Re: Slow index scan on B-Tree index over timestamp field - Mailing list pgsql-performance

Hi Elliot, thank you for your answer.

I tried this query but it still suffer with index scan on tweet_creation_time_index:

"Sort  (cost=4899904.57..4899913.19 rows=3447 width=20) (actual time=37560.938..37562.503 rows=1640 loops=1)"

"  Sort Key: tt.tweet_id"

"  Sort Method: quicksort  Memory: 97kB"

"  Buffers: shared hit=1849 read=32788"

"  ->  Nested Loop  (cost=105592.06..4899702.04 rows=3447 width=20) (actual time=19151.036..37555.227 rows=1640 loops=1)"

"        Buffers: shared hit=1849 read=32788"

"        ->  Hash Join  (cost=105574.10..116461.68 rows=1679 width=8) (actual time=19099.848..19127.606 rows=597 loops=1)"

"              Hash Cond: (relationship.followed_id = t.user_id)"

"              Buffers: shared hit=3 read=31870"

"              ->  Index Only Scan using relationship_id on relationship  (cost=0.42..227.12 rows=154 width=8) (actual time=66.102..89.721 rows=106 loops=1)"

"                    Index Cond: (follower_id = 335093362)"

"                    Heap Fetches: 0"

"                    Buffers: shared hit=2 read=3"

"              ->  Hash  (cost=83308.25..83308.25 rows=1781234 width=16) (actual time=19031.916..19031.916 rows=1759645 loops=1)"

"                    Buckets: 262144  Batches: 1  Memory Usage: 61863kB"

"                    Buffers: shared hit=1 read=31867"

"                    ->  Index Scan using tweet_creation_time_index on tweet t  (cost=0.57..83308.25 rows=1781234 width=16) (actual time=48.595..13759.768 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"

"        ->  Bitmap Heap Scan on tweet_topic tt  (cost=17.96..2841.63 rows=723 width=20) (actual time=30.774..30.847 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=23.084..23.084 rows=3 loops=597)"

"                    Index Cond: (tweet_id = t.id)"

"                    Buffers: shared hit=1763 read=632"

You said that I would need B-Tree indexes on the fields that I want the planner to use index only scan, and I think I have them already on the tweet table:

"tweet_ios_index" btree (id, user_id, creation_time)

Shouldn't the tweet_ios_index be enough to make the scan over tweet_creation_time_index be a index only scan? And, more important, would it be really faster?

Thank you very much,

Caio

On Mon, Nov 4, 2013 at 7:22 PM, Elliot <yields.falsehood@gmail.com> wrote:

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
;