This is a real gotcha with Lucene in it's out of the box
configuration. In the several applications I've built to index
documents I've always hit this and had to set the maxFieldLength to
its maximum possible value. Is there still an argument to be made to
keep the default at 10K or would it be reasonable to bump this up
even if there are, the few, cases where setting it lower is
desirable? We made the compound file index be the default to
prevent file handle limitations at the expense of some (generally
irrelevant) performance, so maybe we could also make this more common
setting the default also?
Erik
On Feb 8, 2006, at 2:17 PM, Dmitry Goldenberg wrote:
Duh! Bingo! Mistery solved. I should have thought of this :)
The discrepancies come in with larger documents, definitely > 10K
terms which is Lucene's default maxFieldLength.
Thanks for your help, Chris
- Dmitry
________________________________
From: Chris Hostetter [mailto:[EMAIL PROTECTED]
Sent: Wed 2/8/2006 10:04 AM
To: java-user@lucene.apache.org
Subject: RE: How to get mapping of query terms to number of their
occurrences in a doc?
: That's what I did, for debugging. The query is "biology", and
here's
: what the API tells me for term frequencies:
: biolog 15
: biologi 31
: biologist 4
:
: I actually see 13 occurrences of "biologist" and "biologists", 64
: occurrences of "biology", 27 occurrences of "biological".
:
: I see "inform 22" but the actual count of the word "information"
in the
: document is 33. But "ioniz 7" is correct.
I think I missunderstood what you ment when you said the counts don't
match up. Are you comparing the number you get from that code with
the
number of times you personally see the word in the source document
before
it has been analyzed?
If so, then there could be a couple of things going on ... i would
start
by using a tool like Luke to see the actual lists of Terms for each
doc --
there may be something else your analyzer is doing that you don't
realize.
It's also possible that you are hitting the maxFieldLength in the
IndexWriter ... when that happens IndexWriter throws away any
remaining
tokens, so if your documenst are really large.
Lastly, I would add a *lot* more debugging to your code. Print out
the
contents of "terms", when you loop over "tfvs" print out the field
and the
full list of strTerms, in the inner most loop when you incriment the
count, print out the field/text/and count.
that's the best advise i have for spotting what's wrong.
: ________________________________
:
: From: Chris Hostetter [mailto:[EMAIL PROTECTED]
: Sent: Tue 2/7/2006 4:10 PM
: To: java-user@lucene.apache.org
: Subject: Re: How to get mapping of query terms to number of their
occurrences in a doc?
:
:
:
:
: A cursory reading of your code looks ok ... stemming shouldn't be
an issue
: as long as your measure of success is comparing docs that match your
: orriginal query with the counts you get out.
:
: What i mean by that is that any stemming should have already been
taken
: care of when your query object was constructed (either by you
manually, or
: by QueryParser). the direct equals comparisons you are dong
should be
: fine.
:
: have you tried adding logging of the raw term field/text and the
freq
: counts you get back to see if that helps you spot the problem?
:
:
: : Date: Mon, 6 Feb 2006 14:34:05 -0800
: : From: Dmitry Goldenberg <[EMAIL PROTECTED]>
: : Reply-To: java-user@lucene.apache.org
: : To: java-user@lucene.apache.org
: : Subject: How to get mapping of query terms to number of their
occurrences
: : in a doc?
: :
: : Given a query, I want to be able to, for each query term, get
the number of occurrences of the term. I have tried what I'm
including below and it does not seem to provide reliable results.
Seems to work fine with exact matching but as soon as stemming
kicks in, all bets are off as to value of the number of occurrences
returned.
: :
: : Any ideas, anyone? Can this be written in a simpler and/or
more efficient way?
: : Thanks -
: :
: : int totalOccurrences = 0;
: :
: : reader = IndexReader.open(getDirectory(indexDirPath));
: : HashSet terms = new HashSet();
: : query.extractTerms(terms);
: :
: : TermFreqVector[] tfvs = reader.getTermFreqVectors(docId);
: : if (tfvs != null) {
: :
: : // For each term frequency vector (i.e. for each field)
: : for (int i = 0; i < tfvs.length; i++) {
: : String field = tfvs[i].getField();
: : String[] strTerms = tfvs[i].getTerms();
: : int[] tfs = tfvs[i].getTermFrequencies();
: :
: : if (strTerms != null) {
: :
: : // For each term in the query
: : for (Iterator iter = terms.iterator(); iter.hasNext
();) {
: :
: : Term term = (Term) iter.next();
: : // For each term in the vector
: : for (int j = 0; j < strTerms.length; j++) {
: :
: : // If found the query term among the vector terms
: : if (field.equals(term.field()) && strTerms
[j].equals(term.text())) {
: :
: : // Add the term frequency to the total
: : totalOccurrences += tfs[j];
: :
: : }
: : }
: : }
: : }
: : }
: : }
: :
:
:
:
: -Hoss
:
:
:
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-Hoss
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