`pmap_reduce` function

I have need for a pmap_reduce function.

In Julia v0.5 and earlier, I was able to customize the base pmap to provide what I needed.
However since v0.6, parallel processing including pmap has been overhauled and largely rewritten. To a non-expert like me, it is much more complex and impenetrable, compared to the simpler implementation of earlier versions, which is still given as an example in the Parallel Computing section of the manual. https://docs.julialang.org/en/stable/manual/parallel-computing/#Scheduling-1

Are there any issues with continuing in v0.6 and later to model my own pmap_reduce on the v0.5 pmap? What are the benefits of the new implementation of pmap?

Alternatively, would you consider a feature request for an official pmap_reduce?

Start with the Parallel Computing manual's Scheduling section and compare its Julia v0.5 pmap example with the current v0.6-and-later pmap implementation. Investigate the current pmap entry point and determine whether a supported pmap_reduce API is needed, including its expected behavior and benefits over the older approach. Done means the feature scope and API are agreed, with appropriate coverage for the proposed behavior.