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ASF GitHub Bot commented on BEAM-1145: -------------------------------------- GitHub user aviemzur opened a pull request: https://github.com/apache/incubator-beam/pull/1594 [BEAM-1145] Remove classifier from shaded spark runner artifact Be sure to do all of the following to help us incorporate your contribution quickly and easily: - [ ] Make sure the PR title is formatted like: `[BEAM-<Jira issue #>] Description of pull request` - [ ] Make sure tests pass via `mvn clean verify`. (Even better, enable Travis-CI on your fork and ensure the whole test matrix passes). - [ ] Replace `<Jira issue #>` in the title with the actual Jira issue number, if there is one. - [ ] If this contribution is large, please file an Apache [Individual Contributor License Agreement](https://www.apache.org/licenses/icla.txt). --- You can merge this pull request into a Git repository by running: $ git pull https://github.com/aviemzur/incubator-beam remove-spark-runner-shaded-artifact-classifier Alternatively you can review and apply these changes as the patch at: https://github.com/apache/incubator-beam/pull/1594.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #1594 ---- commit 0b4a65374629b6490b68db3348de427bc2f14e0a Author: Aviem Zur <aviem...@gmail.com> Date: 2016-12-13T15:22:46Z [BEAM-1145] Remove classifier from shaded spark runner artifact ---- > 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: Amit Sela > > 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)