juliuszsompolski commented on code in PR #49370: URL: https://github.com/apache/spark/pull/49370#discussion_r1913199388
########## sql/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteThreadRunner.scala: ########## @@ -63,6 +63,16 @@ private[connect] class ExecuteThreadRunner(executeHolder: ExecuteHolder) extends } } + /** + * Checks if the execution is completed. + * + * @return + * true if the execution is completed. + */ + private[connect] def isCompleted(): Boolean = { + state.getAcquire() == ThreadState.completed + } Review Comment: What if the `ExecuteThreadRunner` just dies without executing the transition to ThreadState.completed? ########## sql/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteGrpcResponseSender.scala: ########## @@ -319,7 +325,14 @@ private[connect] class ExecuteGrpcResponseSender[T <: Message]( log"waitingForResults=${MDC(WAIT_RESULT_TIME, consumeSleep / NANOS_PER_MILLIS.toDouble)} ms " + log"waitingForSend=${MDC(WAIT_SEND_TIME, sendSleep / NANOS_PER_MILLIS.toDouble)} ms") // scalastyle:on line.size.limit - grpcObserver.onCompleted() + if (executionCompleted && !sizeLimitReached) { Review Comment: I see, right, `executionCompleted` is a val setup even at the init of the sender, so no concurrency changes here... and I misread the nesting of this if in the first place, hence confusion. But what if deadlineReached == true sizeLimitReached == false executionCompleted == true just because the client is slow and was not able to consume sizeLimit of results within the deadline? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org