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[SPARK-44839][SS][CONNECT] Better Error Logging when user tries to serialize spark session #42594

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[SPARK-44839][SS][CONNECT] Better Error Logging when user tries to serialize spark session #42594

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ed53613
done
WweiL Aug 21, 2023
cb81293
reorder error
WweiL Aug 22, 2023
5d617a4
update error
WweiL Aug 22, 2023
ab971ae
Update python/pyspark/errors/error_classes.py
WweiL Aug 22, 2023
01618a7
add new PySparkPicklingError
WweiL Aug 22, 2023
9a4daf5
Merge branch 'master' into SPARK-44839-spark-session-error
WweiL Aug 23, 2023
30c88e9
Merge branch 'master' into SPARK-44839-spark-session-error
WweiL Aug 24, 2023
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reorder error
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@WweiL
WweiL committed Aug 22, 2023
commit cb81293490d512c88470c1ccd4c5180bdb04a9df
10 changes: 5 additions & 5 deletions python/pyspark/errors/error_classes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -708,11 +708,6 @@
"State is either not defined or has already been removed."
]
},
"STREAMING_CONNECT_SERIALIZATION_ERROR" : {
"message" : [
"Cannot serialize the function `<name>`. If you accessed the spark session, or a dataframe defined outside of the function, please be aware that they are not allowed in Spark Connect. For foreachBatch, please access the spark session using `df.sparkSession`, where `df` is the first parameter in your foreachBatch function. For StreamingQueryListener, please access the spark session using `self.spark`. For details please check out the PySpark doc for foreachBatch and StreamingQueryListener."
]
},
"STOP_ITERATION_OCCURRED" : {
"message" : [
"Caught StopIteration thrown from user's code; failing the task: <exc>"
Expand All @@ -723,6 +718,11 @@
"pandas iterator UDF should exhaust the input iterator."
]
},
"STREAMING_CONNECT_SERIALIZATION_ERROR" : {
"message" : [
"Cannot serialize the function `<name>`. If you accessed the spark session, or a dataframe defined outside of the function, please be aware that they are not allowed in Spark Connect. For foreachBatch, please access the spark session using `df.sparkSession`, where `df` is the first parameter in your foreachBatch function. For StreamingQueryListener, please access the spark session using `self.spark`. For details please check out the PySpark doc for foreachBatch and StreamingQueryListener."
]
},
"TOO_MANY_VALUES" : {
"message" : [
"Expected <expected> values for `<item>`, got <actual>."
Expand Down