On Sat, Aug 28, 2010 at 8:34 AM, Alexander Korotkov
<aekorotkov@gmail.com> wrote:
> Here is the patch which adds levenshtein_less_equal function. I'm going to
> add it to current commitfest.
There are some minor stylistic issues with this patch - e.g. lines
ending in whitespace, cuddled elses - but those don't look too
terribly difficult to fix. I'm more concerned about the fact that I
don't really understand the algorithm you're using. Actually, I
didn't really understand the original algorithm either until I went
and read up on it, and I just adjusted the comments to make it a bit
more clear what it's doing. That caused some minor merge conflicts
with your patch, so I'm attaching a rebased version that applies
cleanly over my changes.
Can you explain a bit more what algorithm this is using? It seems
like in the max_d >= 0 case the cells of the notional array have a
meaning which is completely different from what they mean in
otherwise, and it's not clear to me from reading the comments what
that meaning is. I took a look on that font of all human knowledge,
Wikipedia:
http://en.wikipedia.org/wiki/Levenshtein_distance
Their suggestion for handling this case is:
"If we are only interested in the distance if it is smaller than a
threshold k, then it suffices to compute a diagonal stripe of width
2k+1 in the matrix. In this way, the algorithm can be run in O(kl)
time, where l is the length of the shortest string."
It seems like that may be similar to what you're doing here but I
don't think that's exactly it. I don't think that exact thing would
work in our case anyhow because we've got configurable costs.
--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise Postgres Company
