Re: Parallel Append implementation

>
> But as far as code is concerned, I think the two-list approach will
> turn out to be less simple if we derive corresponding two different
> arrays in AppendState node. Handling two different arrays during
> execution does not look clean. Whereas, the bitmapset that I have used
> in Append has turned out to be very simple. I just had to do the below
> check (and that is the only location) to see if it's a partial or
> non-partial subplan. There is nowhere else any special handling for
> non-partial subpath.
>
> /*
> * Increment worker count for the chosen node, if at all we found one.
> * For non-partial plans, set it to -1 instead, so that no other workers
> * run it.
> */
> if (min_whichplan != PA_INVALID_PLAN)
> {
>    if (bms_is_member(min_whichplan,
> ((Append*)state->ps.plan)->partial_subplans_set))
>            padesc->pa_info[min_whichplan].pa_num_workers++;
>    else
>            padesc->pa_info[min_whichplan].pa_num_workers = -1;
> }
>
> Now, since Bitmapset field is used during execution with such
> simplicity, why not have this same data structure in AppendPath, and
> re-use bitmapset field in Append plan node without making a copy of
> it. Otherwise, if we have two lists in AppendPath, and a bitmap in
> Append, again there is going to be code for data structure conversion.
>

I think there is some merit in separating out non-parallel and
parallel plans within the same array or outside it. The current logic
to assign plan to a worker looks at all the plans, unnecessarily
hopping over the un-parallel ones after they are given to a worker. If
we separate those two, we can keep assigning new workers to the
non-parallel plans first and then iterate over the parallel ones when
a worker needs a plan to execute. We might eliminate the need for
special value -1 for num workers. You may separate those two kinds in
two different arrays or within the same array and remember the
smallest index of a parallel plan.

-- 
Best Wishes,
Ashutosh Bapat
EnterpriseDB Corporation
The Postgres Database Company