Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.
Databricks datasource for Grafana
The Databricks datasource allows a direct connection to Databricks to query and visualize Databricks data in Grafana.
This datasource provides a SQL editor to format and color code your SQL statements.
Note: This plugin is for Grafana Enterprise only.
For detailed instructions on how to install the plugin on Grafana Cloud or locally, please checkout the Plugin installation docs.
Once the plugin is installed on your Grafana instance, follow these instructions to add a new Databricks data source, and enter configuration options.
With a configuration file
It is possible to configure data sources using configuration files with Grafana’s provisioning system. To read about how it works, including all the settings that you can set for this data source, refer to Provisioning Grafana data sources.
Here are some provisioning examples for this data source using basic authentication:
apiVersion: 1 datasources: - name: Databricks type: grafana-databricks-datasource jsonData: host: community.cloud.databricks.com port: 443 uid: username/token httpPath: path-from-databricks-odbc-settings secureJsonData: pwd: password/personal-token
Time series visualization options are selectable after adding a
field type to your query. This field will be used as the timestamp. You can
select time series visualizations using the visualization options. Grafana
interprets timestamp rows without explicit time zone as UTC. Any column except
time is treated as a value column.
Multi-line time series
To create multi-line time series, the query must return at least 3 fields in the following order:
- field 1:
datetimefield with an alias of
- field 2: value to group by
- field 3+: the metric values
SELECT log_time AS time, machine_group, avg(disk_free) AS avg_disk_free FROM mgbench.logs1 GROUP BY machine_group, log_time ORDER BY log_time
Templates and variables
To add a new Databricks query variable, refer to Add a query variable.
After creating a variable, you can use it in your Databricks queries by using Variable syntax. For more information about variables, refer to Templates and variables.
Macros in Databricks Query
|Converts Grafana’s interval to INTERVAL DAY TO SECOND literal. Applicable to Spark SQL window grouping expression.|
In some cases, you may want to use window grouping with Spark SQL.
SELECT window.start, avg(aggqueue) FROM a17 GROUP BY window(_time, '$__interval_long')
will be translated into the following query based on dashboard interval.
SELECT window.start, avg(aggqueue) FROM a17 GROUP BY window(_time, '2 MINUTE')
Below are examples when grafana has a
- Add Annotations.
- Configure and use Templates and variables.
- Add Transformations.
- Set up alerting; refer to Alerts overview.