Re: add_path optimization - Mailing list pgsql-hackers

From Robert Haas
Subject Re: add_path optimization
Date
Msg-id 603c8f070902021945i183c100ch98acfbb5fe8bbe0c@mail.gmail.com
Whole thread Raw
In response to Re: add_path optimization  (Stephen Frost <sfrost@snowman.net>)
Responses Re: add_path optimization  (Stephen Frost <sfrost@snowman.net>)
Re: add_path optimization  (Tom Lane <tgl@sss.pgh.pa.us>)
List pgsql-hackers
> A good data set, plus complex queries against it, might be the data from
> the US Census, specifically the TIGER data and the TIGER geocoder.  I've
> been following this thread with the intention of putting together a
> large-data test set, but I just havn't found the time to yet.  Right now
> there's alot of dependencies on PostGIS (which aren't really required to
> just do the queries to pull out the street segment) which I figure
> people would want ripped out.  It'd also be nice to include the other
> Census data besides just the road data.
>
> If people really are interested, I'll see what I can put together.  It's
> *alot* of data (around 23G total in PG), though perhaps just doing 1
> state would be enough for a good test, I keep the states split up
> anyway using CHECK constraints.  Don't think that would change this
> case, though there might be cases where it does affect things..

I'm interested, but I need maybe a 1GB data set, or smaller.  The
thing that we are benchmarking is the planner, and planning times are
related to the complexity of the database and the accompanying
queries, not the raw volume of data.  (It's not size that matters,
it's how you use it?)  In fact, in a large database, one could argue
that there is less reason to care about the planner, because the
execution time will dominate anyway.  I'm interested in complex
queries in web/OLTP type applications, where you need the query to be
planned and executed in 400 ms at the outside (and preferably less
than half of that).

...Robert


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