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Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Grafana data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Grafana data in Databricks.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Grafana data. When you issue complex SQL queries to Grafana, the driver pushes supported SQL operations, like filters and aggregations, directly to Grafana and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Grafana data using native data types.
To work with live Grafana data in Databricks, install the driver on your Databricks cluster.
With the JAR file installed, we are ready to work with live Grafana data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Grafana, and create a basic report.
Connect to Grafana by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.
driver = "cdata.jdbc.api.APIDriver" url = "jdbc:api:RTK=5246...;Profile=C:\profiles\Grafana.apip;ProfileSettings='Token=your_service_account_token;Domain=your_grafana_domain';"
For assistance in constructing the JDBC URL, use the connection string designer built into the Grafana JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.api.jar
Fill in the connection properties and copy the connection string to the clipboard.
Start by setting the Profile connection property to the location of the Grafana Profile on disk (e.g. C:\profiles\Grafana.apip). Next, set the ProfileSettings connection property to the connection string for Grafana (see below).
In Grafana, navigate to Administration > Users and Access > Service accounts, create a service account, then click Add service account token to generate a token.
👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)Once you configure the connection, you can load Grafana data as a dataframe using the CData JDBC Driver and the connection information.
remote_table = spark.read.format ( "jdbc" ) \ .option ( "driver" , driver) \ .option ( "url" , url) \ .option ( "dbtable" , "Alert") \ .load ()
Check the loaded Grafana data by calling the display function.
display (remote_table.select ("Id"))
👁 Displaying Grafana DataIf you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.
remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )
With the Temp View created, you can use SparkSQL to retrieve the Grafana data for reporting, visualization, and analysis.
% sql SELECT Id, Name FROM SAMPLE_VIEW ORDER BY Name DESC LIMIT 5👁 Displaying Grafana Data
The data from Grafana is only available in the target notebook. If you want to use it with other users, save it as a table.
remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )
Download a free, 30-day trial of the CData API Driver for JDBC and start working with your live Grafana data in Databricks. Reach out to our Support Team if you have any questions.
Connect to live data from Grafana with the API Driver
Connect to Grafana