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https://issues.apache.org/jira/browse/BEAM-1145?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Aviem Zur reassigned BEAM-1145:
-------------------------------

    Assignee: Aviem Zur  (was: Amit Sela)

> 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.



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