Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11440#discussion_r54551767
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala
---
@@ -221,8 +221,12 @@ class JobGenerator(jobScheduler: JobScheduler) extends
Logging {
logInfo("Batches pending processing (" + pendingTimes.size + "
batches): " +
pendingTimes.mkString(", "))
// Reschedule jobs for these times
- val timesToReschedule = (pendingTimes ++ downTimes).filter { _ <
restartTime }
- .distinct.sorted(Time.ordering)
+ val skipDownTime =
conf.getBoolean("spark.streaming.skipDownTimeBatch", false)
--- End diff --
I'd prefer not to add yet another configuration to control this. It adds
complexity. I don't think the name is descriptive here; what is a 'down time
batch'? The current behavior is coherent, since the expected behavior is to
pick up where it left off. It's not intended that you leave the job not running
for a long time relative to the batch interval.
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