[jira] [Commented] (BEAM-1145) Remove classifier from shaded spark runner artifact

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/BEAM-1145?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15792940#comment-15792940 ] 

ASF GitHub Bot commented on BEAM-1145:
--------------------------------------

Github user asfgit closed the pull request at:

    https://github.com/apache/beam/pull/1594


> Remove classifier from shaded spark runner artifact
> ---------------------------------------------------
>
>                 Key: BEAM-1145
>                 URL: https://issues.apache.org/jira/browse/BEAM-1145
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-spark
>            Reporter: Aviem Zur
>            Assignee: Aviem Zur
>
> Shade plugin configured in spark runner's pom adds a classifier to spark runner shaded jar
> {code:xml}
> <shadedArtifactAttached>true</shadedArtifactAttached>
> <shadedClassifierName>spark-app</shadedClassifierName>
> {code}
> This means, that in order for a user application that is dependent on spark-runner to work in cluster mode, they have to add the classifier in their dependency declaration, like so:
> {code:xml}
>         <dependency>
>             <groupId>org.apache.beam</groupId>
>             <artifactId>beam-runners-spark</artifactId>
>             <version>0.4.0-incubating-SNAPSHOT</version>
>             <classifier>spark-app</classifier>
>         </dependency>
> {code}
> Otherwise, if they do not specify classifier, the jar they get is unshaded, which in cluster mode, causes collisions between different guava versions.
> Example exception in cluster mode when adding the dependency without classifier:
> {code}
> 16/12/12 06:58:56 WARN TaskSetManager: Lost task 4.0 in stage 8.0 (TID 153, lvsriskng02.lvs.paypal.com): java.lang.NoSuchMethodError: com.google.common.base.Stopwatch.createStarted()Lcom/google/common/base/Stopwatch;
> 	at org.apache.beam.runners.spark.stateful.StateSpecFunctions$1.apply(StateSpecFunctions.java:137)
> 	at org.apache.beam.runners.spark.stateful.StateSpecFunctions$1.apply(StateSpecFunctions.java:98)
> 	at org.apache.spark.streaming.StateSpec$$anonfun$1.apply(StateSpec.scala:180)
> 	at org.apache.spark.streaming.StateSpec$$anonfun$1.apply(StateSpec.scala:179)
> 	at org.apache.spark.streaming.rdd.MapWithStateRDDRecord$$anonfun$updateRecordWithData$1.apply(MapWithStateRDD.scala:57)
> 	at org.apache.spark.streaming.rdd.MapWithStateRDDRecord$$anonfun$updateRecordWithData$1.apply(MapWithStateRDD.scala:55)
> 	at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> 	at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
> 	at org.apache.spark.streaming.rdd.MapWithStateRDDRecord$.updateRecordWithData(MapWithStateRDD.scala:55)
> 	at org.apache.spark.streaming.rdd.MapWithStateRDD.compute(MapWithStateRDD.scala:155)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> 	at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:275)
> 	at org.apache.spark.streaming.rdd.MapWithStateRDD.compute(MapWithStateRDD.scala:149)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> 	at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:275)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> 	at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:275)
> 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:89)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745)
> {code}
> I would suggest that the classifier be removed from the shaded jar, to avoid confusion among users, and have a better user experience.
> P.S. Looks like Dataflow runner does not add a classifier to its shaded jar.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)