Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/3026#discussion_r19834651
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala
---
@@ -58,24 +54,45 @@ abstract class ReceiverInputDStream[T:
ClassTag](@transient ssc_ : StreamingCont
def stop() {}
- /** Ask ReceiverInputTracker for received data blocks and generates RDDs
with them. */
+ /**
+ * Generates RDDs with blocks received by the receiver of this stream. */
override def compute(validTime: Time): Option[RDD[T]] = {
- // If this is called for any time before the start time of the context,
- // then this returns an empty RDD. This may happen when recovering
from a
- // master failure
- if (validTime >= graph.startTime) {
- val blockInfo =
ssc.scheduler.receiverTracker.getReceivedBlockInfo(id)
- receivedBlockInfo(validTime) = blockInfo
- val blockIds = blockInfo.map {
_.blockStoreResult.blockId.asInstanceOf[BlockId] }
- Some(new BlockRDD[T](ssc.sc, blockIds))
- } else {
- Some(new BlockRDD[T](ssc.sc, Array.empty))
- }
- }
+ val blockRDD = {
- /** Get information on received blocks. */
- private[streaming] def getReceivedBlockInfo(time: Time) = {
- receivedBlockInfo.get(time).getOrElse(Array.empty[ReceivedBlockInfo])
+ if (validTime < graph.startTime) {
+ // If this is called for any time before the start time of the
context,
+ // then this returns an empty RDD. This may happen when recovering
from a
+ // driver failure without any write ahead log to recover
pre-failure data.
+ new BlockRDD[T](ssc.sc, Array.empty)
+ } else {
+ // Otherwise, ask the tracker for all the blocks that have been
allocated to this stream
+ // for this batch
+ val blockInfos =
+
ssc.scheduler.receiverTracker.getBlocksOfBatch(validTime).get(id).getOrElse(Seq.empty)
+ val blockStoreResults = blockInfos.map { _.blockStoreResult }
+ val blockIds = blockStoreResults.map {
_.blockId.asInstanceOf[BlockId] }.toArray
+
+ // Check whether all the results are of the same type
+ val resultTypes = blockStoreResults.map { _.getClass }.distinct
+ if (resultTypes.size > 1) {
+ logWarning("Multiple result types in block information, WAL
information will be ignored.")
+ }
+
+ // If all the results are of type WriteAheadLogBasedStoreResult,
then create
+ // WriteAheadLogBackedBlockRDD else create simple BlockRDD.
+ if (resultTypes.size == 1 && resultTypes.head ==
classOf[WriteAheadLogBasedStoreResult]) {
+ val logSegments = blockStoreResults.map {
+ _.asInstanceOf[WriteAheadLogBasedStoreResult].segment
+ }.toArray
+ // Since storeInBlockManager = false, the storage level does not
matter.
+ new WriteAheadLogBackedBlockRDD[T](ssc.sparkContext,
+ blockIds, logSegments, storeInBlockManager = false,
StorageLevel.NONE)
--- End diff --
There can be an additional cost of putting the data back into BM, which is
unnecessary for simple workloads where the data is probably going to be used
only once. I see your point as well. So what we can do is that we allows the
data to be stored in BM only in the serialized form (so storage level =
MEMORY_ONLY_SER). That should be a no-overhead solution.
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