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Workaround in Spark for ConcurrentModification issue (JIRA Hadoop-10456, Spark-1097) #1000

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Workaround in Spark for ConcurrentModification issue (JIRA Hadoop-10456, Spark-1097) #1000

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681b36f
Fix for SPARK-1758: failing test org.apache.spark.JavaAPISuite.wholeT…
nishkamravi2 May 8, 2014
5108700
Fix in Spark for the Concurrent thread modification issue (SPARK-1097…
nishkamravi2 Jun 3, 2014
6b840f0
Undo the fix for SPARK-1758 (the problem is fixed)
nishkamravi2 Jun 3, 2014
df2aeb1
Improved fix for ConcurrentModificationIssue (Spark-1097, Hadoop-10456)
nishkamravi2 Jun 9, 2014
eb663ca
Merge branch 'master' of https://github.com/apache/spark
nishkamravi2 Jun 9, 2014
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11 changes: 7 additions & 4 deletions core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -139,10 +139,13 @@ class HadoopRDD[K, V](
// Create a JobConf that will be cached and used across this RDD's getJobConf() calls in the
// local process. The local cache is accessed through HadoopRDD.putCachedMetadata().
// The caching helps minimize GC, since a JobConf can contain ~10KB of temporary objects.
val newJobConf = new JobConf(broadcastedConf.value.value)
initLocalJobConfFuncOpt.map(f => f(newJobConf))
HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf)
newJobConf
// synchronize to prevent ConcurrentModificationException (Spark-1097, Hadoop-10456)
broadcastedConf.synchronized {
val newJobConf = new JobConf(broadcastedConf.value.value)
initLocalJobConfFuncOpt.map(f => f(newJobConf))
HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf)
newJobConf
}
}
}

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