In my tests I suddenly bumped into a Too Many Clauses exception when trying to get the hits from a boolean query that consisted of a termquery and a wildcard query.
I searched around the net and on the found resources they suggest to increase the BooleanQuery.SetMaxClauseCount().
This sounds fishy to me.. To what should I up it? How can I rely that this new magic number will be sufficient for my query? How far can I increment this number before all hell breaks loose?
In general I feel this is not a solution. There must be a deeper problem..
The query was +{+companyName:mercedes +paintCode:a*} and the index has ~2.5M documents.
the paintCode:a* part of the query is a prefix query for any paintCode beginning with an "a". Is that what you're aiming for?
Lucene expands prefix queries into a boolean query containing all the possible terms that match the prefix. In your case, apparently there are more than 1024 possible paintCodes that begin with an "a".
If it sounds to you like prefix queries are useless, you're not far from the truth.
I would suggest you change your indexing scheme to avoid using a Prefix Query. I'm not sure what you're trying to accomplish with your example, but if you want to search for paint codes by first letter, make a paintCodeFirstLetter field and search by that field.
ADDED
If you're desperate, and are willing to accept partial results, you can build your own Lucene version from source. You need to make changes to the files PrefixQuery.java and MultiTermQuery.java, both under org/apache/lucene/search. In the rewrite method of both classes, change the line
query.add(tq, BooleanClause.Occur.SHOULD); // add to query
to
try {
query.add(tq, BooleanClause.Occur.SHOULD); // add to query
} catch (TooManyClauses e) {
break;
}
I did this for my own project and it works.
If you really don't like the idea of changing Lucene, you could write your own PrefixQuery variant and your own QueryParser, but I don't think it's much better.
It seems like you are using this on a field that is sort of a Keyword type (meaning there will not be multiple tokens in your data source field).
There is a suggestion here that seems pretty elegant to me: http://grokbase.com/t/lucene.apache.org/java-user/2007/11/substring-indexing-to-avoid-toomanyclauses-exception/12f7s7kzp2emktbn66tdmfpcxfya
The basic idea is to break down your term into multiple fields with increasing length until you are pretty sure you will not hit the clause limit.
Example:
Imagine a paintCode like this:
"a4c2d3"
When indexing this value, you create the following field values in your document:
[paintCode]: "a4c2d3"
[paintCode1n]: "a"
[paintCode2n]: "a4"
[paintCode3n]: "a4c"
By the time you query, the number of characters in your term decide which field to search on. This means that you will perform a prefix query only for terms with more of 3 characters, which greatly decreases the internal result count, preventing the infamous TooManyBooleanClausesException. Apparently this also speeds up the searching process.
You can easily automate a process that breaks down the terms automatically and fills the documents with values according to a name scheme during indexing.
Some issues may arise if you have multiple tokens for each field. You can find more details in the article
Related
I'm searching against a table of news articles. The 2 relevant columns are ArticleTitle and ArticleText. When I want to search an article for a particular term, i started out with
column LIKE '%term%'.
However that gave me a lot of articles with the term inside anchor links, for example <a href="example.com/*term*> which would potentially return an irrelevant article.
So then I switched to
column LIKE '% term %'.
The problem with this query is it didn't find articles who's title or text began/ended with the term. Also it didn't match against things like term- or term's, which I do want.
It seems like the query i want should be able to do something like this
'%[^a-z]term[^a-z]%
This should exclude terms within anchor links, but everything else. I think this query still excludes strings that begin/end with the term. Is there a better solution? Does SQL-Server's FULL TEXT INDEXING solve this problem?
Additionally, would it be a good idea to store ArticleTitle and ArticleText as HTML-free columns? Then i could use '%term%' without getting anchor links. These would be 2 extra columns though, because eventually i will need the original HTML for formatting purposes.
Thanks.
SQL Server's LIKE allows you to define Regex-like patterns like you described.
A better option is to use fulltext search:
WHERE CONTAINS(ArticleTitle, 'term')
exploits the index properly (the LIKE '%term%' query is slow), and provides other benefit in the search algorithm.
Additionally, you might benefit from storing a plaintext version of the article alongside the HTML version, and run your search queries on it.
SQL is not designed to interpret HTML strings. As such, you'd only be able to postpone the problem till a more difficult issue arrives (for example, a comment node that contains your search terms as part of a plain sentence).
You can still utilize FULL TEXT as a prefilter and then run an HTML analysis on the application layer to further filter your result set.
I need to make a FuzzyQuery using an index that contains around 8 million lines. That kind of query is pretty slow, needing about 20 seconds for every match. The fact is that I can narrow down the results using another field to about 5000 hits before doing the fuzzy search. For this to work, I should be able to make a search by the "narrower" field first, and then use the fuzzy search within those results.
According to the lucene FAQ, the only thing I have to do is a BooleanQuery, where the "narrower" should be required (BooleanClause.Occur.MUST in lucene 3).
Now I have tried two different approaches:
a) Using the Query Parser, with an input like:
narrower:+narrowing_text fuzzy:fuzzy_text~0.9
b) Constructing a BooleanQuery with a TermQuery and a FuzzyQuery
Neither did work, I'm getting about the same times than the ones when the narrower is not used.
Also, just to check that if the narrower was working the times should be much better, I reindexed only the 5000 items that match the narrower, and the search went fast as hell.
In case anyone wonders, I'm using pylucene 3.0.2.
Doppleganger, you can probably use a Filter, specifically a QueryWrapperFilter.
Follow the example from Lucene in Action. You may have to make some modifications for use in python, but otherwise it should be simple:
Create the query that narrows this down to 5000 hits.
Use it to build a QueryWrapperFilter.
Use the filter in a search involving the fuzzy query.
Using RavenDB to do a query on Lucene Index.
This query parses okay:
X:[[a]] AND Y:[[b]] AND Z:[[c]]
However this query gives me a parse exception:
X:[[a]] AND Y:[[b]] AND Z:[[c]] AND P:[[d]]
"Lucene.Net.QueryParsers.ParseException: Cannot parse '( AND )': Encountered \" \"AND"
I tried this on complexed index and simple reproduce cases and same result it seems once you go past three ands it blows up. Im using [[]] and not analyzed because i want exact matches (also sometimes values contain whitespace etc..) and from RavenDB I have veyr little control over the indexing.
Im wondering how I can rewrite the query to avoid the parse exception?
This is now fixed in the latest RavenDB builds. See this thread for more info.
This looks rather like a bug in Lucene's QueryParser, perhaps try reporting this in the user mailing list.
As a bypass, you could create a BooleanQuery manually and add the terms you want yourself. Since they are not analyzed, and the query doesn't look too complicated, you may be better off without the query-parser.
When my users enter a term like "word" I would like it be treated as a wildcard query "word*" so all terms beginning "word" are found. Is there a way to tell the QueryParser to automatically create wildcard queries or do I have to parse the query myself? This shouldn't be a problem for simple queries but it may become tricky for more complex queries.
Unless I am missing something - a wildcard query for every query is usually inadvisable - it is very expensive and could cause a lot of problems. If you are trying find results including variants of a stem (e.g. win -> winner, winning, etc.) You should consider a n-gram approach.
I have recently just started working with Lucene (specifically, Lucene.Net) and have successfully created several indicies and have no problem with any of them. Previously having worked with Endeca, I find that Lucene is lightweight, powerful, and has a much lower learning curve (due mostly to a concise API).
However, I have one specific index/query situation which I am having problems wrapping my head around. What I have is a person directory. People can be searched for in this application, with the goal of returning both exact and approximate matches. Right now, in the index I concatenate the "FirstName" and "LastName" into a single field called "FullName", adding a space between the two. So FirstName:Jon with LastName:Smith yield FullName:Jon Smith. I do anticipate the possibility of middle names and possibly suffix, but that is not important at the moment.
I would like to do the equivalent of a fuzzy search on the name, so someone searching for "John Smith" would still get back "Jon Smith". I had thought about a multisearch, however, this becomes more involved if his name was actually "Jon Del Carmen" or "Jon Paul Del Carmen". I have nothing in what the user types in to delineate the first name or last name pieces.
The only thought that I have is that I could replace spaces in the concatenated value with a character that would not be discarded. If I did this when I built the document for the index and also when I parsed the query, I could treat it as one larger word, right? Is there another way to do this that would work for both simple names ("Jon Smith") and also more complex names ("Jon Paul Del Carmen")?
Any advice would truly be appreciated. Thanks in advance!
Edit: Additional detail follows.
In Luke, I put in the following query:
FullName:jonn smith~
It is being parsed as:
FullName:jonn CreatedOn:smith~0.5
With an Explanation of:
BooleanQuery:boost=1.0000
clauses=2, maxClauses=1024
Clause 0: SHOULD
TermQuery:boost=1.0000
Term: field='FullName' text='jonn'
Cluase 1: SHOULD
FuzzyQuery: boost=1.0000
prefixLen=0, minSimilarity=0.5000
org.apache.lucene.search.FuzzyTermEnum: diff=-1.0000
FilteredTermEnum: Exception null
"CreatedOn" is another Field in the index. I tried putting quotes around the term "jonn smith", but it then treats it like a phrasequery, instead. I am sure that the problem is that I am just not doing something right, but being so green at all of this, I am not sure what that something truly is.
My problem was with how I was building the index. What I ended up doing was making sure that it was not tokenizing the FullName, and the query started returning the correct results. The Explain results from above were due to an ID10T error on my part and is now returning correctly.