Re: Slow index scan on B-Tree index over timestamp field

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От Elliot
Тема Re: Slow index scan on B-Tree index over timestamp field
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Msg-id 52781027.7080307@gmail.com
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Ответ на Re: Slow index scan on B-Tree index over timestamp field  (Caio Casimiro <casimiro.listas@gmail.com>)
Ответы Re: Slow index scan on B-Tree index over timestamp field  (Caio Casimiro <casimiro.listas@gmail.com>)
Список pgsql-performance
On 2013-11-04 16:10, Caio Casimiro wrote:
Hi Neyman, thank you for your answer.

Unfortunately this query runs almost at the same time:

Sort  (cost=4877693.98..4877702.60 rows=3449 width=20) (actual time=25820.291..25821.845 rows=1640 loops=1)
  Sort Key: tt.tweet_id
  Sort Method: quicksort  Memory: 97kB
  Buffers: shared hit=1849 read=32788
  ->  Nested Loop  (cost=247.58..4877491.32 rows=3449 width=20) (actual time=486.839..25814.120 rows=1640 loops=1)
        Buffers: shared hit=1849 read=32788
        ->  Hash Semi Join  (cost=229.62..88553.23 rows=1681 width=8) (actual time=431.654..13209.159 rows=597 loops=1)
              Hash Cond: (t.user_id = relationship.followed_id)
              Buffers: shared hit=3 read=31870
              ->  Index Scan using tweet_creation_time_index on tweet t  (cost=0.57..83308.25 rows=1781234 width=16) (actual time=130.144..10037.764 rows=1759645 loops=1)
                    Index Cond: ((creation_time >= '2013-05-05 00:00:00-03'::timestamp with time zone) AND (creation_time <= '2013-05-06 00:00:00-03'::timestamp with time zone))
                    Buffers: shared hit=1 read=31867
              ->  Hash  (cost=227.12..227.12 rows=154 width=8) (actual time=94.365..94.365 rows=106 loops=1)
                    Buckets: 1024  Batches: 1  Memory Usage: 3kB
                    Buffers: shared hit=2 read=3
                    ->  Index Only Scan using relationship_id on relationship  (cost=0.42..227.12 rows=154 width=8) (actual time=74.540..94.101 rows=106 loops=1)
                          Index Cond: (follower_id = 335093362)
                          Heap Fetches: 0
                          Buffers: shared hit=2 read=3
        ->  Bitmap Heap Scan on tweet_topic tt  (cost=17.96..2841.63 rows=723 width=20) (actual time=21.014..21.085 rows=3 loops=597)
              Recheck Cond: (tweet_id = t.id)
              Buffers: shared hit=1846 read=918
              ->  Bitmap Index Scan on tweet_topic_pk  (cost=0.00..17.78 rows=723 width=0) (actual time=15.012..15.012 rows=3 loops=597)
                    Index Cond: (tweet_id = t.id)
                    Buffers: shared hit=1763 read=632
Total runtime: 25823.386 ms

I have noticed that in both queries the index scan on tweet_creation_time_index is very expensive. Is there anything I can do to make the planner choose a index only scan?


Yes, because that part of the query is kicking back so many rows, many of which are totally unnecessary anyway - you're first getting all the tweets in a particular time range, then limiting them down to just users that are followed. Here's clarification on the approach I mentioned earlier. All you should really need are basic (btree) indexes on your different keys (tweet_topic.tweet_id, tweet.id, tweet.user_id, relationship.follower_id, relationship.followed_id). I also changed the left join to an inner join as somebody pointed out that your logic amounted to reducing the match to an inner join anyway.

SELECT tt.tweet_id, tt.topic, tt.topic_value
FROM tweet_topic AS tt
  JOIN tweet AS t
    ON tt.tweet_id = t.id
  join relationship
    on t.user_id = relationship.followed_id
WHERE creation_time BETWEEN 'D1' AND 'D2'
  AND relationship.follower_id = N
ORDER BY tt.tweet_id
;

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