Hello, thank you for your answer. I will give it a try and then I post here the results.
In the original email I post the output of \d+ tweet, which contains the indexes and constraints.
Best regards,
Caio
On Mon, Nov 4, 2013 at 8:59 PM, desmodemone <desmodemone@xxxxxxxxx> wrote:
Hello,I think you could try with an index on tweet table columns "user_id, creation_time" [in this order , because the first argument is for the equality predicate and the second with the range scan predicate, the index tweet_user_id_creation_time_index is not ok because it has the reverse order ] so the Hash Join between relationship and tweet will become in theory a netsted loop and so the filter relationship.followed_id = t.user_id will be pushed on the new index search condition with also the creation_time > .. and creation_time < ... . In this manner you will reduce the random i/o of the scanning of 1759645 rows from tweet that are filter later now in hash join to 1679.
I hope it will work, if not, I hope you could attach the DDL of the table ( with constraints and indexes) to better understand the problem.Bye2013/11/4 Caio Casimiro <casimiro.listas@xxxxxxxxx>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)"" -> 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,CaioOn Mon, Nov 4, 2013 at 7:22 PM, Elliot <yields.falsehood@xxxxxxxxx> wrote:
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.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_idSort Method: quicksort Memory: 97kBBuffers: 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: 3kBBuffers: 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: 0Buffers: 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=632Total 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?
ON tt.tweet_id = t.id
SELECT tt.tweet_id, tt.topic, tt.topic_value
FROM tweet_topic AS tt
JOIN tweet AS t
join relationship
on t.user_id = relationship.followed_idAND relationship.follower_id = N
WHERE creation_time BETWEEN 'D1' AND 'D2'
ORDER BY tt.tweet_id
;
