juliuszsompolski commented on a change in pull request #25611:
[SPARK-28901][SQL] SparkThriftServer's Cancel SQL Operation show it in JDBC Tab
UI
URL: https://github.com/apache/spark/pull/25611#discussion_r319933080
##########
File path:
sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
##########
@@ -239,6 +239,15 @@ object HiveThriftServer2 extends Logging {
executionList(id).state = ExecutionState.COMPILED
}
+ def onStatementCanceled(id: String): Unit = {
+ synchronized {
+ executionList(id).finishTimestamp = System.currentTimeMillis
+ executionList(id).state = ExecutionState.CANCELED
+ totalRunning -= 1
Review comment:
@AngersZhuuuu I think it's easy to get something wrong with the
`totalRunning` counter. Even if we covered all the cases now, it's hard to
reason about all the possible paths, and easy to break. I would suggest to
count it on the fly based on status, like I proposed before.
```
def getOnlineSessionNum: Int = synchronized {
sessionList.count(_._2.finishTimestamp == 0)
}
def isExecutionActive(execInfo: ExecutionInfo): Boolean = {
!(execInfo.state == ExecutionState.FAILED ||
execInfo.state == ExecutionState.CANCELED ||
execInfo.closeTimestamp != 0)
}
/**
* When an error or a cancellation occurs, we set the finishTimestamp of
the statement.
* Therefore, when we count the number of running statements, we need to
exclude errors and
* cancellations and count all statements that have not been closed so
far.
*/
def getTotalRunning: Int = synchronized {
executionList.count {
case (_, v) => isExecutionActive(v)
}
}
```
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