Re: Requirements for a database server - Mailing list pgsql-admin
From | Robert.Farrugia@go.com.mt |
---|---|
Subject | Re: Requirements for a database server |
Date | |
Msg-id | OFD7A925C1.5A21485E-ONC1256A93.001E2DCB@go.com.mt Whole thread Raw |
In response to | Requirements for a database server (Robert.Farrugia@go.com.mt) |
List | pgsql-admin |
Hi, As regards to repetitive data, this is a bit tricky. The dataset contains some varchars with repetitive data, but due to the amount of different values, it defeats the purpose of putting them into a seperate table. Unfortunately most of the fields in the table are numbers which cannot be optimized further more. What I will do over the next few weeks, is try to redesign better the tables structures without dropping any data. Thanks for the hints. Unfortunately for us we have bought the Poweredge 2400, which suffers from RAID problems as regards to speed. Thanks Robert Ron Chmara <ron@Opus1.CO To: Robert.Farrugia@go.com.mt M> cc: pgsql-admin@postgresql.org Subject: Re: [ADMIN] Requirements for a database server 22/07/2001 09:06 On Tuesday, July 17, 2001, at 10:52 PM, Robert.Farrugia@go.com.mt wrote: > Hi, > I have been using postgres for the last year now. The database > has grown > from a mere few MBs to over 100GB data and expected to top up > 300GB by the > end of the year. Interesting. The most I've ever seen a PG data set was 87GB, but it was only 2ndNF...... I'm trying to ask a question politely, which is: "Can you improve efficiency be removing repetitive data, such as text or varchar fields?" As I read your post, I thought about a project I'm working on, where we took 180GB and dropped it to 100Mb, simply because their db design stored a lot of data that was repetitive. To put it another way, the english language only has around 20,000 words, so even normal text fields can be optimized at some point with numeric keys. :-) In their case, they were storing every text "GET" string recieved by their web server, and running LIKE searches on it (no, this is not a joke.). When their queries went from > 2 hours to <1 second, they were very confused. :-) > Lately performance of queries, inserts, updates has > continued to grow worse as the dataset has grown larger, even > though most > queries have indexes on them, while vacuuming the database has become a > nightmare. For this reason we were thinking of upgrading the system > hardware. That's one option. RAID controllers are cheap, these days... my standard db box has at *least* 128Mb of RAID cache on it, which helps... depending on table design, of course. Dell makes some nice, multi-raid, systems. If your table design exceeds the amount of RAID cache, you may want to redesign your tables, or look into a mainframe or two. > Is there anyone out there who has databases of this sort ? Can > he point me > out some basic requirements for these sort of databases > (processors, ram, > storage, etc) ? Also would it be worthwile to migrate to > another database > system which is more robust with this kind of amount of data (such as > oracle) ? We test-migrated the above-mentioned project to a testing platform with Oracle, and then realized the $45K oracle license could be better spent on a ground up redesign of the db, and saved $20K by the end of the project. Of course, your case may be different, but in many cases, once a full data set is gathered, there can be numerous optimizations found within the db design that *weren't* apparent before. Using more efficient libraries (such as compiled C instead of JDBC), or optimizing queries (avoiding the evils of table scans) can improve performance 1000%. Fields which used to be "unique enough" may have 10, 50, 100 duplicate entires in them, all text/char/varchar, and can be ruduced to higher-speed int() keys. Queries that are built on complex, multi-data fields, can be split to more rows, or tables (example: If you often query on the first letter in a name, make that an col in the table, and query that). Compound data such as "email_address" can easily be broken down even further, into username and domain tables, and a join between the tables (so all aol.com email addresses come back, lightning fast). Even basic things, like stripping off a leading alpha character from a product code, can boost performance and reduce storage and throughput issues. Of course, if you've already done all of that, you're down to raw performance. Some general notes: In most cases, SMP with postgres helps on concurrent queries, but doesn't do a lot for single queries. 180/SCSI is the only way to go. IDE just doen't work in the best-performance cases. Rip the OS down to the bare essentials. Don't even think of using a stock OS kernel, if you don't have to. If you have a front end for inserts, and another front end for queries, it may help to reduce the front-end overhead. Often, there's a bottleneck which is assumed to be the db engine, when it's really the access method. HTH, -Ronabop --2D426F70|759328624|00101101010000100110111101110000 ron@opus1.com, 520-326-6109, http://www.opus1.com/ron/ The opinions expressed in this email are not necessarily those of myself, my employers, or any of the other little voices in my head.
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