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Hello, I've got a very simple table with a very simple SELECT query, but it takes longer on the initial run than I'd like, so I want to see if there is a strategy to optimize this. Table rt_h_nbbo contains several hundred million rows. All rows for a given entry_date are appended to this table in an overnight process every night - on the order of several million rows each night. The objective is to select all of the rows for a given product_id on a given entry_date. There is a b-tree index on (product_id, entry_date) called rt_h_nbbo_idx. The index appears to be used correctly. I'm seeing that if the data pages are not in memory, nearly all of the time is spent on disk I/O. The first time, the query takes 21 sec. If I run this query a second time, it completes in approx 1-2 ms. Running select pg_relation_size( 'rt_h_nbbo') / reltuples FROM pg_class WHERE relname = 'rt_h_nbbo'; yields roughly 135 bytes/row. I perceive an inefficiency here and I'd like your input as to how to deal with it: The end result of the query is 1631 rows which is approx 220 kb of data (at 135 bytes/row). Compare that to the amount of I/O that was done: 1634 buffers were loaded, 8 kb per buffer - that's about 13Mb of data! Query completed in 21 sec. So 13Mb of data was read from disk, but only 220Kb was useful - about 1.7%. I'd like to make this work faster and hopefully more efficiently. First question is: Does loading 13Mb of data in 21 sec seem kinda slow or about right (hardware specs at bottom of email)? Second question: Perhaps I can reduce the number of pages that contain the data I want by physically storing the data in such a way that it parallels the rt_h_nbbo_idx index? I recall you can do this in Sybase with a CLUSTERED index. The answer for Postgresql seems to be "yes, use the CLUSTER command". But this command does a one-time clustering and requires periodic re-clustering. Is this the best approach? Are there considerations with respect to the type of index (B-tree, GIST, SP-GIST) being used for CLUSTER ? Thanks -Sev Table (this is a fairly large table - hundreds of millions of rows): CREATE TABLE rt_h_nbbo ( product_id integer NOT NULL, bid_price double precision NOT NULL DEFAULT 0.0, bid_size integer NOT NULL DEFAULT 0, ask_price double precision NOT NULL DEFAULT 0.0, ask_size integer NOT NULL DEFAULT 0, last_price double precision NOT NULL DEFAULT 0.0, entry_date date NOT NULL, entry_time time without time zone NOT NULL, event_time time without time zone NOT NULL, day_volume bigint NOT NULL DEFAULT 0, day_trade_ct integer, entry_id bigint NOT NULL, CONSTRAINT rt_h_nbbo_pkey PRIMARY KEY (entry_id), CONSTRAINT rt_h_nbbo_pfkey FOREIGN KEY (product_id) REFERENCES product (product_id) MATCH SIMPLE ON UPDATE NO ACTION ON DELETE NO ACTION ) WITH ( OIDS=FALSE ); ALTER TABLE rt_h_nbbo OWNER TO postgres; Index: CREATE INDEX rt_h_nbbo_idx ON rt_h_nbbo USING btree (product_id, entry_date DESC); Test: SET track_io_timing = on; EXPLAIN (ANALYZE,BUFFERS,VERBOSE,COSTS,TIMING) select * from rt_h_nbbo where product_id=6508 and entry_date='2013-11-26'; Output: "Index Scan using rt_h_nbbo_idx on public.rt_h_nbbo (cost=0.00..12768.21 rows=3165 width=76) (actual time=12.549..21654.547 rows=1631 loops=1)" " Output: product_id, bid_price, bid_size, ask_price, ask_size, last_price, entry_date, entry_time, event_time, day_volume, day_trade_ct, entry_id" " Index Cond: ((rt_h_nbbo.product_id = 6508) AND (rt_h_nbbo.entry_date = '2013-11-26'::date))" " Buffers: shared hit=4 read=1634" " I/O Timings: read=21645.468" "Total runtime: 21655.002 ms" Hardware Top of the line HP DL380 G7 server with 32 Gb Ram, P410i RAID, 10K SAS drives in Raid-1 config. Wal on separate Raid-1 volume with 15K SAS drives. The only unusual thing here is that I'm running on Windows Server 2008 R2. |
