jose-torres commented on a change in pull request #23156: [SPARK-24063][SS] Add
maximum epoch queue threshold for ContinuousExecution
URL: https://github.com/apache/spark/pull/23156#discussion_r260045881
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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@@ -1413,6 +1413,14 @@ object SQLConf {
.booleanConf
.createWithDefault(true)
+ val CONTINUOUS_STREAMING_EPOCH_BACKLOG_QUEUE_SIZE =
+ buildConf("spark.sql.streaming.continuous.epochBacklogQueueSize")
+ .internal()
+ .doc("The max number of entries to be stored in queue to wait for late
epochs. " +
+ "If this parameter is exceeded by the size of the queue, stream will
stop with an error.")
+ .intConf
+ .createWithDefault(10000)
Review comment:
Oh, sorry, I've just been following along here. I agree that a queue of 10k
epochs stacked up indicates the query is never going to make progress. The
tasks of a continuous processing query are all co-scheduled - if one or more of
the tasks ends up that far behind, it's almost surely because it's
unrecoverably broken.
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