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From "JoneZhang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-9970) Hive on spark
Date Thu, 16 Jul 2015 02:05:04 GMT

    [ https://issues.apache.org/jira/browse/HIVE-9970?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14629068#comment-14629068
] 

JoneZhang commented on HIVE-9970:
---------------------------------

1.Make sure  build spark without hive.
If there is the following directory in spark-assembly-*-hadoop*.jar,this is not allowed.
spark-assembly-*-hadoop*.jar\org\apache\hive   
spark-assembly-*-hadoop*.jar\org\apache\hadoop\hive 
2. See if there is an older version of hive jar under CLASSPATH.Remove it If there exists.

> Hive on spark
> -------------
>
>                 Key: HIVE-9970
>                 URL: https://issues.apache.org/jira/browse/HIVE-9970
>             Project: Hive
>          Issue Type: Bug
>            Reporter: Amithsha
>
> Hi all,
> Recently i have configured Spark 1.2.0 and my environment is hadoop
> 2.6.0 hive 1.1.0 Here i have tried hive on Spark while executing
> insert into i am getting the following g error.
> Query ID = hadoop2_20150313162828_8764adad-a8e4-49da-9ef5-35e4ebd6bc63
> Total jobs = 1
> Launching Job 1 out of 1
> In order to change the average load for a reducer (in bytes):
> set hive.exec.reducers.bytes.per.reducer=<number>
> In order to limit the maximum number of reducers:
> set hive.exec.reducers.max=<number>
> In order to set a constant number of reducers:
> set mapreduce.job.reduces=<number>
> Failed to execute spark task, with exception
> 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create
> spark client.)'
> FAILED: Execution Error, return code 1 from
> org.apache.hadoop.hive.ql.exec.spark.SparkTask
> Have added the spark-assembly jar in hive lib
> And also in hive console using the command add jar followed by the steps
> set spark.home=/opt/spark-1.2.1/;
> add jar /opt/spark-1.2.1/assembly/target/scala-2.10/spark-assembly-1.2.1-hadoop2.4.0.jar;
> set hive.execution.engine=spark;
> set spark.master=spark://xxxxxxx:7077;
> set spark.eventLog.enabled=true;
> set spark.executor.memory=512m;
> set spark.serializer=org.apache.spark.serializer.KryoSerializer;
> Can anyone suggest!!!!
> Thanks & Regards
> Amithsha



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