Github user coolfrood commented on a diff in the pull request:
https://github.com/apache/spark/pull/6361#discussion_r31439444
--- Diff: core/src/main/scala/org/apache/spark/scheduler/Task.scala ---
@@ -126,6 +129,21 @@ private[spark] abstract class Task[T](val stageId:
Int, var partitionId: Int) ex
taskThread.interrupt()
}
}
+
+ /**
+ * Deserializes the task from the broadcast variable.
+ * If Kryo serialization is being sed, a copy of the buffer is made
because Kryo deserialization
+ * is not thread-safe w.r.t. the deserialization buffer (see SPARK-7708)
+ */
+ protected[this] def deserialize[T: ClassTag](taskBinary:
Broadcast[Array[Byte]]): T = {
+ val ser = SparkEnv.get.closureSerializer.newInstance()
--- End diff --
How do you feel about implementing a pool in the `Task` object and
accessing it from `Task`'s `run` method? This way, the serializer instance can
be handed back into the pool after the task is done executing.
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