X-Original-To: pgsql-sql-postgresql.org@localhost.postgresql.org Received: from localhost (unknown [200.46.204.144]) by svr1.postgresql.org (Postfix) with ESMTP id 5486F566F4 for ; Tue, 22 Mar 2005 19:33:29 +0000 (GMT) Received: from svr1.postgresql.org ([200.46.204.71]) by localhost (av.hub.org [200.46.204.144]) (amavisd-new, port 10024) with ESMTP id 49615-02 for ; Tue, 22 Mar 2005 19:33:20 +0000 (GMT) Received: from mx5.net.nih.gov (mx5.net.nih.gov [165.112.130.36]) by svr1.postgresql.org (Postfix) with ESMTP id B883B56796 for ; Tue, 22 Mar 2005 19:33:12 +0000 (GMT) Received: from mx5.net.nih.gov (localhost [127.0.0.1]) by mx5.net.nih.gov (8.12.10/8.11.6) with ESMTP id j2MJXCaq028731 for ; Tue, 22 Mar 2005 14:33:12 -0500 Received: from [128.231.145.14] (holmes.nhgri.nih.gov [128.231.145.14]) by mx5.net.nih.gov (8.12.10/8.11.6) with ESMTP id j2MJXCKd028728 for ; Tue, 22 Mar 2005 14:33:12 -0500 Mime-Version: 1.0 (Apple Message framework v619.2) Content-Transfer-Encoding: 7bit Message-Id: <0af8c6d3baaf3d4a6d918df294019507@mail.nih.gov> Content-Type: text/plain; charset=US-ASCII; delsp=yes; format=flowed To: PostgreSQL SQL From: Sean Davis Subject: Self-referencing table question Date: Tue, 22 Mar 2005 14:33:12 -0500 X-Mailer: Apple Mail (2.619.2) X-Virus-Scanned: by amavisd-new at hub.org X-Spam-Status: No, hits=0.006 tagged_above=0 required=5 tests=AWL X-Spam-Level: X-Archive-Number: 200503/302 X-Sequence-Number: 20781 I have a table that looks like: Column | Type | Modifiers | Description ---------+--------------+-----------+------------- from_id | integer | not null | to_id | integer | not null | val | numeric(4,3) | | Indexes: "correlation_pkey" PRIMARY KEY, btree (from_id, to_id) "correlation_from_id_idx" btree (from_id) "correlation_to_id_idx" btree (to_id) "correlation_val_idx" btree (val) Has OIDs: yes The table describes a pairwise correlation matrix between about 7700 vectors (so the table has n^2= 60652944 rows, to be exact). I am trying to choose the top 100 correlated vectors with a seed vector; this is easily: select to_id from correlation where from_id=623 order by val desc limit 100; Then, I want to take those 100 values and find all from_id,to_id tuples where val>0.5 (to construct a graph where all "ids" are nodes and are connected to each other when their correlation is >0.5). I can do this like: explain analyze select from_id,to_id,val from exprsdb.correlation where from_id in (1,2,3,4,5,6,7,8,10,9,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27 ,28,29,30) and to_id in (1,2,3,4,5,6,7,8,10,9,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27 ,28,29,30) and from_id>to_id and val>0.5; However, this does not scale well AT ALL. The actual (very messy) explain analyze output is below. The thing I notice is that the index on to_id is not used. Also, the primary key index on (from_id, to_id is not used, it seems. Finally, with only 30 values, this already takes 2.6 seconds and I am proposing to do this on 100-200 values. Any hints on how better to accomplish this set of tasks? Index Scan using correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx, correlation_from_id_idx on correlation (cost=0.00..129377.49 rows=62 width=17) (actual time=340.563..2603.967 rows=19 loops=1) Index Cond: ((from_id = 1) OR (from_id = 2) OR (from_id = 3) OR (from_id = 4) OR (from_id = 5) OR (from_id = 6) OR (from_id = 7) OR (from_id = 8) OR (from_id = 10) OR (from_id = 9) OR (from_id = 11) OR (from_id = 12) OR (from_id = 13) OR (from_id = 14) OR (from_id = 15) OR (from_id = 16) OR (from_id = 17) OR (from_id = 18) OR (from_id = 19) OR (from_id = 20) OR (from_id = 21) OR (from_id = 22) OR (from_id = 23) OR (from_id = 24) OR (from_id = 25) OR (from_id = 26) OR (from_id = 27) OR (from_id = 28) OR (from_id = 29) OR (from_id = 30)) Filter: (((to_id = 1) OR (to_id = 2) OR (to_id = 3) OR (to_id = 4) OR (to_id = 5) OR (to_id = 6) OR (to_id = 7) OR (to_id = 8) OR (to_id = 10) OR (to_id = 9) OR (to_id = 11) OR (to_id = 12) OR (to_id = 13) OR (to_id = 14) OR (to_id = 15) OR (to_id = 16) OR (to_id = 17) OR (to_id = 18) OR (to_id = 19) OR (to_id = 20) OR (to_id = 21) OR (to_id = 22) OR (to_id = 23) OR (to_id = 24) OR (to_id = 25) OR (to_id = 26) OR (to_id = 27) OR (to_id = 28) OR (to_id = 29) OR (to_id = 30)) AND (from_id > to_id) AND (val > 0.5)) Total runtime: 2604.383 ms Thanks, Sean