Are the tokens unique within a document? If so, why not store a document for every doc/token pair with fields:

id (doc#/token#)
doc-id (doc#)
token
weight1
weight2
frequency

Then search for token, sort by weight1, weight2 or frequency.

If the token matches are unique within a document you will only get each document listed once. If they aren't unique, it's not clear what you want to sort by anyway....

-Mike

On 05/05/2011 04:12 PM, Chris Schilling wrote:
Hi,

I am trying to figure out how to solve this problem:

I have about 500,000 files that I would like to index, but the files are 
structured.  So, each file has the following layout:

doc1
token1, weight11, frequency1, weight21
token2, weight12, frequency2, weight22
.
.
.

etc for 500,000 docs.

Basically, I would like to index the tokens for each doc.  When I search for a 
token, I would like to be able to return the top docs sorted by weight1, 
frequency, or weight2.

So, in my naive setup, I loop through the files in the directory, then I loop 
through the lines of the file.   In side of the loop through each file, I call 
this function:

        public Document processKeywords(Document doc, String keyword, Float 
weight1, Float weight2, Integer frequency) throws Exception {
                        Document doc = new Document();
                        doc.add(new Field("keywords", keyword, Field.Store.NO, 
Field.Index.ANALYZED));                        
                        doc.add(new NumericField(keyword+"weight1", 
Field.Store.YES, true).setFloatValue(weight1));                   
                        doc.add(new NumericField(keyword+"weight2", 
Field.Store.YES, true).setFloatValue(weight2));                   
                        doc.add(new NumericField(keyword+"frequency", 
Field.Store.YES, true).setFloatValue(frequency));                       
                        return doc;
        }

So, for each token, I create 3 new fields each time. Notice how I am trying to index the 
keyword in the "keywords" field.  For the weights and frequency, I create a new 
field with a name based on the keyword.  On average, I have 100 tokens per document, so 
each document will have about 300 distinct fields.

When running my program, the lucene portion eats up tons of memory and when it 
gets to the max alloted by the JVM (I have tried allowing up to 4 Gb), the 
program slows to a crawl.  I assume it is spending all of its time in garbage 
collection due to all these fields.

My code above seems like a very hacky way of accomplishing what I want (sorting 
documents based on keyword search using different numeric fields associated 
with that keyword).

FYI, here is the main search code, where q is the token I am searching for and sortby is 
the field I want to use to sort.  I setup a QP to search for the keyword in the 
"keywords" field.  Then, I can extract the stats that I indexed for the given 
query keyword.

        private static final QueryParser parser = new QueryParser(Version.LUCENE_30, 
"keywords", new StandardAnalyzer(Version.LUCENE_30));

        public void search(String q, String sortby) throws IOException, 
ParseException {
                Query query = parser.parse(q);
                long start = System.currentTimeMillis();
                TopDocs hits = this.is.search(query, null, 10, new Sort(new 
SortField(q+"sortby", SortField.FLOAT, true)));
                long end = System.currentTimeMillis();
                System.out.println("Found " + hits.totalHits +
                                " document(s) (in " + (end - start) +
                                " milliseconds) that matched query '" +
                                q + "':");
                for(ScoreDoc scoreDoc : hits.scoreDocs) {
                        Document doc = this.is.doc(scoreDoc.doc);
                        String hash = doc.get("hash");
                        System.out.println(hash + " " + doc.get(q+"sortby") + " 
" + hash);
                }
        }

I am pretty new to Lucene, so I hope this makes sense.  I tried to pare my 
problem down as much as possible.  Like I said, the main problem I am running 
into is that after processing about 30000 documents, the indexing slows to a 
crawl and seems to spend all of its time in the garbage collector.  I am 
looking for a more efficient/effective way of solving this problem.  Code 
tidbits would help, but are not necessary :)

Thanks for your help,
Chris S.

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