How to work with Grafana Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Grafana, Spark can work with live Grafana data. This article describes how to connect to and query Grafana data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Grafana data due to optimized data processing built into the driver. 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 (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze Grafana data using native data types.

Install the CData JDBC Driver for Grafana

Download the CData JDBC Driver for Grafana installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Grafana Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Grafana JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for Grafana/lib/cdata.jdbc.api.jar
   

2. With the shell running, you can connect to Grafana with a JDBC URL and use the SQL Context load() function to read a table.

   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).

   Grafana API Profile Settings

   In Grafana, navigate to Administration > Users and Access > Service accounts, create a service account, then click Add service account token to generate a token.

   Built-in Connection String Designer

   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.

   

   Configure the connection to Grafana, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Grafana.apip;ProfileSettings='Token=your_service_account_token;Domain=your_grafana_domain';").option("dbtable","Alert").option("driver","cdata.jdbc.api.APIDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Grafana data as a temporary table:

   scala> api_df.registerTable("alert")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> api_df.sqlContext.sql("SELECT Id, Name FROM Alert WHERE State = alerting").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   

Using the CData JDBC Driver for Grafana in Apache Spark, you are able to perform fast and complex analytics on Grafana data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.