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https://issues.apache.org/jira/browse/SPARK-19181?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-19181:
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Assignee: (was: Apache Spark)
> SparkListenerSuite.local metrics fails when average executorDeserializeTime
> is too short.
> -----------------------------------------------------------------------------------------
>
> Key: SPARK-19181
> URL: https://issues.apache.org/jira/browse/SPARK-19181
> Project: Spark
> Issue Type: Bug
> Components: Tests
> Affects Versions: 2.1.0
> Reporter: Jose Soltren
> Priority: Minor
>
> https://github.com/apache/spark/blob/master/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala#L249
> The "local metrics" test asserts that tasks should take more than 1ms on
> average to complete, even though a code comment notes that this is a small
> test and tasks may finish faster. I've been seeing some "failures" here on
> fast systems that finish these tasks quite quickly.
> There are a few ways forward here:
> 1. Disable this test.
> 2. Relax this check.
> 3. Implement sub-millisecond granularity for task times throughout Spark.
> 4. (Imran Rashid's suggestion) Add buffer time by, say, having the task
> reference a partition that implements a custom Externalizable.readExternal,
> which always waits 1ms before returning.
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