How to work with Onfleet 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 Onfleet, Spark can work with live Onfleet data. This article describes how to connect to and query Onfleet data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Onfleet data due to optimized data processing built into the driver. When you issue complex SQL queries to Onfleet, the driver pushes supported SQL operations, like filters and aggregations, directly to Onfleet 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 Onfleet data using native data types.

Install the CData JDBC Driver for Onfleet

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

Start a Spark Shell and Connect to Onfleet Data

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

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

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

   Onfleet uses HTTP ApiKey Authentication. Your Onfleet API Key is used to authenticate requests. You can generate or view your API Key in the Onfleet dashboard under Settings > API.

   Using ApiKey Authentication

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your Onfleet API Key.

   Example connection string:

   Profile=C:\profiles\Onfleet.apip;AuthScheme=APIKey;ProfileSettings="ApiKey=your_api_key";
   

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Onfleet 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 Onfleet, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Onfleet.apip;AuthScheme=APIKey;ProfileSettings="ApiKey=your_api_key";").option("dbtable","Administrators").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 Onfleet data as a temporary table:

   scala> api_df.registerTable("administrators")

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

   scala> api_df.sqlContext.sql("SELECT ,  FROM Administrators WHERE  = ").collect.foreach(println)

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

   

Using the CData JDBC Driver for Onfleet in Apache Spark, you are able to perform fast and complex analytics on Onfleet 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.