Finding out why parallel queries not avoided

2018-07-21 Thread Didier Carlier
I’m trying to find out why parallel queries are sometimes not used.

For example, I have 2 tables, calendar (1 row per day, ~3K rows) and measure 
(~300M rows) which includes a FK to calendar.

I.e knowing two day numbers, I can find out how many measures there are between 
these two dates with a 
select count(*) from measure m where m.fromdateid >=1462 and m.fromdateid < 
1826;
(1462 and 1826 are the calendar ids corresponding to 2015-01-01 and 2015-12-31)

This uses parallel query:
explain select count(*) from measure m where m.fromdateid >=1462 and 
m.fromdateid < 1826;
 QUERY PLAN 
 
--
Finalize Aggregate  (cost=3894860.64..3894860.65 rows=1 width=8)
  ->  Gather  (cost=3894860.61..3894860.62 rows=8 width=8)
Workers Planned: 8
->  Partial Aggregate  (cost=3894860.61..3894860.62 rows=1 width=8)
  ->  Parallel Bitmap Heap Scan on measure m  
(cost=11265.96..3881068.52 rows=5516835 width=0)
Recheck Cond: ((fromdateid >= 1462) AND (fromdateid < 1826))
->  Bitmap Index Scan on idx_measure_fromdate  
(cost=0.00..232.29 rows=44134699 width=0)
  Index Cond: ((fromdateid >= 1462) AND (fromdateid < 
1826))


The “equivalent" query without hard coding the day numbers gives this query 
plan:

explain select count(*) from calendar c1, calendar c2, measure m where 
 c1.stddate='2015-01-01' and c2.stddate='2015-12-31' and m.fromdateid 
>=c1.calendarid and m.fromdateid < c2.calendarid;
  QUERY PLAN
  
--
 Aggregate  (cost=5073362.73..5073362.74 rows=1 width=8)
   ->  Nested Loop  (cost=8718.47..4988195.81 rows=34066770 width=0)
 ->  Index Scan using calendar_stddate_unique on calendar c2  
(cost=0.28..2.30 rows=1 width=4)
   Index Cond: (stddate = '2015-12-31 00:00:00+01'::timestamp with 
time zone)
 ->  Nested Loop  (cost=8718.19..4647525.81 rows=34066770 width=4)
   ->  Index Scan using calendar_stddate_unique on calendar c1  
(cost=0.28..2.30 rows=1 width=4)
 Index Cond: (stddate = '2015-01-01 00:00:00+01'::timestamp 
with time zone)
   ->  Bitmap Heap Scan on measure m  (cost=8717.91..4306855.81 
rows=34066770 width=4)
 Recheck Cond: ((fromdateid >= c1.calendarid) AND 
(fromdateid < c2.calendarid))
 ->  Bitmap Index Scan on idx_measure_fromdate  
(cost=0.00..201.22 rows=34072527 width=0)
   Index Cond: ((fromdateid >= c1.calendarid) AND 
(fromdateid < c2.calendarid))

Both queries return the same answers but I don't see why the second one doesn't 
use parallel query.
I've tried a few different ways to express the same thing, e.g subselect, CTE 
etc in order to try to ease the query planner work but it always avoids the 
parallel query.
I also set the parallel_tuple_cost and parallel_setup_cost to 0 without success.

Any idea ? Or is there a way to ask the query planner more details about the 
decisions it makes ?

Kind regards,
Didier


Re: Finding out why parallel queries not avoided

2018-07-21 Thread David Rowley
On 21 July 2018 at 20:15, Didier Carlier  wrote:
> explain select count(*) from calendar c1, calendar c2, measure m where
>  c1.stddate='2015-01-01' and c2.stddate='2015-12-31' and m.fromdateid 
> >=c1.calendarid and m.fromdateid < c2.calendarid;
>   QUERY PLAN
> --
>  Aggregate  (cost=5073362.73..5073362.74 rows=1 width=8)
>->  Nested Loop  (cost=8718.47..4988195.81 rows=34066770 width=0)
>  ->  Index Scan using calendar_stddate_unique on calendar c2  
> (cost=0.28..2.30 rows=1 width=4)
>Index Cond: (stddate = '2015-12-31 00:00:00+01'::timestamp 
> with time zone)
>  ->  Nested Loop  (cost=8718.19..4647525.81 rows=34066770 width=4)
>->  Index Scan using calendar_stddate_unique on calendar c1  
> (cost=0.28..2.30 rows=1 width=4)
>  Index Cond: (stddate = '2015-01-01 
> 00:00:00+01'::timestamp with time zone)
>->  Bitmap Heap Scan on measure m  (cost=8717.91..4306855.81 
> rows=34066770 width=4)
>  Recheck Cond: ((fromdateid >= c1.calendarid) AND 
> (fromdateid < c2.calendarid))
>  ->  Bitmap Index Scan on idx_measure_fromdate  
> (cost=0.00..201.22 rows=34072527 width=0)
>Index Cond: ((fromdateid >= c1.calendarid) AND 
> (fromdateid < c2.calendarid))
>
> Both queries return the same answers but I don't see why the second one 
> doesn't use parallel query.

You'd likely be better of writing the query as:

select count(*) from measure where fromdateid >= (select calendarid
from calendar where stddate = '2015-01-01') and fromdateid < (select
calendarid from calendar where stddate = '2015-12-31');

The reason you get the poor nested loop plan is that nested loop is
the only join method that supports non-equijoin.

Unsure why you didn't get a parallel plan. Parallel in pg10 supports a
few more plan shapes than 9.6 did. Unsure what version you're using.


-- 
 David Rowley   http://www.2ndQuadrant.com/
 PostgreSQL Development, 24x7 Support, Training & Services