JDBC client should catch task failed exception instead of NPE in the incremental mode #4711
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pan3793
reviewed
Apr 14, 2023
| warn(s"Ignore exception in terminal state with $statementId: $errMsg") | ||
| val ke = KyuubiSQLException(errMsg) | ||
| setOperationException(ke) | ||
| throw ke |
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always re-throw exception makes sense to me, no sure if it will break some cases.
Codecov Report
@@ Coverage Diff @@
## master #4711 +/- ##
============================================
- Coverage 58.05% 57.98% -0.08%
Complexity 13 13
============================================
Files 580 580
Lines 32231 32232 +1
Branches 4302 4302
============================================
- Hits 18712 18690 -22
- Misses 11729 11744 +15
- Partials 1790 1798 +8
... and 12 files with indirect coverage changes 📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more |
pan3793
approved these changes
Apr 14, 2023
turboFei
approved these changes
Apr 14, 2023
|
Thanks, merged to master/1.7 |
pan3793
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Apr 14, 2023
… of NPE in the incremental mode
### _Why are the changes needed?_
Since the job was lazily submitted in the incremental mode, the engine should not catch the task failed exception even though the operation is in the terminal state.
Before this PR:
```
0: jdbc:hive2://0.0.0.0:10009/> set kyuubi.operation.incremental.collect=true;
+---------------------------------------+--------+
| key | value |
+---------------------------------------+--------+
| kyuubi.operation.incremental.collect | true |
+---------------------------------------+--------+
0: jdbc:hive2://0.0.0.0:10009/> SELECT raise_error('custom error message');
Error: (state=,code=0)
0: jdbc:hive2://0.0.0.0:10009/>
```
kyuubi server log
```
2023-04-14 18:47:50.185 ERROR org.apache.kyuubi.server.KyuubiTBinaryFrontendService: Error fetching results:
java.lang.NullPointerException: null
at org.apache.kyuubi.server.BackendServiceMetric.$anonfun$fetchResults$1(BackendServiceMetric.scala:191) ~[classes/:?]
at org.apache.kyuubi.metrics.MetricsSystem$.timerTracing(MetricsSystem.scala:111) ~[classes/:?]
at org.apache.kyuubi.server.BackendServiceMetric.fetchResults(BackendServiceMetric.scala:187) ~[classes/:?]
at org.apache.kyuubi.server.BackendServiceMetric.fetchResults$(BackendServiceMetric.scala:182) ~[classes/:?]
at org.apache.kyuubi.server.KyuubiServer$$anon$1.fetchResults(KyuubiServer.scala:147) ~[classes/:?]
at org.apache.kyuubi.service.TFrontendService.FetchResults(TFrontendService.scala:530) [classes/:?]
```
After this PR:
```
0: jdbc:hive2://0.0.0.0:10009/> set kyuubi.operation.incremental.collect=true;
+---------------------------------------+--------+
| key | value |
+---------------------------------------+--------+
| kyuubi.operation.incremental.collect | true |
+---------------------------------------+--------+
0: jdbc:hive2://0.0.0.0:10009/> SELECT raise_error('custom error message');
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3.0 (TID 3) (0.0.0.0 executor driver): java.lang.RuntimeException: custom error message
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.project_doConsume_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:136)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2672)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2608)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2607)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2607)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1182)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1182)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1182)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2860)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2791)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:952)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2228)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2249)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2268)
at org.apache.spark.rdd.RDD.collectPartition$1(RDD.scala:1036)
at org.apache.spark.rdd.RDD.$anonfun$toLocalIterator$3(RDD.scala:1038)
at org.apache.spark.rdd.RDD.$anonfun$toLocalIterator$3$adapted(RDD.scala:1038)
at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:486)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:492)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.kyuubi.operation.IterableFetchIterator.hasNext(FetchIterator.scala:97)
at scala.collection.Iterator$SliceIterator.hasNext(Iterator.scala:268)
at scala.collection.Iterator.toStream(Iterator.scala:1417)
at scala.collection.Iterator.toStream$(Iterator.scala:1416)
at scala.collection.AbstractIterator.toStream(Iterator.scala:1431)
at scala.collection.TraversableOnce.toSeq(TraversableOnce.scala:354)
at scala.collection.TraversableOnce.toSeq$(TraversableOnce.scala:354)
at scala.collection.AbstractIterator.toSeq(Iterator.scala:1431)
at org.apache.kyuubi.engine.spark.operation.SparkOperation.$anonfun$getNextRowSet$1(SparkOperation.scala:265)
at org.apache.kyuubi.engine.spark.operation.SparkOperation.$anonfun$withLocalProperties$1(SparkOperation.scala:155)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169)
at org.apache.kyuubi.engine.spark.operation.SparkOperation.withLocalProperties(SparkOperation.scala:139)
at org.apache.kyuubi.engine.spark.operation.SparkOperation.getNextRowSet(SparkOperation.scala:243)
at org.apache.kyuubi.operation.OperationManager.getOperationNextRowSet(OperationManager.scala:141)
at org.apache.kyuubi.session.AbstractSession.fetchResults(AbstractSession.scala:240)
at org.apache.kyuubi.service.AbstractBackendService.fetchResults(AbstractBackendService.scala:214)
at org.apache.kyuubi.service.TFrontendService.FetchResults(TFrontendService.scala:530)
at org.apache.hive.service.rpc.thrift.TCLIService$Processor$FetchResults.getResult(TCLIService.java:1837)
at org.apache.hive.service.rpc.thrift.TCLIService$Processor$FetchResults.getResult(TCLIService.java:1822)
at org.apache.thrift.ProcessFunction.process(ProcessFunction.java:39)
at org.apache.thrift.TBaseProcessor.process(TBaseProcessor.java:39)
at org.apache.kyuubi.service.authentication.TSetIpAddressProcessor.process(TSetIpAddressProcessor.scala:36)
at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:286)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.RuntimeException: custom error message
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.project_doConsume_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:136)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
... 3 more (state=,code=0)
0: jdbc:hive2://0.0.0.0:10009/>
```
### _How was this patch tested?_
- [ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible
- [ ] Add screenshots for manual tests if appropriate
- [x] [Run test](https://kyuubi.readthedocs.io/en/master/develop_tools/testing.html#running-tests) locally before make a pull request
Closes #4711 from cfmcgrady/incremental-show-error-msg.
Closes #4711
66bb527 [Fu Chen] JDBC client should catch task failed exception in the incremental mode
Authored-by: Fu Chen <cfmcgrady@gmail.com>
Signed-off-by: Cheng Pan <chengpan@apache.org>
(cherry picked from commit db46b5b)
Signed-off-by: Cheng Pan <chengpan@apache.org>
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Why are the changes needed?
Since the job was lazily submitted in the incremental mode, the engine should not catch the task failed exception even though the operation is in the terminal state.
Before this PR:
kyuubi server log
After this PR:
How was this patch tested?
Add some test cases that check the changes thoroughly including negative and positive cases if possible
Add screenshots for manual tests if appropriate
Run test locally before make a pull request