Hive on Spark: Getting Started
Spark Installation
Follow instructions to install Spark: https://spark.apache.org/docs/latest/spark-standalone.html. In particular:
- 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
- Start Spark cluster (Master and workers).
- Keep note of the <Spark Master URL>. This can be found in Spark master WebUI.
Configuring Hive
- 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.
- 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
There are several ways to add the Spark dependency to Hive:
Set the property 'spark.home' to point to the Spark installation:
hive> set spark.home=/location/to/sparkHome;
Set the spark-assembly jar on the Hive auxpath:
hive --auxpath /location/to/spark-assembly-*.jar
Add the spark-assembly jar for the current user session:
hive> add jar /location/to/spark-assembly-*.jar;
- Link the spark-assembly jar to HIVE_HOME/lib
Configure Hive execution to Spark:
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:
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 (Green are resolved, will be removed from this list)
Issue | Cause | Resolution |
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Error: Could not find or load main class org.apache.spark.deploy.SparkSubmit | Spark dependency not correctly set. | Add Spark dependency to Hive, see Step 3 above. |
org.apache.spark.SparkException: Job aborted due to stage failure: Task 5.0:0 had a not serializable result: java.io.NotSerializableException: org.apache.hadoop.io.BytesWritable | Spark serializer not set to Kryo. | Set spark.serializer to be org.apache.spark.serializer.KryoSerializer, see Step 5 above. |
[ERROR] Terminal initialization failed; falling back to unsupported | Hive has upgraded to Jline2 but jline 0.94 exists in the Hadoop lib. |
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java.lang.SecurityException: class "javax.servlet.DispatcherType"'s | Two versions of the servlet-api are in the classpath. |
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