Work with Btrieve Data in Apache Spark Using SQL

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Btrieve JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Pervasive SQL (Btrieve) databases.



Access and process Btrieve 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 Btrieve, Spark can work with live Btrieve data. This article describes how to connect to and query Btrieve data from a Spark shell.

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

Install the CData JDBC Driver for Btrieve

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

Start a Spark Shell and Connect to Btrieve Data

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

    The PSQL v13 client will need to be installed on the same machine as the driver. To connect, set the User, Password, Server, and Database properties.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.btrieve.jar

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

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

    scala> val btrieve_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:btrieve:User=myuser;Password=mypassword;Server=myserver;Database=mydatabase;").option("dbtable","Billing").option("driver","cdata.jdbc.btrieve.BtrieveDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Btrieve data as a temporary table:

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

    scala> btrieve_df.sqlContext.sql("SELECT Student_ID, Transaction_Number FROM Billing WHERE Student_ID = 22").collect.foreach(println)

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

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