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https://issues.apache.org/jira/browse/LUCENE-1606?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12701279#action_12701279
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Eks Dev commented on LUCENE-1606:
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Robert,
in order for Lev. Automata to work, you need to have the complete dictionary as
DFA. Once you have dictionary as DFA (or any sort of trie), computing simple
regex-s or simple fixed or weighted Levenshtein distance becomes a snap.
Levenshtein-Automata is particularity fast at it, much simpler and only
slightly slower method (one pager code)
"K.Oflazer"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.3862
As said, you cannot really walk current term dictionary as automata/trie (or
you have an idea on how to do that?). I guess there is enough application where
stoing complete Term dictionary into RAM-DFA is not a problem. Even making some
smart (heavily cached) persistent trie/DFA should not be all that complex.
Or you intended just to iterate all terms, and compute distance faster "break
LD Matrix computation as soon as you see you hit the boundary"? But this
requires iteration over all terms?
I have done something similar, in memory, but unfortunately someone else paid
me for this and is not willing to share...
> Automaton Query/Filter (scalable regex)
> ---------------------------------------
>
> Key: LUCENE-1606
> URL: https://issues.apache.org/jira/browse/LUCENE-1606
> Project: Lucene - Java
> Issue Type: New Feature
> Components: contrib/*
> Reporter: Robert Muir
> Priority: Minor
> Fix For: 2.9
>
> Attachments: automaton.patch, automatonMultiQuery.patch,
> automatonmultiqueryfuzzy.patch, automatonMultiQuerySmart.patch,
> automatonWithWildCard.patch, automatonWithWildCard2.patch
>
>
> Attached is a patch for an AutomatonQuery/Filter (name can change if its not
> suitable).
> Whereas the out-of-box contrib RegexQuery is nice, I have some very large
> indexes (100M+ unique tokens) where queries are quite slow, 2 minutes, etc.
> Additionally all of the existing RegexQuery implementations in Lucene are
> really slow if there is no constant prefix. This implementation does not
> depend upon constant prefix, and runs the same query in 640ms.
> Some use cases I envision:
> 1. lexicography/etc on large text corpora
> 2. looking for things such as urls where the prefix is not constant (http://
> or ftp://)
> The Filter uses the BRICS package (http://www.brics.dk/automaton/) to convert
> regular expressions into a DFA. Then, the filter "enumerates" terms in a
> special way, by using the underlying state machine. Here is my short
> description from the comments:
> The algorithm here is pretty basic. Enumerate terms but instead of a
> binary accept/reject do:
>
> 1. Look at the portion that is OK (did not enter a reject state in the
> DFA)
> 2. Generate the next possible String and seek to that.
> the Query simply wraps the filter with ConstantScoreQuery.
> I did not include the automaton.jar inside the patch but it can be downloaded
> from http://www.brics.dk/automaton/ and is BSD-licensed.
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