[GitHub] jose-torres commented on a change in pull request #23156: [SPARK-24063][SS] Add maximum epoch queue threshold for ContinuousExecution

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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
 
 

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 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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