| From: | Peter Eisentraut <peter_e(at)gmx(dot)net> |
|---|---|
| To: | pgsql-hackers(at)postgresql(dot)org, Martijn van Oosterhout <kleptog(at)svana(dot)org> |
| Cc: | Dimitri Fontaine <dim(at)hi-media(dot)com> |
| Subject: | Re: Query Hints? No thanks. Data hints? |
| Date: | 2008-05-06 12:44:52 |
| Message-ID: | 200805061444.53225.peter_e@gmx.net |
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| Lists: | pgsql-hackers |
Am Dienstag, 6. Mai 2008 schrieb Martijn van Oosterhout:
> Cross-table correlations are easy for the second part, because it's
> fairly simple to see where it could be used. However, no-one has come
> up with an algorithm to produce a useful number to use. For others it's
> harder.
For an algorithm, principal components analysis would be my guess. It is
designed to answer the question "this column value is tied to this other
column value in this way" [quote Simon], at least for the sort of data that a
B-tree would cover. For nonlinear data, it is of course harder.
> In general postgres could use many bits of information not currently
> available. For example: A=B implies lower(A)=lower(B), hence an index
> on lower(A) could be used to optimise comparisons against A. Certain
> operations preserve order, which may also be useful.
Locale horrors looming ... ;-)
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