## What changes were proposed in this pull request?
We are now forced to use `pyspark/daemon.py` and `pyspark/worker.py` in PySpark.
This doesn't allow a custom modification for it (well, maybe we can still do this in a super hacky way though, for example, setting Python executable that has the custom modification). Because of this, for example, it's sometimes hard to debug what happens inside Python worker processes.
This is actually related with [SPARK-7721](https://issues.apache.org/jira/browse/SPARK-7721) too as somehow Coverage is unable to detect the coverage from `os.fork`. If we have some custom fixes to force the coverage, it works fine.
This is also related with [SPARK-20368](https://issues.apache.org/jira/browse/SPARK-20368). This JIRA describes Sentry support which (roughly) needs some changes within worker side.
With this configuration advanced users will be able to do a lot of pluggable workarounds and we can meet such potential needs in the future.
As an example, let's say if I configure the module `coverage_daemon` and had `coverage_daemon.py` in the python path:
```python
import os
from pyspark import daemon
if "COVERAGE_PROCESS_START" in os.environ:
from pyspark.worker import main
def _cov_wrapped(*args, **kwargs):
import coverage
cov = coverage.coverage(
config_file=os.environ["COVERAGE_PROCESS_START"])
cov.start()
try:
main(*args, **kwargs)
finally:
cov.stop()
cov.save()
daemon.worker_main = _cov_wrapped
if __name__ == '__main__':
daemon.manager()
```
I can track the coverages in worker side too.
More importantly, we can leave the main code intact but allow some workarounds.
## How was this patch tested?
Manually tested.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#20151 from HyukjinKwon/configuration-daemon-worker.
afae8f2bc8