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https://issues.apache.org/jira/browse/BEAM-6812?focusedWorklogId=216433&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-216433
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ASF GitHub Bot logged work on BEAM-6812:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 20/Mar/19 19:49
            Start Date: 20/Mar/19 19:49
    Worklog Time Spent: 10m 
      Work Description: jhalaria commented on pull request #8042: [BEAM-6812]: 
Convert keys to ByteArray in Combine.perKey to make sure hashCode is consistent
URL: https://github.com/apache/beam/pull/8042#discussion_r267517341
 
 

 ##########
 File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/TransformTranslator.java
 ##########
 @@ -569,8 +569,8 @@ private static Partitioner 
getPartitioner(EvaluationContext context) {
     Long bundleSize =
         
context.getSerializableOptions().get().as(SparkPipelineOptions.class).getBundleSize();
     return (bundleSize > 0)
-        ? null
-        : new HashPartitioner(context.getSparkContext().defaultParallelism());
+        ? new HashPartitioner(context.getSparkContext().defaultParallelism())
+        : null;
 
 Review comment:
   I see. I reverted back the changes made to `getPartition`
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 216433)
    Time Spent: 2h 20m  (was: 2h 10m)

> Convert keys to ByteArray in Combine.perKey for Spark
> -----------------------------------------------------
>
>                 Key: BEAM-6812
>                 URL: https://issues.apache.org/jira/browse/BEAM-6812
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Ankit Jhalaria
>            Assignee: Ankit Jhalaria
>            Priority: Critical
>          Time Spent: 2h 20m
>  Remaining Estimate: 0h
>
> * During calls to Combine.perKey, we want they keys used to have consistent 
> hashCode when invoked from different JVM's.
>  * However, while testing this in our company we found out that when using 
> protobuf as keys during combine, the hashCodes can be different for the same 
> key when invoked from different JVMs. This results in duplicates. 
>  * `ByteArray` class in Spark has a stable has code when dealing with arrays 
> as well. 
>  * GroupByKey correctly converts keys to `ByteArray` and uses coders for 
> serialization.
>  * The fix does something similar when dealing with combines.



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