Hive on Spark: Getting Started

Spark Installation

Follow instructions to install Spark: https://spark.apache.org/docs/latest/spark-standalone.html.  In particular:

1. Install Spark (either download pre-built Spark, or build assembly from source).  
   • Install/build a compatible version.  Hive root pom.xml's <spark.version> defines what version of Spark it was built/tested with. 
   • Install/build a compatible distribution.  Each version of Spark has several distributions, corresponding with different versions of Hadoop.
   • Once Spark is installed, find and keep note of the <spark-assembly-*.jar> location.
   • If you download Spark pre-built you will need to replace the Spark 1.2.x assembly with http://ec2-50-18-79-139.us-west-1.compute.amazonaws.com/data/spark-assembly-1.2.0-SNAPSHOT-hadoop2.3.0-cdh5.1.2.jar
2. Start Spark cluster (Master and workers).
   • Keep note of the <Spark Master URL>.  This can be found in Spark master WebUI.

Configuring Hive

1. As Hive on Spark is still in development, currently only a Hive assembly built from the Hive/Spark development branch supports Spark execution.  The development branch is located here: https://github.com/apache/hive/tree/spark.  Checkout the branch and build the Hive assembly as described in https://cwiki.apache.org/confluence/display/Hive/HiveDeveloperFAQ.
2. If you download Spark, make sure you use a 1.2.x assembly: http://ec2-50-18-79-139.us-west-1.compute.amazonaws.com/data/spark-assembly-1.2.0-SNAPSHOT-hadoop2.3.0-cdh5.1.2.jar

3. Start Hive with <spark-assembly-*.jar> on the Hive auxpath:

   hive --auxpath /location/to/spark-assembly-*.jar

4. Configure Hive execution to Spark:

   hive> set hive.execution.engine=spark;

5. Configure Spark-application configs for Hive.  See: http://spark.apache.org/docs/latest/configuration.html.  This can be done either by adding a file "spark-defaults.conf" with these properties to the Hive classpath, or by setting them on Hive configuration:

   hive> set spark.master=<Spark Master URL>
   
   hive> set spark.eventLog.enabled=true;             
   
   hive> set spark.executor.memory=512m;              
   
   hive> set spark.serializer=org.apache.spark.serializer.KryoSerializer;

Common Issues