example, the following query searches for metrics with the term "request" and the term "error", and returns only the results that contain both terms:

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request AND error

You can find more information about the Lucene query syntax and the available search options in the Lucene documentation.

@reagan_barton 

Grafana has deprecated Lucene queries with version 7.0 and above. However, you can still use the legacy Explore mode in Grafana to write Lucene queries. Follow these steps to use Lucene queries in Grafana:

1. Open Grafana and navigate to the Explore tab.
2. Select the data source you want to query from the drop-down list.
3. In the query editor, click on the "Switch to lucene syntax" link. This will enable the Lucene query mode.
4. Now you can write your Lucene query in the query editor. For example, to search for metrics with the term "request", you can use the following query: Metric contains "request"
5. Once you have written your query, click the "Run Query" button to execute the query and display the results.

Note: Lucene queries are legacy and have limited functionalities compared to the modern query languages like Elasticsearch Query DSL or PromQL. It is recommended to use Elasticsearch or Prometheus data sources along with their respective query languages for more advanced and flexible querying capabilities.