Re: B-Heaps

From: Yeb Havinga <yebhavinga(at)gmail(dot)com>
To: Greg Smith <greg(at)2ndquadrant(dot)com>
Cc: Eliot Gable <egable+pgsql-performance(at)gmail(dot)com>, pgsql-performance(at)postgresql(dot)org
Subject: Re: B-Heaps
Date: 2010-06-15 19:33:06
Message-ID: 4C17D572.2030305@gmail.com
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Greg Smith wrote:
> Eliot Gable wrote:
>> Just curious if this would apply to PostgreSQL:
>> http://queue.acm.org/detail.cfm?id=1814327
>
> It's hard to take this seriously at all when it's so ignorant of
> actual research in this area. Take a look at
> http://www.cc.gatech.edu/~bader/COURSES/UNM/ece637-Fall2003/papers/BFJ01.pdf
> for a second
Interesting paper, thanks for the reference!
> PostgreSQL is modeling a much more complicated situation where there
> are many levels of caches, from CPU to disk. When executing a query,
> the database tries to manage that by estimating the relative costs for
> CPU operations, row operations, sequential disk reads, and random disk
> reads. Those fundamental operations are then added up to build more
> complicated machinery like sorting. To minimize query execution cost,
> various query plans are considered, the cost computed for each one,
> and the cheapest one gets executed. This has to take into account a
> wide variety of subtle tradeoffs related to whether memory should be
> used for things that would otherwise happen on disk. There are three
> primary ways to search for a row, three main ways to do a join, two
> for how to sort, and they all need to have cost estimates made for
> them that balance CPU time, memory, and disk access.
Do you think that the cache oblivious algorithm described in the paper
could speed up index scans hitting the disk Postgres (and os/hardware)
multi level memory case? (so e.g. random page cost could go down?)

regards,
Yeb Havinga

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