Ami Koren added the comment:
Thanks David. using spawn - multiprocessing.get_context('spawn').Pool(... -
does the job . It does has it's flows - fork allows me to share data between
workers (especially large readonly memory database, which I don't want to
duplicate for
New submission from Ami Koren:
Happens on Linux (Debian), Linux version 3.16.0-4-amd64 .
Seems like a multiprocessing issue.
When I use both multiprocessing pool and subprocess somewhere in the same
python program, sometimes the subprocess become
'zombie', and the parent wait for