[ 
https://issues.apache.org/jira/browse/LUCENE-1606?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12786528#action_12786528
 ] 

Robert Muir commented on LUCENE-1606:
-------------------------------------

bq. I'm not sure at the moment - but its wikipedia dumps, so I'd guess its 
rather high actually.

I looked at the wikipedia dump in benchmark (when indexed with 
standardanalyzer), body only has 65k terms... I think thats pretty small :)
I do not think automaton will help much with such a small number of terms, its 
definitely a worst case benchmark you are performing.
I think very little time is probably spent here in term enumeration so 
scalability does not matter for that corpus.

More interesting to see the benefits would be something like indexing geonames 
data (lots of terms), or even that (much smaller) persian corpus i mentioned 
with nearly 500k terms... 


> 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: Search
>            Reporter: Robert Muir
>            Assignee: Robert Muir
>            Priority: Minor
>             Fix For: 3.1
>
>         Attachments: automaton.patch, automatonMultiQuery.patch, 
> automatonmultiqueryfuzzy.patch, automatonMultiQuerySmart.patch, 
> automatonWithWildCard.patch, automatonWithWildCard2.patch, 
> BenchWildcard.java, LUCENE-1606-flex.patch, LUCENE-1606-flex.patch, 
> LUCENE-1606-flex.patch, LUCENE-1606-flex.patch, LUCENE-1606-flex.patch, 
> LUCENE-1606-flex.patch, LUCENE-1606.patch, LUCENE-1606.patch, 
> LUCENE-1606.patch, LUCENE-1606.patch, LUCENE-1606.patch, LUCENE-1606.patch, 
> LUCENE-1606.patch, LUCENE-1606.patch, LUCENE-1606.patch, LUCENE-1606.patch, 
> LUCENE-1606.patch, LUCENE-1606.patch, LUCENE-1606.patch, 
> LUCENE-1606_nodep.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.

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.


---------------------------------------------------------------------
To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org
For additional commands, e-mail: java-dev-h...@lucene.apache.org

Reply via email to