Re: Join slow on "large" tables - Mailing list pgsql-performance
From | Scott Marlowe |
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Subject | Re: Join slow on "large" tables |
Date | |
Msg-id | 1086648432.27200.37.camel@localhost.localdomain Whole thread Raw |
In response to | Join slow on "large" tables (Josué Maldonado <josue@lamundial.hn>) |
Responses |
Re: Join slow on "large" tables
|
List | pgsql-performance |
On Mon, 2004-06-07 at 16:19, Josué Maldonado wrote: > Hello list, > > Server is dual Xeon 2.4, 2GBRAM, Postgresql is running on partition: > /dev/sda9 29G 8.9G 20G 31% /home2 > /dev/sda9 on /home2 type jfs (rw) > > Version() > PostgreSQL 7.4 on i686-pc-linux-gnu, compiled by GCC gcc (GCC) 3.2 > 20020903 (Red Hat Linux 8.0 3.2-7) > > I have a view to join two tables inventory details (pkardex) and > inventory documents header (pmdoc) this view usually runs pretty slow as > indicated in the explain analyze, pkardex is 1943465 rows and its size > aprox 659MB, pmdoc is 1183520 rows and its size is aprox 314MB. The view > definition is: > > SELECT pkd_pk AS kpk, (pkd_stamp)::date AS kfecha, pkd_docto AS kdocto, > ((((pdc_custid)::text || ' '::text) || > (pdc_custname)::text))::character > varying(50) AS kclpv, pkd_saldo AS ksaldo, pkd_es AS kes, CASE WHEN > (pkd_es > = 'E'::bpchar) THEN pkd_qtyinv ELSE (0)::numeric END AS kentrada, > CASE WHEN > (pkd_es = 'S'::bpchar) THEN pkd_qtyinv ELSE (0)::numeric END AS > ksalida, > pkd_pcode AS kprocode, pkd_price AS kvalor, pdc_tipdoc AS ktipdoc > FROM (pkardex JOIN pmdoc ON ((pmdoc.pdc_pk = pkardex.doctofk))); > > > Shared memory is: > /root: cat /proc/sys/kernel/shmmax > 1073741824 > > and postgresql.conf have this settings: > tcpip_socket = true > sort_mem = 8190 # min 64, size in KB > vacuum_mem = 262144 # min 1024, size in KB > checkpoint_segments = 10 > max_connections = 256 > shared_buffers = 32000 > effective_cache_size = 160000 # typically 8KB each > random_page_cost = 2 # units are one sequ > > The explain analyze is: > dbmund=# explain analyze select * from vkardex where kprocode='1017'; > Nested Loop (cost=0.00..32155.66 rows=5831 width=114) (actual > time=18.223..47983.157 rows=4553 loops=1) > -> Index Scan using pkd_pcode_idx on pkardex (cost=0.00..11292.52 > rows=5831 width=72) (actual time=18.152..39520.406 rows=5049 loops=1) > Index Cond: ((pkd_pcode)::text = '1017'::text) > -> Index Scan using pdc_pk_idx on pmdoc (cost=0.00..3.55 rows=1 > width=50) (actual time=1.659..1.661 rows=1 loops=5049) > Index Cond: (pmdoc.pdc_pk = "outer".doctofk) > Total runtime: 47988.067 ms > (6 rows) OK, you have to ask yourself a question here. Do I have enough memory to let both postgresql and the kernel to cache this data, or enough memory for only one. Then, you pick one and try it out. But there's some issues here. PostgreSQL's shared buffer are not, and should not generally be thought of as "cache". A cache's job it to hold the whole working set, or as much as possible, ready for access. A buffer's job is to hold all the data we're tossing around right this second. Once we're done with the data, the buffers can and do just drop whatever was in them. PostgreSQL does not have caching, in the classical sense. that may or may not change. The kernel, on the other hand, has both cache and buffer. Ever notice that a Linux top shows the cache usually being much bigger than the buffers? My 512 Meg home box right now has 252968k for cache, and 43276k for buffers. Now, you're tossing around enough data to actually maybe have a use for a huge set of buffers, but this means you'll need to starve your cache to get enough buffers. Which means that if one process does this kind of join, drops connection, and two seconds later, another process connects and does nearly the same thing, it's likely to have to read it all from the hard drives again, as it's not in the postgresql buffer, and not in the kernel cache. Starting a seperate connection, doing a simple select * from table1; sekect * from table 2, dropping the result set returned, and staying connected seems to be enough to get 7.4 to hold onto the data. PostgreSQL's current buffer management algo is dirt simple. The ones in the kernel's cache are quite good. So you can quickly reach a point where PostgreSQL is chasing it's tail where the kernel would have done OK. Your numbers show that you are tossing 659M and 314M against each other, but I don't know if you're harvesting the whole set at once, or just a couple row of each. Indexing help, or is this always gonna be a big seq scan of 90% of both tables? If you are getting the whole thing all the time, and want postgresql to buffer the whole thing (I recommend against it, although a very few circumstances seem to support it) you need to have 973M of buffer. That would be 124544 or we'll just call it 130000. This high of a number means you will be getting more than 50% of the RAM for postgreSQL. At that point, it seems you might as well go for broke and grab most of it, ~200000 or so. If you're not always mushing the two things against each other, and you've got other datasets to interact with, index it. Oh, in your reply you might to include an explain analyze of the query, and maybe an output of top while the query is running.
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