Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/6361#discussion_r31401808
--- 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 --
It's actually pretty expensive to construct KryoSerializer instances, so
this might become a significant bottleneck for short tasks (JavaSerializer
instances are cheap, on the other hand). We'll still need to ensure that the
KryoSerializerInstance is only used in one thread at a time, though. Maybe we
can pool instances inside of `Executor` and loan them to tasks by passing them
in via `runTask`. Alternatively, we could expose the serializer instance via
TaskContext.
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