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Posted to reviews@spark.apache.org by "bogao007 (via GitHub)" <gi...@apache.org> on 2023/09/18 22:02:32 UTC
[GitHub] [spark] bogao007 opened a new pull request, #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
bogao007 opened a new pull request, #42986:
URL: https://github.com/apache/spark/pull/42986
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### What changes were proposed in this pull request?
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Handle errors inside streaming Python workers (foreach_batch_worker and listener_worker) and propagate to server side.
- Write 0 to Python worker's outfile if no error occurs.
- Write -2 and traceback to outfile if there's an error which can be read from the server side.
I was referring to the code [here](https://github.com/apache/spark/blob/981312284f0776ca847c8d21411f74a72c639b22/python/pyspark/sql/worker/analyze_udtf.py#L157-L160) from another existing Python worker.
### Why are the changes needed?
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1. If you propose a new API, clarify the use case for a new API.
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Without this change, there's no error handling in streaming python workers. The server side is [expecting](https://github.com/apache/spark/blob/981312284f0776ca847c8d21411f74a72c639b22/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala#L128-L129) 0 being written in [python worker's](https://github.com/apache/spark/blob/981312284f0776ca847c8d21411f74a72c639b22/python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py#L73) output stream. But if any error is thrown in the worker, the 0 is not written anymore which would lead to an `EOFException` since we are trying to read from an empty stream.
If we remove the [lines](https://github.com/apache/spark/blob/981312284f0776ca847c8d21411f74a72c639b22/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala#L128-L129) reading python worker's output. The streaming query would succeed even if there's an error in foreachBatch function which is not the desired behavior we want.
With this PR, we are propagating the errors from Python worker to the server so it would fail the streaming query.
### Does this PR introduce _any_ user-facing change?
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Yes
### How was this patch tested?
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Enabled `test_streaming_foreach_batch_propagates_python_errors` test.
Did manual testing
ForeachBatch:
```
>>> def collectBatch(df, id):
... raise RuntimeError("this should fail the query")
>>> df = spark.readStream.format("text").load("python/test_support/sql/streaming")
>>> q = df.writeStream.foreachBatch(collectBatch).start()
```
```
23/09/18 14:21:12 ERROR MicroBatchExecution: Query [id = 8168dc4d-02cc-4ddd-996c-96667d928b88, runId = 04829434-767e-4d13-b4c2-e45ce8932223] terminated with error
java.lang.IllegalStateException: Found error inside foreachBatch Python process: Traceback (most recent call last):
File "/Users/bo.gao/workplace/spark/python/lib/pyspark.zip/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py", line 76, in main
File "/Users/bo.gao/workplace/spark/python/lib/pyspark.zip/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py", line 69, in process
File "<stdin>", line 2, in collectBatch
RuntimeError: this should fail the query
at org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.$anonfun$pythonForeachBatchWrapper$1(StreamingForeachBatchHelper.scala:137)
at org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.$anonfun$pythonForeachBatchWrapper$1$adapted(StreamingForeachBatchHelper.scala:115)
at org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.$anonfun$dataFrameCachingWrapper$1(StreamingForeachBatchHelper.scala:70)
at org.apache.spark.sql.connect.planner.StreamingForeachBatchHelper$.$anonfun$dataFrameCachingWrapper$1$adapted(StreamingForeachBatchHelper.scala:60)
at org.apache.spark.sql.execution.streaming.sources.ForeachBatchSink.addBatch(ForeachBatchSink.scala:34)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:732)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$6(SQLExecution.scala:150)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:241)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId0$1(SQLExecution.scala:116)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId0(SQLExecution.scala:72)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:196)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:729)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:427)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:425)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:729)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:286)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:427)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:425)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:249)
at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:67)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:239)
at org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:311)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:289)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.$anonfun$run$1(StreamExecution.scala:211)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:211)
```
StreamingQueryListener:
```
>>> class TestListener(StreamingQueryListener):
... def onQueryStarted(self, event):
... raise RuntimeError("this should fail the listener")
... def onQueryProgress(self, event):
... pass
... def onQueryIdle(self, event):
... pass
... def onQueryTerminated(self, event):
... pass
...
>>> test_listener = TestListener()
>>> spark.streams.addListener(test_listener)
>>> df = spark.readStream.format("rate").option("rowsPerSecond", 10).load()
>>> query = df.writeStream.format("noop").queryName("test").start()
>>> query.stop()
```
```
23/09/18 14:18:56 ERROR StreamingQueryListenerBus: Listener PythonStreamingQueryListener threw an exception
java.lang.IllegalStateException: Found error inside Streaming query listener Python process for function onQueryStarted: Traceback (most recent call last):
File "/Users/bo.gao/workplace/spark/python/lib/pyspark.zip/pyspark/sql/connect/streaming/worker/listener_worker.py", line 90, in main
File "/Users/bo.gao/workplace/spark/python/lib/pyspark.zip/pyspark/sql/connect/streaming/worker/listener_worker.py", line 78, in process
File "<stdin>", line 3, in onQueryStarted
RuntimeError: this should fail the listener
at org.apache.spark.sql.connect.planner.PythonStreamingQueryListener.handlePythonWorkerError(StreamingQueryListenerHelper.scala:88)
at org.apache.spark.sql.connect.planner.PythonStreamingQueryListener.onQueryStarted(StreamingQueryListenerHelper.scala:50)
at org.apache.spark.sql.execution.streaming.StreamingQueryListenerBus.doPostEvent(StreamingQueryListenerBus.scala:131)
at org.apache.spark.sql.execution.streaming.StreamingQueryListenerBus.doPostEvent(StreamingQueryListenerBus.scala:43)
at org.apache.spark.util.ListenerBus.postToAll(ListenerBus.scala:117)
at org.apache.spark.util.ListenerBus.postToAll$(ListenerBus.scala:101)
at org.apache.spark.sql.execution.streaming.StreamingQueryListenerBus.postToAll(StreamingQueryListenerBus.scala:88)
at org.apache.spark.sql.execution.streaming.StreamingQueryListenerBus.post(StreamingQueryListenerBus.scala:77)
at org.apache.spark.sql.streaming.StreamingQueryManager.postListenerEvent(StreamingQueryManager.scala:231)
at org.apache.spark.sql.execution.streaming.StreamExecution.postEvent(StreamExecution.scala:408)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:283)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.$anonfun$run$1(StreamExecution.scala:211)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:211)
```
### Was this patch authored or co-authored using generative AI tooling?
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[GitHub] [spark] rangadi commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "rangadi (via GitHub)" <gi...@apache.org>.
rangadi commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329448797
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -125,8 +128,21 @@ object StreamingForeachBatchHelper extends Logging {
dataOut.writeLong(args.batchId)
dataOut.flush()
- val ret = dataIn.readInt()
- logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
Review Comment:
Minor: Can simply be `case 0 => `
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -38,33 +43,56 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
sessionHolder.sessionId,
"pyspark.sql.connect.streaming.worker.listener_worker")
- val (dataOut, _) = runner.init()
+ val (dataOut, dataIn) = runner.init()
override def onQueryStarted(event: StreamingQueryListener.QueryStartedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(0)
dataOut.flush()
+ handlePythonWorkerError("onQueryStarted")
}
override def onQueryProgress(event: StreamingQueryListener.QueryProgressEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(1)
dataOut.flush()
+ handlePythonWorkerError("onQueryProgress")
}
override def onQueryIdle(event: StreamingQueryListener.QueryIdleEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(2)
dataOut.flush()
+ handlePythonWorkerError("onQueryIdle")
}
override def onQueryTerminated(event: StreamingQueryListener.QueryTerminatedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(3)
dataOut.flush()
+ handlePythonWorkerError("onQueryTerminated")
}
private[spark] def stopListenerProcess(): Unit = {
runner.stop()
}
+
+ private def handlePythonWorkerError(functionName: String): Unit = {
+ try {
+ dataIn.readInt() match {
Review Comment:
Can you add a comment to reuse this code?
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -125,8 +128,21 @@ object StreamingForeachBatchHelper extends Logging {
dataOut.writeLong(args.batchId)
dataOut.flush()
- val ret = dataIn.readInt()
- logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside foreachBatch Python process: $msg", null)
Review Comment:
Handle other return here.
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -38,33 +43,56 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
sessionHolder.sessionId,
"pyspark.sql.connect.streaming.worker.listener_worker")
- val (dataOut, _) = runner.init()
+ val (dataOut, dataIn) = runner.init()
override def onQueryStarted(event: StreamingQueryListener.QueryStartedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(0)
dataOut.flush()
+ handlePythonWorkerError("onQueryStarted")
}
override def onQueryProgress(event: StreamingQueryListener.QueryProgressEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(1)
dataOut.flush()
+ handlePythonWorkerError("onQueryProgress")
}
override def onQueryIdle(event: StreamingQueryListener.QueryIdleEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(2)
dataOut.flush()
+ handlePythonWorkerError("onQueryIdle")
}
override def onQueryTerminated(event: StreamingQueryListener.QueryTerminatedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(3)
dataOut.flush()
+ handlePythonWorkerError("onQueryTerminated")
}
private[spark] def stopListenerProcess(): Unit = {
runner.stop()
}
+
+ private def handlePythonWorkerError(functionName: String): Unit = {
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
+ throw new SparkException("Python worker exited unexpectedly (crashed)", eof)
Review Comment:
Always include the base exception (same for foreach batch side).
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
Yeah, we can't handle the retries in the PR. we need to implement that feature properly.
@bogao007 can catch any `NonFatal(ex)` here.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329447168
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
If we want to add retry logic, adding it here would not solve the problem. If the EOF is due to an IOException during `write_` functions, we might need to add retries inside the workers. But I'm not sure how high would the possibility be for that scenario, since if IOException happens while writing, it's highly possible that the socket is closed, and retry would no help in that case.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329574367
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
Not sure if catching any `NonFatal(ex)` is a good solution here since if errors occurs, it's highly possible that something went wrong in the python worker, and better to fail the query in this case. I'll leave it as what it is for now and also added a TODO in `StreamingForeachBatchHelper` to improve handling this scenario later.
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -125,8 +128,21 @@ object StreamingForeachBatchHelper extends Logging {
dataOut.writeLong(args.batchId)
dataOut.flush()
- val ret = dataIn.readInt()
- logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside foreachBatch Python process: $msg", null)
Review Comment:
Updated.
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -38,33 +43,56 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
sessionHolder.sessionId,
"pyspark.sql.connect.streaming.worker.listener_worker")
- val (dataOut, _) = runner.init()
+ val (dataOut, dataIn) = runner.init()
override def onQueryStarted(event: StreamingQueryListener.QueryStartedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(0)
dataOut.flush()
+ handlePythonWorkerError("onQueryStarted")
}
override def onQueryProgress(event: StreamingQueryListener.QueryProgressEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(1)
dataOut.flush()
+ handlePythonWorkerError("onQueryProgress")
}
override def onQueryIdle(event: StreamingQueryListener.QueryIdleEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(2)
dataOut.flush()
+ handlePythonWorkerError("onQueryIdle")
}
override def onQueryTerminated(event: StreamingQueryListener.QueryTerminatedEvent): Unit = {
PythonRDD.writeUTF(event.json, dataOut)
dataOut.writeInt(3)
dataOut.flush()
+ handlePythonWorkerError("onQueryTerminated")
}
private[spark] def stopListenerProcess(): Unit = {
runner.stop()
}
+
+ private def handlePythonWorkerError(functionName: String): Unit = {
+ try {
+ dataIn.readInt() match {
Review Comment:
Done.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329574367
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
Not sure if catching any `NonFatal(ex)` is a good solution here since if errors occurs, it's highly possible that something went wrong in the python worker, and better to fail the query in this case. I'll leave it as what it is for now and also added a TODO in `StreamingForeachBatchHelper` to improve the handling of this scenario later.
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[GitHub] [spark] WweiL commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "WweiL (via GitHub)" <gi...@apache.org>.
WweiL commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329441472
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
@HyukjinKwon @taku-k Guys, do you know if the EOFException would happen frequently in existing pyspark tests? I was wondering if this is possible:
Say in common PythonRunner, EOF occurs, then the task would likely be failing but spark nicely handles the retry.
But here if the socket has some error, we don't have any retry logic, and the stream query would just fail with our issue.
Given that streamingPythonRunners are long-running processes, I was wondering if you also think having a retry-logic would be beneficial as a followup.
cc @rangadi
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[GitHub] [spark] rangadi commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "rangadi (via GitHub)" <gi...@apache.org>.
rangadi commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329577300
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
Absolutely. It should fail the query. I thought this code was wrapping it in a SparkException and throwing it.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329356792
##########
python/pyspark/sql/connect/streaming/worker/listener_worker.py:
##########
@@ -83,7 +86,14 @@ def process(listener_event_str, listener_event_type): # type: ignore[no-untyped
while True:
event = utf8_deserializer.loads(infile)
event_type = read_int(infile)
- process(event, int(event_type)) # TODO(SPARK-44463): Propagate error to the user.
+ # Handle errors inside Python worker. Write 0 to outfile if no errors and write -2 with
+ # traceback string if error occurs.
+ try:
+ process(event, int(event_type))
+ write_int(0, outfile)
Review Comment:
I think that's the only way to propagate something out of the Python worker, if it fails, then I'm not sure if there's anything else that could propagate that error out.
From the [existing worker](https://github.com/apache/spark/blob/981312284f0776ca847c8d21411f74a72c639b22/python/pyspark/sql/worker/analyze_udtf.py#L161-L163), it does not do anything if there's an IOException but close the python process. But let me update the code to use the same way they did, which should be slightly better.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329422764
##########
python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py:
##########
@@ -69,8 +73,32 @@ def process(df_id, batch_id): # type: ignore[no-untyped-def]
while True:
df_ref_id = utf8_deserializer.loads(infile)
batch_id = read_long(infile)
- process(df_ref_id, int(batch_id)) # TODO(SPARK-44463): Propagate error to the user.
- write_int(0, outfile)
+ # Handle errors inside Python worker. Write 0 to outfile if no errors and write -2 with
+ # traceback string if error occurs.
+ try:
+ process(df_ref_id, int(batch_id))
+ write_int(0, outfile)
+ except BaseException as e:
Review Comment:
done.
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -125,8 +128,21 @@ object StreamingForeachBatchHelper extends Logging {
dataOut.writeLong(args.batchId)
dataOut.flush()
- val ret = dataIn.readInt()
- logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new IllegalStateException(s"Found error inside foreachBatch Python process: $msg")
Review Comment:
updated.
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329393005
##########
python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py:
##########
@@ -69,8 +73,32 @@ def process(df_id, batch_id): # type: ignore[no-untyped-def]
while True:
df_ref_id = utf8_deserializer.loads(infile)
batch_id = read_long(infile)
- process(df_ref_id, int(batch_id)) # TODO(SPARK-44463): Propagate error to the user.
- write_int(0, outfile)
+ # Handle errors inside Python worker. Write 0 to outfile if no errors and write -2 with
+ # traceback string if error occurs.
+ try:
+ process(df_ref_id, int(batch_id))
+ write_int(0, outfile)
+ except BaseException as e:
Review Comment:
you could put that into `pyspark.util`
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[GitHub] [spark] HyukjinKwon commented on pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #42986:
URL: https://github.com/apache/spark/pull/42986#issuecomment-1724629485
Otherwise looks sane to me. cc @ueshin
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329392786
##########
python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py:
##########
@@ -69,8 +73,32 @@ def process(df_id, batch_id): # type: ignore[no-untyped-def]
while True:
df_ref_id = utf8_deserializer.loads(infile)
batch_id = read_long(infile)
- process(df_ref_id, int(batch_id)) # TODO(SPARK-44463): Propagate error to the user.
- write_int(0, outfile)
+ # Handle errors inside Python worker. Write 0 to outfile if no errors and write -2 with
+ # traceback string if error occurs.
+ try:
+ process(df_ref_id, int(batch_id))
+ write_int(0, outfile)
+ except BaseException as e:
Review Comment:
I think we should probably put this handling into a util and reuse it in the regular `worker.py` too.
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[GitHub] [spark] bogao007 commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "bogao007 (via GitHub)" <gi...@apache.org>.
bogao007 commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329447168
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingQueryListenerHelper.scala:
##########
@@ -76,16 +78,21 @@ class PythonStreamingQueryListener(listener: SimplePythonFunction, sessionHolder
}
private def handlePythonWorkerError(functionName: String): Unit = {
- dataIn.readInt() match {
- case ret if ret == 0 =>
- logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
- case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
- val exLength = dataIn.readInt()
- val obj = new Array[Byte](exLength)
- dataIn.readFully(obj)
- val msg = new String(obj, StandardCharsets.UTF_8)
- throw new IllegalStateException(s"Found error inside Streaming query listener Python " +
- s"process for function $functionName: $msg")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Streaming query listener function $functionName completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new PythonException(s"Found error inside Streaming query listener Python " +
+ s"process for function $functionName: $msg", null)
+ }
+ } catch {
+ case eof: EOFException =>
Review Comment:
If we want to add retry logic, adding it here would not solve the problem. If the EOF is due to an IOException during `write_` functions, we might need to add retries inside the workers. But I'm not sure how high would the possibility be for that scenario to happen, since if IOException happens while writing, it's highly possible that the socket is closed, and retry would no help in that case.
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[GitHub] [spark] WweiL commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "WweiL (via GitHub)" <gi...@apache.org>.
WweiL commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329337505
##########
python/pyspark/sql/connect/streaming/worker/listener_worker.py:
##########
@@ -83,7 +86,14 @@ def process(listener_event_str, listener_event_type): # type: ignore[no-untyped
while True:
event = utf8_deserializer.loads(infile)
event_type = read_int(infile)
- process(event, int(event_type)) # TODO(SPARK-44463): Propagate error to the user.
+ # Handle errors inside Python worker. Write 0 to outfile if no errors and write -2 with
+ # traceback string if error occurs.
+ try:
+ process(event, int(event_type))
+ write_int(0, outfile)
Review Comment:
Do you think it's possible that the `read_` and `write_` method could throw exceptions?
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #42986:
URL: https://github.com/apache/spark/pull/42986#discussion_r1329392064
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -125,8 +128,21 @@ object StreamingForeachBatchHelper extends Logging {
dataOut.writeLong(args.batchId)
dataOut.flush()
- val ret = dataIn.readInt()
- logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ try {
+ dataIn.readInt() match {
+ case ret if ret == 0 =>
+ logInfo(s"Python foreach batch for dfId ${args.dfId} completed (ret: $ret)")
+ case SpecialLengths.PYTHON_EXCEPTION_THROWN =>
+ val exLength = dataIn.readInt()
+ val obj = new Array[Byte](exLength)
+ dataIn.readFully(obj)
+ val msg = new String(obj, StandardCharsets.UTF_8)
+ throw new IllegalStateException(s"Found error inside foreachBatch Python process: $msg")
Review Comment:
Should it be `PythonException`? To match with `PythonRunner.handlePythonException`. Or it'd be great to see if we can reuse them.
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[GitHub] [spark] HyukjinKwon closed pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon closed pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
URL: https://github.com/apache/spark/pull/42986
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[GitHub] [spark] HyukjinKwon commented on pull request #42986: [SPARK-44463][SS][CONNECT] Improve error handling for Connect steaming Python worker
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #42986:
URL: https://github.com/apache/spark/pull/42986#issuecomment-1726838303
Merged to master.
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