[GitHub] [spark] JoshRosen commented on issue #25138: [SPARK-26175][PYSPARK] Closing stdin of the worker process right after fork

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JoshRosen commented on issue #25138: [SPARK-26175][PYSPARK] Closing stdin of the worker process right after fork
URL: https://github.com/apache/spark/pull/25138#issuecomment-511143818
 
 
   Good catch. This seems reasonable to me.
   
   One question, though: is it possible to add a regression test for this? Here's some brainstorming on how we might do that:
   
   - Prior to this patch's change, the example you gave would hang indefinitely upon cancellation, whereas afterwards it'll exit quickly, so maybe we can add a Python unit test alongside existing Python-initiated cancel (assuming that we have those tests in `.py` files or some other type of test case that lets us run PySpark code).
   - In our test, could we start an async job, wait until it's running, kill the job, then assert that the number of running tasks (as reported by executor status API) reaches 0 within some reasonable time period?
   - One risk in my proposal is race conditions in waiting for the tasks to kick off: if we cancel a task before it forks a child process then our test will spuriously pass (i.e. it wouldn't function as a reliable regression test). Fixing this is kinda tricky, though, because our usual trick of using semaphores / countdown latches doesn't work well in a cross-language world. Maybe our best option is to just hardcode some reasonable time constants there? Or have the Python code `touch` a file and then wait for that file to appear before killing the task (e.g. a subprocess of `touch /filename/picked/by/driver/in/advance && cat`).
   
   Just thinking aloud here; let me know if you can think of a cleaner way to test this (or whether we can regression-test this via some other means).

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