[jira] [Commented] (FLINK-4586) NumberSequenceIterator and Accumulator threading issue

["Johannes (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-4586?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15468729#comment-15468729 ] 

Johannes commented on FLINK-4586:
---------------------------------

The testcase also fails, when just using a plain collection and a rebalance to create some form of a parallel collection

{code}
fromCollection(1 to 100).rebalance() 
{code}

So it seems to be not specific to the NumberSequenceIterator.

So either the initialization of the accumulator is wrong in the sample code, or there is a deeper issue.

> NumberSequenceIterator and Accumulator threading issue
> ------------------------------------------------------
>
>                 Key: FLINK-4586
>                 URL: https://issues.apache.org/jira/browse/FLINK-4586
>             Project: Flink
>          Issue Type: Bug
>          Components: DataSet API
>    Affects Versions: 1.1.2
>            Reporter: Johannes
>            Priority: Minor
>         Attachments: FLINK4586Test.scala
>
>
> There is a strange problem when using the NumberSequenceIterator in combination with an AverageAccumulator.
> It seems like the individual accumulators are reinitialized and overwrite parts of intermediate solutions.
> The following scala snippit exemplifies the problem.
> Instead of printing the correct average, the result should be {{50.5}} but is something completely different, like {{8.08}}, dependent on the number of cores used.
> If the parallelism is set to {{1}} the result is correct, which indicates a likely threading problem. 
> The problem occurs using the java and scala API.
> {code}
> env
>   .fromParallelCollection(new NumberSequenceIterator(1, 100))
>   .map(new RichMapFunction[Long, Long] {
> 	var a : AverageAccumulator = _
> 	override def map(value: Long): Long = {
> 	  a.add(value)
> 	  value
> 	}
> 	override def open(parameters: Configuration): Unit = {
> 	  a = new AverageAccumulator
> 	  getRuntimeContext.addAccumulator("test", a)
> 	}
>   })
>   .reduce((a, b) => a + b)
>   .print()
> val lastJobExecutionResult: JobExecutionResult = env.getLastJobExecutionResult
> println(lastJobExecutionResult.getAccumulatorResult("test"))
> {code}



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