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DocumentationPluginsDatabricks datasource for Grafana

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.

Note: This plugin uses dynamic links for Credentials authentication (deprecated). We suggest using Token authentication. If you run the plugin on bare Alpine Linux, using Credentials authentication it will not work. If for some reason Token based auth is not an option and Alpine Linux is a requirement, we suggest using our Alpine images.

Manual configuration

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
  - name: Databricks
    type: grafana-databricks-datasource
      port: 443
      uid: username/token
      httpPath: path-from-databricks-odbc-settings
      pwd: password/personal-token

Time series

Time series visualization options are selectable after adding a datetime 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: datetime field with an alias of time
  • field 2: value to group by
  • field 3+: the metric values

For example:

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

$____interval_longConverts Grafana’s interval to INTERVAL DAY TO SECOND literal. Applicable to Spark SQL window grouping expression.

$__interval_long macro

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')

Macro examples

Below are examples when grafana has a 1m interval.

FormatExpands to
$__interval_long1 MINUTE

Learn more