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

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

Install the CData JDBC Driver for HBase

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

Start a Spark Shell and Connect to HBase Data

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

   Set the Port and Server to connect to Apache HBase.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.apachehbase.jar

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

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

   scala> val apachehbase_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:apachehbase:Server=127.0.0.1;Port=8080;").option("dbtable","Customers").option("driver","cdata.jdbc.apachehbase.ApacheHBaseDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the HBase data as a temporary table:

   scala> apachehbase_df.registerTable("customers")

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

   scala> apachehbase_df.sqlContext.sql("SELECT CustomerName, Price FROM Customers 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 HBase in Apache Spark, you are able to perform fast and complex analytics on HBase 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.