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

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

Install the CData JDBC Driver for xBase

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

Start a Spark Shell and Connect to xBase Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for xBase/lib/cdata.jdbc.xbase.jar
   

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

   The DataSource property must be set to the name of the folder that contains the .dbf files. Specify the IncludeFiles property to work with xBase table files having extensions that differ from .dbf. Specify multiple extensions in a comma-separated list.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.xbase.jar
   

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

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

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

   scala> val xbase_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:xbase:DataSource=MyDBFFilesFolder;").option("dbtable","Invoices").option("driver","cdata.jdbc.xbase.xBaseDriver").load()
   

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

4. Register the xBase data as a temporary table:

   scala> xbase_df.registerTable("invoices")

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

   scala> xbase_df.sqlContext.sql("SELECT Company, Total FROM Invoices WHERE Class = ASSET").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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