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.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
