I'll side-step the explanations part of your mail since I don't know how to answer.. But a few observations, see below.
On 9/19/06, Kroehling, Thomas <[EMAIL PROTECTED]> wrote:
Hi, I am trying to write a WildcardFilter in order to prevent TooManyBooleanClauses and high memory usage. I wrap a Filter in a ConstantScoreQuery. I enumerate over the WildcardTerms for a query. This way I can set a maximum number of terms which i will evaluate. If too many terms match, I throw an exception. I also have a maximum number of documents which are allowed to match using BitsSets cardinality. I am not sure, if that is necessary, but I thought, if only a few terms, but a few million documents might match, that could also considerably slow down a search.
This seems like a prime candidate for generating "unexpected" results, so I'd start by taking it out and seeing if your search and wildcard enumerations agree better. I thought, I could get the TermDocs for each WildcardTerm and use:
int count = termDocs.read(docs, freqs); In order to have an optimized way to read not more than a maximum number of documents which match this term.
You shouldn't be reading documents at all, just enumerating the terms that are indexed and setting bits. It's expensive to read the docs, and the javadocs warn against this (of course I could just not understand what you're doing...). I would then step through docs and
set the bits for these documents. Sometimes this works, but sometimes this returns a different number search results. When I search for "content:test" in my index, I find 66 documents, but when I search for "t*st" with my WildcardFilter, I only find 23. There is only one term "test" matching this query and searching for this term in Luke also returns 66 documents. I found out that the SegmentTermDocs sets a variable df to "23", which leads to stop searching any further. Unfortunately I do not quite understand, where this variable really comes from and what it is for. I probably could just step through the TermDocs for each WildcardTerm.
Start here. Unless and until you have some idea that the simple way of doing things isn't too slow for your problem, don't try anything fancy. Filters were *built* for this type of thing, and I've been pleasantly surprised at how fast they can be built. Admittedly, mine are on about 1M documents..... Here's some sample code that works for me, field and value are fields set in the constructor...... public BitSet bits(IndexReader reader) throws IOException { bits = new BitSet(reader.maxDoc()); TermDocs termDocs = reader.termDocs(); WildcardTermEnum wildEnum = new WildcardTermEnum(reader, new Term(field, value)); for (Term term = null; (term = wildEnum.term()) != null; wildEnum.next()) { termDocs.seek(new Term( field, term.text())); while (termDocs.next()) { bits.set(termDocs.doc()); } } return bits; } Note a few things... CachingWrapperFilter will cache these filters for future use. If you have an idea of the kinds of wildcards you will need ahead of time, you could always generate filters and store them away if it turns out that performance is a problem (although I've rarely seen this be practical since the silly users type things unpredictably<G>). I'd really recommend that you try the simple thing first and try a couple of timings on really ugly filter creation, something like a* before trying anything more complex.... Best Erick Is that should a correct (and not dramatically slow) way to find all
documents? But I would like to understand, the difference in search results and what the method TermDocs.read(docs, freqs) method does and if my kind of filter does really make sense. I periodically rebuild my index and I wonder why my WildcardFilter sometimes returns the correct search results and sometimes not. What is the difference between steping through the term docs with termDocs.next() and using the read-method. Can anybodey explain that? Thanks in advance, Thomas --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]