Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/5533#discussion_r29633916
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala
---
@@ -175,39 +176,41 @@ private[streaming] class
StreamingJobProgressListener(ssc: StreamingContext)
completedBatchUIData.toSeq
}
- def processingDelayDistribution: Option[Distribution] = synchronized {
- extractDistribution(_.processingDelay)
+ def streamName(streamId: Int): Option[String] = {
+ ssc.graph.getInputStreamName(streamId)
}
- def schedulingDelayDistribution: Option[Distribution] = synchronized {
- extractDistribution(_.schedulingDelay)
- }
+ /**
+ * Return all InputDStream Ids
+ */
+ def streamIds: Seq[Int] = ssc.graph.getInputStreams().map(_.id)
- def totalDelayDistribution: Option[Distribution] = synchronized {
- extractDistribution(_.totalDelay)
- }
-
- def receivedRecordsDistributions: Map[Int, Option[Distribution]] =
synchronized {
- val latestBatchInfos = retainedBatches.reverse.take(batchUIDataLimit)
- val latestReceiverNumRecords =
latestBatchInfos.map(_.receiverNumRecords)
- val streamIds = ssc.graph.getInputStreams().map(_.id)
- streamIds.map { id =>
- val recordsOfParticularReceiver =
- latestReceiverNumRecords.map(v => v.getOrElse(id, 0L).toDouble *
1000 / batchDuration)
- val distribution = Distribution(recordsOfParticularReceiver)
- (id, distribution)
+ /**
+ * Return all of the event rates for each InputDStream in each batch.
+ */
--- End diff --
Can update comment to make it clear what this return type is. Its hard to
guess from `Map[Int, Seq[(Long, Double)]]`.
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