On Mon, Feb 20, 2017 at 10:54 AM, Ashutosh Bapat
<ashutosh.ba...@enterprisedb.com> wrote:
> On Sun, Feb 19, 2017 at 2:33 PM, Robert Haas <robertmh...@gmail.com> wrote:
>> On Fri, Feb 17, 2017 at 11:44 AM, Ashutosh Bapat
>> <ashutosh.ba...@enterprisedb.com> wrote:
>>> That's true for a partitioned table, but not necessarily for every
>>> append relation. Amit's patch is generic for all append relations. If
>>> the child plans are joins or subquery segments of set operations, I
>>> doubt if the same logic works. It may be better if we throw as many
>>> workers (or some function "summing" those up) as specified by those
>>> subplans. I guess, we have to use different logic for append relations
>>> which are base relations and append relations which are not base
>>> relations.
>> Well, I for one do not believe that if somebody writes a UNION ALL
>> with 100 branches, they should get 100 (or 99) workers.  Generally
>> speaking, the sweet spot for parallel workers on queries we've tested
>> so far has been between 1 and 4.  It's straining credulity to believe
>> that the number that's correct for parallel append is more than an
>> order of magnitude larger.  Since increasing resource commitment by
>> the logarithm of the problem size has worked reasonably well for table
>> scans, I believe we should pursue a similar approach here.
> Thanks for that explanation. I makes sense. So, something like this
> would work: total number of workers = some function of log(sum of
> sizes of relations). The number of workers allotted to each segment
> are restricted to the the number of workers chosen by the planner
> while planning that segment. The patch takes care of the limit right
> now. It needs to incorporate the calculation for total number of
> workers for append.

log(sum of sizes of relations) isn't well-defined for a UNION ALL query.

Robert Haas
EnterpriseDB: http://www.enterprisedb.com
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