I notice that spark serialize each task with the dependencies (files and JARs
added to the SparkContext) ,
def serializeWithDependencies(
task: Task[_],
currentFiles: HashMap[String, Long],
currentJars: HashMap[String, Long],
serializer: SerializerInstance)
: ByteBuffer = {
val out = new ByteArrayOutputStream(4096)
val dataOut = new DataOutputStream(out)
// Write currentFiles
dataOut.writeInt(currentFiles.size)
for ((name, timestamp) <- currentFiles) {
dataOut.writeUTF(name)
dataOut.writeLong(timestamp)
}
// Write currentJars
dataOut.writeInt(currentJars.size)
for ((name, timestamp) <- currentJars) {
dataOut.writeUTF(name)
dataOut.writeLong(timestamp)
}
// Write the task itself and finish
dataOut.flush()
val taskBytes = serializer.serialize(task).array()
out.write(taskBytes)
ByteBuffer.wrap(out.toByteArray)
}
Why not send currentJars and currentFiles to exetutor using actor? I think
it's not necessary to serialize them for each task.
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