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 ... ;-) -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
