Re: [HACKERS] parallelize queries containing initplans

On Wed, Aug 9, 2017 at 10:24 AM, Haribabu Kommi
<kommi.haribabu@gmail.com> wrote:
>
> I tested the latest patch and the parallel plan is getting choose for most
> of
> the init plans.
>
Thanks for testing.

> For the following query the parallel plan is not chosen. The query contains
> an init plan that refer the outer node.
>
> postgres=# explain analyze select * from t1 where t1.i in (select t2.i from
> t2 where t1.k = (select max(k) from t3 where t3.i=t1.i));
>                                                      QUERY PLAN
> ---------------------------------------------------------------------------------------------------------------------
>  Seq Scan on t1  (cost=0.00..22426.28 rows=448 width=12) (actual
> time=8.335..132.557 rows=2 loops=1)
>    Filter: (SubPlan 2)
>    Rows Removed by Filter: 894
>    SubPlan 2
>      ->  Result  (cost=16.27..31.26 rows=999 width=4) (actual
> time=0.146..0.146 rows=0 loops=896)
>            One-Time Filter: (t1.k = $1)
>            InitPlan 1 (returns $1)
>              ->  Aggregate  (cost=16.25..16.27 rows=1 width=4) (actual
> time=0.145..0.145 rows=1 loops=896)
>                    ->  Seq Scan on t3  (cost=0.00..16.25 rows=2 width=4)
> (actual time=0.131..0.144 rows=0 loops=896)
>                          Filter: (i = t1.i)
>                          Rows Removed by Filter: 900
>            ->  Seq Scan on t2  (cost=16.27..31.26 rows=999 width=4) (actual
> time=0.012..0.013 rows=10 loops=2)
>  Planning time: 0.272 ms
>  Execution time: 132.623 ms
> (14 rows)
>

An observation is that the filter at Result node can't be pushed down
to the sequential scan on t2 because the filter is on t1. So, it has
to scan the complete t2 relation and send all the tuple to upper node,
a worst case for parallelism. Probably, this is the reason the
optimizer doesn't pick parallel plan for the above case.

Just for clarification, do you see any changes in the plan after
forcing parallelism(parallel_tuple_cost, parallel_setup_cost,
min_parallel_table_scan_size=0)?