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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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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No
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