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- There are several ways to add the Spark dependency to Hive:
Set the property 'spark.home' to point to the Spark installation:
Code Block hive> set spark.home=/location/to/sparkHome;
Define the SPARK_HOME environment variable before starting Hive CLI/HiveServer2:
Code Block language bash export SPARK_HOME=/usr/lib/spark....
- Link the spark-assembly jar to
HIVE_HOME/lib.
Configure Hive execution to Spark:
Code Block hive> set hive.execution.engine=spark;
See the Spark section of Hive Configuration Properties for other properties for configuring Hive and the Remote Spark Driver.
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-site.xml). For instance:Code Block hive> set spark.master=<Spark Master URL> hive> set spark.eventLog.enabled=true; hive> set spark.eventLog.dir=<Spark event log folder (must exist)> hive> set spark.executor.memory=512m; hive> set spark.serializer=org.apache.spark.serializer.KryoSerializer;
A little explanation for some of the configuration properties:
spark.executor.memory: Amount of memory to use per executor process.spark.executor.cores: Number of cores per executor.spark.yarn.executor.memoryOverhead: The amount of off heap memory (in megabytes) to be allocated per executor, when running Spark on Yarn. This is memory that accounts for things like VM overheads, interned strings, other native overheads, etc. In addition to the executor's memory, the container in which the executor is launched needs some extra memory for system processes, and this is what this overhead is for.spark.executor.instances: The number of executors assigned to each application.spark.driver.memory: The amount of memory assigned to the Remote Spark Context (RSC). We recommend 4GB.spark.yarn.driver.memoryOverhead: We recommend 400 (MB).
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