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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