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- 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-build you will need to replace the spark 1.0.x assembly with http://ec2-50-18-79-139.us-west-1.compute.amazonaws.com/data/spark-assembly-1.1.0-SNAPSHOT-hadoop2.3.0.jar
- Start Spark cluster (Master and workers).
- Keep note of the <Spark Master URL>. This can be found in Spark master WebUI.
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- As Hive on Spark is still in development, currently only a Hive assembly built from hive/spark development branch supports Spark execution. The development branch is located here: https://github.com/apache/hive/tree/spark. Checkout branch and build hive assembly as described in https://cwiki.apache.org/confluence/display/Hive/HiveDeveloperFAQ.
- If you download spark, make sure you use a 1.1.x assembly: http://ec2-50-18-79-139.us-west-1.compute.amazonaws.com/data/spark-assembly-1.1.0-SNAPSHOT-hadoop2.3.0.jar
Start hive with <spark-assembly-*.jar> on the hive auxpath:
Code Block hive --auxpath /location/to/spark-assembly-*.jar
Configure hive execution to Spark:
Code Block hive> set hive.execution.engine=spark;
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:
Code Block 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;
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