Re: very slow queries when max_parallel_workers_per_gather is higherthan zero

> Query Performs nicely, but no parallel workers are used:
> GroupAggregate  (cost=2611148.87..2611152.89 rows=31 width=22) (actual
> time=0.084..0.084 rows=0 loops=1)
>    Group Key:
> f_zendesktickets_aaeljtllr5at3el.cstm_custom_38746665_primary_column
>    ->  Sort  (cost=2611148.87..2611149.11 rows=99 width=28) (actual
> time=0.082..0.082 rows=0 loops=1)
>          Sort Key:
> f_zendesktickets_aaeljtllr5at3el.cstm_custom_38746665_primary_column
>          Sort Method: quicksort  Memory: 25kB
>          ->  Nested Loop  (cost=1639.25..2611145.59 rows=99 width=28)
> (actual time=0.076..0.076 rows=0 loops=1)
>                Join Filter:
> (((f_ticketattributeshistory_aajzjp98uraszb6.attrnewvalue_id = ANY
> ('{4757,4758,4759}'::integer[])) AND (4754 =
> f_ticketattributeshistory_aajzjp98uraszb6.attroldvalue_id) AND (4790 =
> f_ticketattributeshistory_aajzjp98uraszb6.ticketfield_id)) OR
> (f_zendesktickets_aaeljtllr5at3el.dt_createda
> t_id = f_ticketupdate_aad5jtwal0ayaax.dt_event_id))
>                ->  Nested Loop  (cost=1638.81..1809540.39 rows=350270
> width=20) (actual time=0.075..0.075 rows=0 loops=1)
>                      ->  Nested Loop  (cost=1638.24..1508474.08
> rows=69140 width=8) (actual time=0.075..0.075 rows=0 loops=1)
>                            ->  Bitmap Heap Scan on
> dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61iagl1z
> dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61ia 
> (cost=4.34..27.35 rows=7 width=4) (actual time=0.026..0.038 rows=7 loops=1)
>                                  Recheck Cond: (6171 = id_euweek)
>                                  Heap Blocks: exact=7
>                                  ->  Bitmap Index Scan on
> dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_a_id_euweek_idx 
> (cost=0.00..4.33 rows=7 width=0) (actual time=0.019..0.019 rows=7 loops=1)
>                                        Index Cond: (6171 = id_euweek)
>                            ->  Bitmap Heap Scan on
> f_ticketupdate_aad5jtwal0ayaax  (cost=1633.90..214617.67 rows=87472
> width=8) (actual time=0.004..0.004 rows=0 loops=7)
>                                  Recheck Cond: (dt_event_id =

> dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61ia.id
> <http://dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61ia.id>)
>                                  ->  Bitmap Index Scan on
> f_ticketupdate_aad5jtwal0ayaax_dt_event_id_idx  (cost=0.00..1612.03
> rows=87472 width=0) (actual time=0.003..0.003 rows=0 loops=7)
>                                        Index Cond: (dt_event_id =
> dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61ia.id
> <http://dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61ia.id>)
>                      ->  Index Scan using
> f_ticketattributeshistory_aajzjp98uraszb6_ticketupdate_id_idx on
> f_ticketattributeshistory_aajzjp98uraszb6  (cost=0.57..4.12 rows=23
> width=20) (never executed)
>                            Index Cond: (ticketupdate_id =
> f_ticketupdate_aad5jtwal0ayaax.id
> <http://f_ticketupdate_aad5jtwal0ayaax.id>)
>                ->  Index Scan using
> f_zendesktickets_aaeljtllr5at3el_pkey on
> f_zendesktickets_aaeljtllr5at3el  (cost=0.43..2.27 rows=1 width=12)
> (never executed)
>                      Index Cond: (id =
> f_ticketattributeshistory_aajzjp98uraszb6.zendesktickets_id)
>                      Filter: ((4765 <> status_id) AND (group_id = 17429))
>  Planning time: 8.516 ms
>  Execution time: 1.895 ms
>
> the speed is back
>

Yeah, but the cost is higher (2611152 vs. 1949508). So clearly, the
database believes it's going to be cheaper. I suspect a part of the
issue might be that the join is misestimated - it's expected to produce
~29k rows, but produces 0.

Can you check if this query has the same issue? It's just the
problematic join, and it should be simpler to investigate:

SELECT count(*)
  FROM f_ticketupdate_aad5jtwal0ayaax AS f
  INNER JOIN
  dwh_dm_aabv5kk9rxac4lz_aaonw7nchsan2n1_aad8xhr0m_aaewg8j61iagl1z AS d
  ON (f.dt_event_id = d.id)

regards

--
Tomas Vondra                  http://www.2ndQuadrant.com
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