In contrast to the goal of issue #37, this ticket aims to support parallelization of a function across all Python servers.
To clarify:
Default behaviour in py is to execute a Python function on a server, selected using the configured scheduler
Issue #37 introduces the functionality of executing a single function on all Python servers, skipping the scheduler.
This issue also wants to skip the scheduler, but where it differs from issue #37 is to partition the input data set so that each Python server can tackle a different part of the problem.
Maybe these functions could go in a py-para.lfe module ...
This may only require:
In contrast to the goal of issue #37, this ticket aims to support parallelization of a function across all Python servers.
To clarify:
Maybe these functions could go in a
py-para.lfe
module ...Sources for reference: