Re: [HACKERS] Parallel Plans and Cost of non-filter functions

I'm working on a custom aggregate, that generates a serialized data format. The preparation of the geometry before being formatted is pretty intense, so it is probably a good thing for that work to be done in parallel, in partial aggregates. Here's an example SQL call:

EXPLAIN analyze

SELECT length(ST_AsMVT(a)) FROM (

    SELECT ST_AsMVTGeom(p.geom, ::geometry_literal, 4096, 0, true), gid, fed_num

    FROM pts_10 p

    WHERE p.geom && ::geometry_literal

    AND p.geom IS NOT NULL

    ) a;

The ST_AsMVTGeom() function can be comically expensive, it's really good when it's in partial aggregates. But the cost of the function seems to be ignored.

(First note that, in order to consistently get parallel plans I have to brutally suppress parallel_tuple_cost, as described here http://blog.cleverelephant.ca/2017/10/parallel-postgis-2.html)

Whether I get a parallel aggregate seems entirely determined by the number of rows, not the cost of preparing those rows.

When changing the number of rows in the subquery, with a LIMIT, I can change from a seq scan to a paralllel seq scan and finally to a parallel aggregate, as the number of rows goes up. 

An odd effect: when I have enough rows to get a paralllel seq scan, I get flip it back to a seq scan, by *increasing* the cost of ST_AsMVTGeom. That seems odd and backwards.

Is there anywhere a guide or rough description to how costs are used in determining parallel plans? The empirical approach starts to wear one down after a while :)

P.