Work with DB2 Data in Apache Spark Using SQL

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Rapidly create and deploy powerful Java applications that integrate with IBM DB2.

Access and process DB2 Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for DB2, Spark can work with live DB2 data. This article describes how to connect to and query DB2 data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live DB2 data due to optimized data processing built into the driver. When you issue complex SQL queries to DB2, the driver pushes supported SQL operations, like filters and aggregations, directly to DB2 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 DB2 data using native data types.

Install the CData JDBC Driver for DB2

Download the CData JDBC Driver for DB2 installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to DB2 Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for DB2 JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for DB2/lib/cdata.jdbc.db2.jar
  2. With the shell running, you can connect to DB2 with a JDBC URL and use the SQL Context load() function to read a table.

    Built-in Connection String Designer

    For assistance in constructing the JDBC URL, use the connection string designer built into the DB2 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

    java -jar cdata.jdbc.db2.jar

    Fill in the connection properties and copy the connection string to the clipboard.

    Configure the connection to DB2, using the connection string generated above.

    scala> val db2_df ="jdbc").option("url", "jdbc:db2:Server=;Port=50000;User=admin;Password=admin;Database=test;").option("dbtable","Orders").option("driver","cdata.jdbc.db2.DB2Driver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the DB2 data as a temporary table:

    scala> db2_df.registerTable("orders")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> db2_df.sqlContext.sql("SELECT OrderName, Freight FROM Orders WHERE ShipCity = New York").collect.foreach(println)

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

Using the CData JDBC Driver for DB2 in Apache Spark, you are able to perform fast and complex analytics on DB2 data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.