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Work with Sybase Data in Apache Spark Using SQL

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

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

Install the CData JDBC Driver for Sybase

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

Start a Spark Shell and Connect to Sybase Data

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

    To authenticate with Sybase, set User and Password. Additionally, set IntegratedSecurity; to true to use Windows authentication otherwise, Sybase authentication is used. Set the Server and Database properties. To secure connections with TLS/SSL, set Encrypt to true.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.sybase.jar

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

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

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

    scala> sybase_df.sqlContext.sql("SELECT Id, ProductName FROM Products WHERE ProductName = Konbu").collect.foreach(println)

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

Using the CData JDBC Driver for Sybase in Apache Spark, you are able to perform fast and complex analytics on Sybase data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 170+ CData JDBC Drivers and get started today.