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From: Eduardo Morras <emorras@s21sec.com>
To: Robert Haas <robertmhaas@gmail.com>
Cc: pgsql-performance@postgresql.org
Subject: Re: Compression in PG
Date: Mon, 02 Nov 2009 10:51:06 +0100
Message-ID: <20091102095349.45474558AA6@s21sec.com> (raw)
In-Reply-To: <603c8f070911012024q26bd2b2aw9da2cef4d8face0f@mail.gmail.co m>
References: <234efe30911010651k6cf3d398t9d61e560d57b52b7@mail.gmail.com>
<162867790911010656m37b315dbp41761a014745b9e4@mail.gmail.com>
<dcc563d10911010757o3cededc0x9859ef2c47002919@mail.gmail.com>
<234efe30911010853k1908b6a6kdb1ebcdbc4c22691@mail.gmail.com>
<603c8f070911012024q26bd2b2aw9da2cef4d8face0f@mail.gmail.com>
At 05:24 02/11/2009, you wrote:
>The only reason I can think of for wanting to compress very small
>datums is if you have a gajillion of them, they're highly
>compressible, and you have extra CPU time coming out of your ears. In
>that case - yeah, you might want to think about pre-compressing them
>outside of Pg. If you're doing this for some other reason you could
>probably get some better advice if you explain what it is...
>
>...Robert
There is another reason. If you compress (lossless) all the small text datums with the same algorithm, you get unique and smaller representations of the text that can be used as primary unique keys. You can see it like a variable length hashing algorithm.
Depending the compression method (f.ex. static huffman) you can compare 2 texts using only the compressed versions or sort them faster. This cannot be done with the actual LZ algorithm.
--------------------------------
Eduardo Morrás González
Dept. I+D+i e-Crime Vigilancia Digital
S21sec Labs
Tlf: +34 902 222 521
Móvil: +34 555 555 555
www.s21sec.com, blog.s21sec.com
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