On 2010-12-13 03:28, Robert Haas wrote:
> Well, I'm not real familiar with contingency tables, but it seems like
> you could end up needing to store a huge amount of data to get any
> benefit out of it, in some cases. For example, in the United States,
> there are over 40,000 postal codes, and some even larger number of
> city names, and doesn't the number of entries go as O(m*n)? Now maybe
> this is useful enough anyway that we should Just Do It, but it'd be a
> lot cooler if we could find a way to give the planner a meaningful
> clue out of some more compact representation.
A sparse matrix that holds only 'implicative' (P(A|B) <> P(A*B)?)
combinations? Also, some information might be deduced from others. For
Heikki's city/region example, for each city it would be known that it is
100% in one region. In that case it suffices to store only that
information, since 0% in all other regions ca be deduced. I wouldn't be
surprized if storing implicatures like this would reduce the size to O(n).
regards,
Yeb Havinga
