Re: knngist - 0.8

From: Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>
To: Dimitri Fontaine <dimitri(at)2ndQuadrant(dot)fr>
Cc: Greg Stark <gsstark(at)mit(dot)edu>, Oleg Bartunov <oleg(at)sai(dot)msu(dot)su>, Robert Haas <robertmhaas(at)gmail(dot)com>, Teodor Sigaev <teodor(at)sigaev(dot)ru>, Pgsql Hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: knngist - 0.8
Date: 2010-12-04 21:58:18
Message-ID: 12543.1291499898@sss.pgh.pa.us
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Dimitri Fontaine <dimitri(at)2ndQuadrant(dot)fr> writes:
> Greg Stark <gsstark(at)mit(dot)edu> writes:
>> I kind of assumed the natural client for KNN-gist was the tsearch full
>> text search indexes handling sorting by relevance. For example if I
>> search for "Postgres DBA" I should find documents where those words
>> appear adjacent first and documents where the two words appear far
>> apart in the document sorted further down. Is that not on the list of
>> operators supported or planned to be supported?

> From the presentation I've seen, the typical use case is more searching
> "PostgreSQL DBA" at 100 km around a known location. Or more typical yet,
> Pizza restaurants around a known place:)

Right offhand I don't see how KNNGIST could usefully be applied to the
problem Greg is thinking about. A KNNGIST search is only going to be
fast if the target items can be found in a reasonably small part of the
index. Nearest-neighbor in a geometrically organized index qualifies,
but I don't see how Greg's problem matches the structure of a tsearch
index.

regards, tom lane

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