[
https://issues.apache.org/jira/browse/SPARK-33339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dongjoon Hyun updated SPARK-33339:
----------------------------------
Description:
When a system.exit exception occurs during the process, the python worker exits
abnormally, and then the executor task is still waiting for the worker for
reading from socket, causing it to hang.
The system.exit exception may be caused by the user's error code, but spark
should at least throw an error to remind the user, not get stuck
we can run a simple test to reproduce this case:
{code:python}
from pyspark.sql import SparkSession
def err(line):
raise SystemExit
spark = SparkSession.builder.appName("test").getOrCreate()
spark.sparkContext.parallelize(range(1,2), 2).map(err).collect()
spark.stop()
{code}
was:
When a system.exit exception occurs during the process, the python worker exits
abnormally, and then the executor task is still waiting for the worker for
reading from socket, causing it to hang.
The system.exit exception may be caused by the user's error code, but spark
should at least throw an error to remind the user, not get stuck
we can run a simple test to reproduce this case:
```
from pyspark.sql import SparkSession
def err(line):
raise SystemExit
spark = SparkSession.builder.appName("test").getOrCreate()
spark.sparkContext.parallelize(range(1,2), 2).map(err).collect()
spark.stop()
```
> Pyspark application will hang due to non Exception
> --------------------------------------------------
>
> Key: SPARK-33339
> URL: https://issues.apache.org/jira/browse/SPARK-33339
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.5, 3.0.0, 3.0.1
> Reporter: lrz
> Assignee: lrz
> Priority: Major
> Fix For: 3.0.2, 3.1.0
>
>
> When a system.exit exception occurs during the process, the python worker
> exits abnormally, and then the executor task is still waiting for the worker
> for reading from socket, causing it to hang.
> The system.exit exception may be caused by the user's error code, but spark
> should at least throw an error to remind the user, not get stuck
> we can run a simple test to reproduce this case:
> {code:python}
> from pyspark.sql import SparkSession
> def err(line):
> raise SystemExit
> spark = SparkSession.builder.appName("test").getOrCreate()
> spark.sparkContext.parallelize(range(1,2), 2).map(err).collect()
> spark.stop()
> {code}
>
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