16b_baseline.txt

text/plain

Filename: 16b_baseline.txt
Type: text/plain
Part: 5
Message: Re: Is there value in having optimizer stats for joins/foreignkeys?
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SET
                                                                                        QUERY PLAN                                                                                        
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Aggregate  (cost=5353.71..5353.72 rows=1 width=64) (actual time=10607.642..10607.644 rows=1.00 loops=1)
   Buffers: shared hit=22223141 read=1381834
   ->  Nested Loop  (cost=9.37..5337.88 rows=3165 width=33) (actual time=2.503..9525.673 rows=3710592.00 loops=1)
         Join Filter: (an.person_id = n.id)
         Buffers: shared hit=22223141 read=1381834
         ->  Nested Loop  (cost=8.95..4667.49 rows=1378 width=25) (actual time=2.490..6179.436 rows=2832555.00 loops=1)
               Buffers: shared hit=11897439 read=1107501
               ->  Nested Loop  (cost=8.52..4048.53 rows=1378 width=21) (actual time=2.481..3069.508 rows=2832555.00 loops=1)
                     Join Filter: (ci.movie_id = t.id)
                     Buffers: shared hit=3159885 read=751362
                     ->  Nested Loop  (cost=8.08..3929.09 rows=63 width=29) (actual time=2.245..937.683 rows=68316.00 loops=1)
                           Buffers: shared hit=815660 read=146762
                           ->  Nested Loop  (cost=7.66..3850.15 rows=177 width=33) (actual time=2.224..598.822 rows=148552.00 loops=1)
                                 Join Filter: (mc.movie_id = t.id)
                                 Buffers: shared hit=295838 read=72376
                                 ->  Nested Loop  (cost=7.23..3829.71 rows=34 width=25) (actual time=2.185..494.519 rows=41840.00 loops=1)
                                       Buffers: shared hit=125415 read=54538
                                       ->  Nested Loop  (cost=6.80..3813.14 rows=34 width=4) (actual time=2.177..346.122 rows=41840.00 loops=1)
                                             Buffers: shared hit=24 read=12569
                                             ->  Seq Scan on keyword k  (cost=0.00..2685.11 rows=1 width=4) (actual time=0.382..7.022 rows=1.00 loops=1)
                                                   Filter: (keyword = 'character-name-in-title'::text)
                                                   Rows Removed by Filter: 134168
                                                   Buffers: shared hit=22 read=986
                                             ->  Bitmap Heap Scan on movie_keyword mk  (cost=6.80..1124.98 rows=305 width=8) (actual time=1.794..336.613 rows=41840.00 loops=1)
                                                   Recheck Cond: (k.id = keyword_id)
                                                   Heap Blocks: exact=11547
                                                   Buffers: shared hit=2 read=11583
                                                   ->  Bitmap Index Scan on keyword_id_movie_keyword  (cost=0.00..6.72 rows=305 width=0) (actual time=0.965..0.965 rows=41840.00 loops=1)
                                                         Index Cond: (keyword_id = k.id)
                                                         Index Searches: 1
                                                         Buffers: shared hit=2 read=36
                                       ->  Index Scan using title_pkey on title t  (cost=0.43..0.49 rows=1 width=21) (actual time=0.003..0.003 rows=1.00 loops=41840)
                                             Index Cond: (id = mk.movie_id)
                                             Index Searches: 41840
                                             Buffers: shared hit=125391 read=41969
                                 ->  Index Scan using movie_id_movie_companies on movie_companies mc  (cost=0.43..0.54 rows=5 width=8) (actual time=0.002..0.002 rows=3.55 loops=41840)
                                       Index Cond: (movie_id = mk.movie_id)
                                       Index Searches: 41840
                                       Buffers: shared hit=170423 read=17838
                           ->  Index Scan using company_name_pkey on company_name cn  (cost=0.42..0.45 rows=1 width=4) (actual time=0.002..0.002 rows=0.46 loops=148552)
                                 Index Cond: (id = mc.company_id)
                                 Filter: ((country_code)::text = '[us]'::text)
                                 Rows Removed by Filter: 1
                                 Index Searches: 148552
                                 Buffers: shared hit=519822 read=74386
                     ->  Index Scan using movie_id_cast_info on cast_info ci  (cost=0.44..1.40 rows=40 width=8) (actual time=0.003..0.029 rows=41.46 loops=68316)
                           Index Cond: (movie_id = mk.movie_id)
                           Index Searches: 68316
                           Buffers: shared hit=2344225 read=604600
               ->  Index Only Scan using name_pkey on name n  (cost=0.43..0.45 rows=1 width=4) (actual time=0.001..0.001 rows=1.00 loops=2832555)
                     Index Cond: (id = ci.person_id)
                     Heap Fetches: 0
                     Index Searches: 2832555
                     Buffers: shared hit=8737554 read=356139
         ->  Index Scan using person_id_aka_name on aka_name an  (cost=0.42..0.46 rows=2 width=20) (actual time=0.001..0.001 rows=1.31 loops=2832555)
               Index Cond: (person_id = ci.person_id)
               Index Searches: 2832555
               Buffers: shared hit=10325702 read=274333
 Planning:
   Buffers: shared hit=550 read=125
 Planning Time: 4.686 ms
 Execution Time: 10607.707 ms
(62 rows)