Re: plan_rows confusion with parallel queries - Mailing list pgsql-hackers
| From | Tomas Vondra |
|---|---|
| Subject | Re: plan_rows confusion with parallel queries |
| Date | |
| Msg-id | fadacbae-7810-b007-9274-70ebf9d7b862@2ndquadrant.com Whole thread Raw |
| In response to | Re: plan_rows confusion with parallel queries (Tomas Vondra <tomas.vondra@2ndquadrant.com>) |
| Responses |
Re: plan_rows confusion with parallel queries
Re: plan_rows confusion with parallel queries |
| List | pgsql-hackers |
On 11/02/2016 11:56 PM, Tomas Vondra wrote:
> On 11/02/2016 09:00 PM, Tom Lane wrote:
>> Tomas Vondra <tomas.vondra@2ndquadrant.com> writes:
>>> while eye-balling some explain plans for parallel queries, I got a bit
>>> confused by the row count estimates. I wonder whether I'm alone.
>>
>> I got confused by that a minute ago, so no you're not alone. The problem
>> is even worse in join cases. For example:
>>
>> Gather (cost=34332.00..53265.35 rows=100 width=8)
>> Workers Planned: 2
>> -> Hash Join (cost=33332.00..52255.35 rows=100 width=8)
>> Hash Cond: ((pp.f1 = cc.f1) AND (pp.f2 = cc.f2))
>> -> Append (cost=0.00..8614.96 rows=417996 width=8)
>> -> Parallel Seq Scan on pp (cost=0.00..8591.67
>> rows=416667 widt
>> h=8)
>> -> Parallel Seq Scan on pp1 (cost=0.00..23.29
>> rows=1329 width=8
>> )
>> -> Hash (cost=14425.00..14425.00 rows=1000000 width=8)
>> -> Seq Scan on cc (cost=0.00..14425.00 rows=1000000
>> width=8)
>>
>> There are actually 1000000 rows in pp, and none in pp1. I'm not bothered
>> particularly by the nonzero estimate for pp1, because I know where that
>> came from, but I'm not very happy that nowhere here does it look like
>> it's estimating a million-plus rows going into the join.
>>
Although - it is estimating 1M rows, but only "per worker" estimates are
shown, and because there are 2 workers planned it says 1M/2.4 which is
the 416k. I agree it's a bit unclear, but at least it's consistent with
how we treat loops (i.e. that the numbers are per loop).
But there's more fun with joins - consider for example this simple join:
QUERY PLAN
------------------------------------------------------------------------------ Gather (cost=19515.96..43404.82
rows=96957width=12) (actual time=295.167..746.312 rows=99999 loops=1) Workers Planned: 2 Workers Launched:
2 -> Hash Join (cost=18515.96..32709.12 rows=96957 width=12) (actual time=249.281..670.309
rows=33333loops=3) Hash Cond: (t2.a = t1.a) -> Parallel Seq Scan on t2 (cost=0.00..8591.67
rows=416667width=8) (actual time=0.100..184.315 rows=333333 loops=3) -> Hash
(cost=16925.00..16925.00rows=96957 width=8) (actual time=246.760..246.760 rows=99999 loops=3)
Buckets: 131072 Batches: 2 Memory Usage: 2976kB -> Seq Scan on t1
(cost=0.00..16925.00rows=96957 width=8) (actual time=0.065..178.385 rows=99999 loops=3)
Filter: (b < 100000) Rows Removed by Filter: 900001 Planning time: 0.763 ms Execution time:
793.653ms
(13 rows)
Suddenly we don't show per-worker estimates for the hash join - both the
Hash Join and the Gather have exactly the same cardinality estimate.
Now, let's try forcing Nested Loops and see what happens:
QUERY PLAN
----------------------------------------------------------------------------- Gather (cost=1000.42..50559.65
rows=96957width=12) (actual time=0.610..203.694 rows=99999 loops=1) Workers Planned: 2 Workers Launched: 2
-> Nested Loop (cost=0.42..39863.95 rows=96957 width=12) (actual time=0.222..182.755 rows=33333
loops=3) -> Parallel Seq Scan on t1 (cost=0.00..9633.33 rows=40399 width=8)
(actual time=0.030..40.358 rows=33333 loops=3) Filter: (b < 100000) Rows Removed by
Filter:300000 -> Index Scan using t2_a_idx on t2 (cost=0.42..0.74 rows=1 width=8)
(actualtime=0.002..0.002 rows=1 loops=99999) Index Cond: (a = t1.a) Planning time: 0.732 ms Execution
time:250.707 ms
(11 rows)
So, different join method but same result - 2 workers, loops=3. But
let's try with small tables (100k rows instead of 1M rows):
QUERY PLAN
---------------------------------------------------------------------------- Gather (cost=0.29..36357.94 rows=100118
width=12)(actual
time=13.219..589.723 rows=100000 loops=1) Workers Planned: 1 Workers Launched: 1 Single Copy: true -> Nested
Loop (cost=0.29..36357.94 rows=100118 width=12) (actual time=0.288..442.821 rows=100000 loops=1)
-> Seq Scan on t1 (cost=0.00..1444.18 rows=100118 width=8) (actual time=0.148..49.308
rows=100000loops=1) -> Index Scan using t2_a_idx on t2 (cost=0.29..0.34 rows=1 width=8)
(actual time=0.002..0.002 rows=1 loops=100000) Index Cond: (a = t1.a) Planning time:
0.483ms Execution time: 648.941 ms
(10 rows)
Suddenly, we get nworkers=1 with loops=1 (and not nworkers+1 as before).
FWIW I've only seen this with force_parallel_mode=on, and the row counts
are correct, so perhaps that's OK. single_copy seems a bit
underdocumented, though.
regards
--
Tomas Vondra http://www.2ndQuadrant.com
PostgreSQL Development, 24x7 Support, Remote DBA, Training & Services
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