Why DuplicateFilter doesn't work together with other filters? For example, if a little remake of the test DuplicateFilterTest, then the impression that the filter is not applied to other filters and first trims results:
public void testKeepsLastFilter()
throws Throwable {
DuplicateFilter df = new DuplicateFilter(KEY_FIELD);
df.setKeepMode(DuplicateFilter.KM_USE_LAST_OCCURRENCE);
Query q = new ConstantScoreQuery(new ChainedFilter(new Filter[]{
new QueryWrapperFilter(tq),
// new QueryWrapperFilter(new TermQuery(new Term("text", "out"))), // works right, it is the last document.
new QueryWrapperFilter(new TermQuery(new Term("text", "now"))) // why it doesn't work? It is the third document, but hits count is 0.
}, ChainedFilter.AND));
// this varians doesn't hit too:
// ScoreDoc[] hits = searcher.search(new FilteredQuery(tq, df), new QueryWrapperFilter(new TermQuery(new Term("text", "now"))), 1000).scoreDocs;
// ScoreDoc[] hits = searcher.search(new FilteredQuery(tq, new QueryWrapperFilter(new TermQuery(new Term("text", "now")))), df, 1000).scoreDocs;
ScoreDoc[] hits = searcher.search(q, df, 1000).scoreDocs;
assertTrue("Filtered searching should have found some matches", hits.length > 0);
for (int i = 0; i < hits.length; i++) {
Document d = searcher.doc(hits[i].doc);
String url = d.get(KEY_FIELD);
TermDocs td = reader.termDocs(new Term(KEY_FIELD, url));
int lastDoc = 0;
while (td.next()) {
lastDoc = td.doc();
}
assertEquals("Duplicate urls should return last doc", lastDoc, hits[i].doc);
}
}
DuplicateFilter independently constructs a filter which chooses either the first or last occurence of all documents containing each key. This can be cached with minimal memory overhead.
Your second filter independently selects some other documents. The two choices may not coincide. To filter duplicates according to some arbitrary subset of all docs would probably need to use a field cache to be performant and this is where things get expensive RAM-wise
Related
I have the following Apache Lucene 7 application:
StandardAnalyzer standardAnalyzer = new StandardAnalyzer();
Directory directory = new RAMDirectory();
IndexWriterConfig config = new IndexWriterConfig(standardAnalyzer);
IndexWriter writer = new IndexWriter(directory, config);
Document document = new Document();
document.add(new TextField("content", new FileReader("document.txt")));
writer.addDocument(document);
writer.close();
IndexReader reader = DirectoryReader.open(directory);
IndexSearcher searcher = new IndexSearcher(reader);
Query fuzzyQuery = new FuzzyQuery(new Term("content", "Company"), 2);
TopDocs results = searcher.search(fuzzyQuery, 5);
System.out.println("Hits: " + results.totalHits);
System.out.println("Max score:" + results.getMaxScore())
when I use it with :
new FuzzyQuery(new Term("content", "Company"), 2);
the application works fine and returns the following result:
Hits: 1
Max score:0.35161147
but when I try to search with multi term query, for example:
new FuzzyQuery(new Term("content", "Company name"), 2);
it returns the following result:
Hits: 0
Max score:NaN
Anyway, the phrase Company name exists in the source document.txt file.
How to properly use FuzzyQuery in this case in order to be able to do the fuzzy search for multi-word phrases.
UPDATED
Based on the provided solution I have tested it on the following text information:
Company name: BlueCross BlueShield Customer Service
1-800-521-2227
of Texas Preauth-Medical 1-800-441-9188
Preauth-MH/CD 1-800-528-7264
Blue Card Access 1-800-810-2583
For the following query:
SpanQuery[] clauses = new SpanQuery[2];
clauses[0] = new SpanMultiTermQueryWrapper<FuzzyQuery>(new FuzzyQuery(new Term("content", "BlueCross"), 2));
clauses[1] = new SpanMultiTermQueryWrapper<FuzzyQuery>(new FuzzyQuery(new Term("content", "BlueShield"), 2));
SpanNearQuery query = new SpanNearQuery(clauses, 0, true);
the search works fine:
Hits: 1
Max score:0.5753642
but when I try to corrupt a little bit the search query(for example from BlueCross to BlueCros)
SpanQuery[] clauses = new SpanQuery[2];
clauses[0] = new SpanMultiTermQueryWrapper<FuzzyQuery>(new FuzzyQuery(new Term("content", "BlueCros"), 2));
clauses[1] = new SpanMultiTermQueryWrapper<FuzzyQuery>(new FuzzyQuery(new Term("content", "BlueShield"), 2));
SpanNearQuery query = new SpanNearQuery(clauses, 0, true);
it stops working and returns:
Hits: 0
Max score:NaN
The problem here is the following, you're using TextField, which is tokenizing field. E.g. your text "Company name is working on something" would be effectively split by spaces (and others delimeters). So, even if you have the text Company name, during indexation it will become Company, name, is, etc.
In this case this TermQuery won't be able to find what you're looking for. The trick which going to help you would look like this:
SpanQuery[] clauses = new SpanQuery[2];
clauses[0] = new SpanMultiTermQueryWrapper(new FuzzyQuery(new Term("content", "some"), 2));
clauses[1] = new SpanMultiTermQueryWrapper(new FuzzyQuery(new Term("content", "text"), 2));
SpanNearQuery query = new SpanNearQuery(clauses, 0, true);
However, I wouldn't recommend this approach much, especially if your load would be big and you're planning on searching on a 10 term long company names. One should be aware, that those query are potentially heavy to execute.
The following problem with BlueCros is the following. By default Lucene uses StandardAnalyzer for TextField. So it means it effectively lowercase the terms, basically it means that BlueCross in the content field becomes bluecross.
Fuzzy difference between BlueCros and bluecross is 3, that's the reason you do not have a match.
Simple proposal would be to convert term in query to the lowercase, by doing something like .toLowerCase()
In general, one should prefer to use same analyzers during the query time as well (e.g. during construction of the query)
For Lucene.Net it can be like this.
private string _IndexPath = #"Your Index Path";
private Directory _Directory;
private Searcher _IndexSearcher;
private MultiPhraseQuery _MultiPhraseQuery;
_Directory = FSDirectory.Open(_IndexPath);
IndexReader indexReader = IndexReader.Open(_Directory, true);
string field = "Name" // Your field name
string keyword = "big red fox"; // your search term
float fuzzy = 0,7f; // between 0-1
using (_IndexSearcher = new IndexSearcher(indexReader))
{
// "big red fox" to [big,red,fox]
var keywordSplit = keyword.Split();
_MultiPhraseQuery = new MultiPhraseQuery();
FuzzyTermEnum[] _FuzzyTermEnum = new FuzzyTermEnum[keywordSplit.Length];
Term[] _Term = new Term[keywordSplit.Length];
for (int i = 0; i < keywordSplit.Length; i++)
{
_FuzzyTermEnum[i] = new FuzzyTermEnum(indexReader, new Term(field, keywordSplit[i]),fuzzy);
_Term[i] = _FuzzyTermEnum[i].Term;
if (_Term[i] == null)
{
_MultiPhraseQuery.Add(new Term(field, keywordSplit[i]));
}
else
{
_MultiPhraseQuery.Add(_FuzzyTermEnum[i].Term);
}
}
var results = _IndexSearcher.Search(_MultiPhraseQuery, indexReader.MaxDoc);
foreach (var loopDoc in results.ScoreDocs.OrderByDescending(s => s.Score))
{
//YourCode Here
}
}
I've implemented a lucene-based software to index more than 10 millions of person's names and these names can be written on different ways like "Luíz" and "Luis". The index was created using the phonetic values of the respective tokens (a custom analyzer was created).
Currently, I'm using QueryParser to query for a given name with good results. But, in the book "Lucene in Action" is mentioned that SpanNearQuery can improve my queries using the proximity of tokens. I've played with the SpanNearQuery against a non-phonetic index of name and the results were superior compared to QueryParser.
As we should query using the same analyzer used to indexing, I couldn't find how I can use my custom phonetic analyzer and SpanNearQuery at same time, or rephrasing:
how can I use SpanNearQuery on the phonetic index?
Thanks in advance.
My first thought is: Wouldn't a phrase query with slop do the job? That would certainly be the easiest way:
"term1 term2"~5
This will use your phonetic analyzer, and produce a proximity query with the resulting tokens.
So, if you really do need to use SpanQueries here (perhaps you are using fuzzy queries or wildcards or some such, or PhraseQuery has been leering menacingly at you and you want nothing more to do with it), you'll need to do the analysis yourself. You can do this by getting a TokenStream from Analyzer.tokenStream, and iterating through the analyzed tokens.
If you are using a phonetic algorithm that produces a single code per term (soundex, for example):
SpanNearQuery.Builder nearBuilder = new SpanNearQuery.Builder("text", true);
nearBuilder.setSlop(4);
TokenStream stream = analyzer.tokenStream("text", queryStringToParse);
stream.addAttribute(CharTermAttribute.class);
stream.reset();
while(stream.incrementToken()) {
CharTermAttribute token = stream.getAttribute(CharTermAttribute.class);
nearBuilder.addClause(new SpanTermQuery(new Term("text", token.toString())));
}
Query finalQuery = nearBuilder.build();
stream.close();
If you are using a double metaphone, where you can have 1-2 terms at the same position, it's a bit more complex, as you'll need to consider those position increments:
SpanNearQuery.Builder nearBuilder = new SpanNearQuery.Builder("text", true);
nearBuilder.setSlop(4);
TokenStream stream = analyzer.tokenStream("text", "through and through");
stream.addAttribute(CharTermAttribute.class);
stream.addAttribute(PositionIncrementAttribute.class);
stream.reset();
String queuedToken = null;
while(stream.incrementToken()) {
CharTermAttribute token = stream.getAttribute(CharTermAttribute.class);
PositionIncrementAttribute increment = stream.getAttribute(PositionIncrementAttribute.class);
if (increment.getPositionIncrement() == 0) {
nearBuilder.addClause(new SpanOrQuery(
new SpanTermQuery(new Term("text", queuedToken)),
new SpanTermQuery(new Term("text", token.toString()))
));
queuedToken = null;
}
else if (increment.getPositionIncrement() >= 1 && queuedToken != null) {
nearBuilder.addClause(new SpanTermQuery(new Term("text", queuedToken)));
queuedToken = token.toString();
}
else {
queuedToken = token.toString();
}
}
if (queuedToken != null) {
nearBuilder.addClause(new SpanTermQuery(new Term("text", queuedToken)));
}
Query finalQuery = nearBuilder.build();
stream.close();
I am using Lucene.net to search a given document. Requirement is once search is done, it should highlight the searched term in the document. I have seen examples which returns the best fragments. But what i need is to highlight in the main content.
using (StandardAnalyzer standardAnalyzer = new StandardAnalyzer(Version.LUCENE_30, stopWords))
{
QueryParser parser = new QueryParser(Version.LUCENE_30, "Content", standardAnalyzer);
parser.AllowLeadingWildcard = true;
Query qry = parser.Parse(searchText);
Directory indexDir = CreateRAMDirectory(htmlContent);
IndexReader reader = IndexReader.Open(indexDir, true);
IndexSearcher searcher = new IndexSearcher(reader);
searcher.SetDefaultFieldSortScoring(true, true);
IFormatter formatter = new SimpleHTMLFormatter("<span style=\"font-weight:bold; background-color:yellow;\">", "</span>");
SimpleFragmenter fragmenter = new SimpleFragmenter(1000);
QueryScorer scorer = null;
scorer = new QueryScorer(qry);
ScoreDoc[] hits = searcher.Search(qry, null, 10000, Sort.RELEVANCE).ScoreDocs;
Highlighter highlighter = new Highlighter(formatter, scorer);
highlighter.TextFragmenter = fragmenter;
foreach (var result in hits)
{
int docId = result.Doc;
float score = result.Score;
Document doc = searcher.Doc(docId);
Lucene.Net.Analysis.TokenStream stream = standardAnalyzer.TokenStream("Content", new IO.StringReader(searchText));
String highlighterData = highlighter.GetBestFragments(stream, searchText, 1000, "");
}
}
I am a newbie to Lucene.net, how can i get the entire document with searched term content highlighted rather than fragments?
The fragmenter governs how large the chunks of text returned are. To use the entire field contents, just use NullFragmenter, instead of SimpleFragmenter.
Fragmenter fragmenter = new NullFragmenter();
.....
highlighter.TextFragmenter = fragmenter;
I had the same issue, even with the NullFragmenter, it only returned roughly 51 kB of text.
By analyzing the objects, I found out that there is another property at the highligher which sets how large a fragment would be at maximum. Set this value to the length of your string, then the whole document will be processed.
highlighter.TextFragmenter = new NullFragmenter();
highlighter.MaxDocCharsToAnalyze = text.Length;
We're having some problems with a SpanNotQuery in elasticsearch. It looks like the exclude part of the query is ignored.
To reproduce the problem I created a set of documents:
fiets kopen
fiets lopen
harrie kopen
harrie lopen
harrie fiets
kopen lopen
A SpanTermQuery for harrie will result in (3, 4, 5)
A SpanTermQuery for kopen will result in (1, 3, 6)
Now I want to combine this in a SpanNotQuery where the include is 'harrie' and exclude 'kopen'
I would expect the result to be (4, 5), but it is (3, 4, 5).
We have to use SpanQueries, this is just a small subset of the trouble we're running in to.
I created a unit test with only Lucene to show our problem
public class LuceneTest {
#Test
public void test() throws Exception {
RAMDirectory ram = new RAMDirectory();
createAndFillIndex(ram);
DirectoryReader directoryReader = DirectoryReader.open(ram);
IndexSearcher searcher = new IndexSearcher(directoryReader);
SpanQuery include = new SpanTermQuery(new Term("dummy", "harrie"));
SpanQuery exclude = new SpanTermQuery(new Term("dummy", "kopen"));
Query spanNot = new SpanNotQuery(include, exclude);
TopDocs search = searcher.search(spanNot, 100);
for (ScoreDoc scoreDoc : search.scoreDocs) {
Document result = searcher.doc(scoreDoc.doc);
String dummy = result.get("dummy");
System.out.println(scoreDoc.doc + ": " + dummy);
}
}
private void createAndFillIndex(RAMDirectory ram) throws IOException {
IndexWriterConfig conf = new IndexWriterConfig(Version.LUCENE_47, new SimpleAnalyzer(Version.LUCENE_47));
IndexWriter writer = new IndexWriter(ram, conf);
add(writer, "nul"); //0
add(writer, "fiets kopen"); //1
add(writer, "fiets lopen"); //2
add(writer, "harrie kopen"); //3
add(writer, "harrie lopen"); //4
add(writer, "harrie fiets"); //5
add(writer, "kopen lopen"); //6
writer.close();
}
private void add(IndexWriter writer, String value) throws IOException {
Document doc = new Document();
IndexableField f = new TextField("dummy", value, Field.Store.YES);
doc.add(f);
writer.addDocument(doc);
}
}
Does anyone know what we're doing wrong?
Thanks!
The documentation gives a hint here. It matches:
spans from include which have no overlap with spans from exclude
We're dealing with spans, not whole documents. The matching span for a simple term query though, is just the single term. In each of the three matched documents in your example, the matched span is harrie, which does not have any overlap with the term kopen in any of them.
It's probably more helpful to look at an example that shows how it's intended to work. You should be able to copy-paste the following fragments into your example (and by the way, thanks for the MCVE!). Let's try this query:
SpanQuery include = new SpanTermQuery(new Term("dummy", "harrie"));
SpanQuery exclude = new SpanTermQuery(new Term("dummy", "kopen"));
SpanQuery matchterm = new SpanTermQuery(new Term("dummy", "match"));
SpanQuery[] clauses = {include, matchterm};
SpanQuery nearQuery = new SpanNearQuery(clauses, 2, true);
Query spanNot = new SpanNotQuery(nearQuery, exclude);
against these documents:
add(writer, "harrie kopen match"); //1
add(writer, "harrie match kopen"); //2
add(writer, "harrie other stuff match kopen"); //3
You should see 2 hits.
Document 1: matches nearQuery with the span: "harrie kopen match". This contains "kopen" (that is, overlaps with the span matching exclude), and so it is eliminated by the SpanNotQuery
Document 2: matches nearQuery with the span: "harrie match". The document contains "kopen", but not within the matched span, so the document remains matched.
Document 3: matches nearQuery with the span: "marrie other stuff match". Again, the document contains "kopen", but not within the matched span, so it get through.
If you want the negation to be over the entire document, rather than just the matched span, use a BooleanQuery instead.
SpanQuery include = new SpanTermQuery(new Term("dummy", "harrie"));
SpanQuery exclude = new SpanTermQuery(new Term("dummy", "kopen"));
Query query = new BooleanQuery();
query.add(new BooleanClause(include, BooleanClause.Occur.MUST))
query.add(new BooleanClause(exclude, BooleanClause.Occur.MUST_NOT))
I have the following code:
public static void main(String[] args) throws Throwable {
String[] texts = new String[]{
"starts_with k mer",
"starts_with mer",
"starts_with bleue est mer",
"starts_with mer est bleue",
"starts_with mer bla1 bla2 bla3 bla4 bla5",
"starts_with bleue est la mer",
"starts_with la mer est bleue",
"starts_with la mer"
};
//write:
Set<String> stopWords = new HashSet<String>();
StandardAnalyzer stdAn = new StandardAnalyzer(Version.LUCENE_36, stopWords);
Directory fsDir = FSDirectory.open(INDEX_DIR);
IndexWriterConfig iwConf = new IndexWriterConfig(Version.LUCENE_36,stdAn);
iwConf.setOpenMode(IndexWriterConfig.OpenMode.CREATE);
IndexWriter indexWriter = new IndexWriter(fsDir,iwConf);
for(String text:texts) {
Document document = new Document();
document.add(new Field("title",text,Store.YES,Index.ANALYZED));
indexWriter.addDocument(document);
}
indexWriter.commit();
//read
IndexReader indexReader = IndexReader.open(fsDir);
IndexSearcher indexSearcher = new IndexSearcher(indexReader);
//get query:
//Query query = getQueryFromString("mer");
Query query = getQueryFromAPI("mer");
//explain
System.out.println("======== Query: "+query+"\n");
TopDocs hits = indexSearcher.search(query, 10);
for (ScoreDoc scoreDoc : hits.scoreDocs) {
Document doc = indexSearcher.doc(scoreDoc.doc);
System.out.println(">>> "+doc.get("title"));
System.out.println("Explain:");
System.out.println(indexSearcher.explain(query, scoreDoc.doc));
}
}
private static Query getQueryFromString(String searchString) throws Throwable {
Set<String> stopWords = new HashSet<String>();
Query query = new QueryParser(Version.LUCENE_36, "title",new StandardAnalyzer(Version.LUCENE_36, stopWords)).parse("("+searchString+") \"STARTS_WITH "+searchString+"\"");
return query;
}
private static Query getQueryFromAPI(String searchString) throws Throwable {
Set<String> stopWords = new HashSet<String>();
Query searchStringTermsMatchTitle = new QueryParser(Version.LUCENE_36, "title", new StandardAnalyzer(Version.LUCENE_36, stopWords)).parse(searchString);
PhraseQuery titleStartsWithSearchString = new PhraseQuery();
titleStartsWithSearchString.add(new Term("title","STARTS_WITH".toLowerCase()+" "+searchString));
BooleanQuery query = new BooleanQuery(true);
BooleanClause matchClause = new BooleanClause(searchStringTermsMatchTitle, Occur.SHOULD);
query.add(matchClause);
BooleanClause startsWithClause = new BooleanClause(titleStartsWithSearchString, Occur.SHOULD);
query.add(startsWithClause);
return query;
}
Basically I'm indexing some strings, and then I have two methods for creating a Lucene Query from user input, one that simply builds the corresponding Lucene query String "manually" (via string concatenation) and another that uses Lucene's API for building queries. They seem to be building the same query, as the debug output of the query shows the exact same query string, but the search results are not the same:
running the query built via String concatenation yields (for argument "mer"):
title:mer title:"starts_with mer"
and ideed in this case when I search with it I get documents that match the title:"starts_with mer" part first. Here's the explain on the first result:
>>> starts_with mer
Explain:
1.2329358 = (MATCH) sum of:
0.24658716 = (MATCH) weight(title:mer in 1), product of:
0.4472136 = queryWeight(title:mer), product of:
0.882217 = idf(docFreq=8, maxDocs=8)
0.50692016 = queryNorm
0.55138564 = (MATCH) fieldWeight(title:mer in 1), product of:
1.0 = tf(termFreq(title:mer)=1)
0.882217 = idf(docFreq=8, maxDocs=8)
0.625 = fieldNorm(field=title, doc=1)
0.9863486 = (MATCH) weight(title:"starts_with mer" in 1), product of:
0.8944272 = queryWeight(title:"starts_with mer"), product of:
1.764434 = idf(title: starts_with=8 mer=8)
0.50692016 = queryNorm
1.1027713 = fieldWeight(title:"starts_with mer" in 1), product of:
1.0 = tf(phraseFreq=1.0)
1.764434 = idf(title: starts_with=8 mer=8)
0.625 = fieldNorm(field=title, doc=1)
running the query built via Lucene query helper tools yields an apparently identical query:
title:mer title:"starts_with mer"
but this time the results are not the same, since in fact the title:"starts_with mer" part is not matched. Here's an explain of the first result:
>>> starts_with mer
Explain:
0.15185544 = (MATCH) sum of:
0.15185544 = (MATCH) weight(title:mer in 1), product of:
0.27540696 = queryWeight(title:mer), product of:
0.882217 = idf(docFreq=8, maxDocs=8)
0.312176 = queryNorm
0.55138564 = (MATCH) fieldWeight(title:mer in 1), product of:
1.0 = tf(termFreq(title:mer)=1)
0.882217 = idf(docFreq=8, maxDocs=8)
0.625 = fieldNorm(field=title, doc=1)
My question is: whay don't I get the same results? I'd really like to be able to use the Query helper tools here, especially since there's the BooleanQuery(disableCoord) option which I'd like to use and I really don't know how to express direclly into Lucene query string. (Yes, my example passes "true" there, I've also tried with "false", same result).
===UPDATE
femtoRgon's answer is great: the problem was that I was adding the whole search string as a term, instead of first splitting it into terms and then adding each one to the query.
The answer femtoRgon gives works ok if the input string consists of one term: in this case, separatedly adding the "STARTS_WITH" text as one term, and then adding the search string as a 2nd term works.
However if the user inputs something that would be tokenzied by more than one term, you'd have to first split it into terms (preferably using the same analyzers and/or tokenizers that you used when indexing - to get consistent results) and then add each term to the query.
What I ended up doing is making a function that splits the query string into terms, using the same analyzer that I used for indexing:
private static List<String> getTerms(String text) throws Throwable {
Analyzer analyzer = getAnalyzer();
StringReader textReader = new StringReader(text);
TokenStream tokenStream = analyzer.tokenStream(FIELD_NAME_TITLE, textReader);
tokenStream.reset();
List<String> terms = new ArrayList<String>();
CharTermAttribute charTermAttribute = tokenStream.addAttribute(CharTermAttribute.class);
while (tokenStream.incrementToken()) {
String term = charTermAttribute.toString();
terms.add(term);
}
textReader.close();
tokenStream.close();
analyzer.close();
return terms;
}
Then I first add the "STARTS_WITH" as one term, and then each of the elements in the list as a separate term:
PhraseQuery titleStartsWithSearchString = new PhraseQuery();
titleStartsWithSearchString.add(new Term("title","STARTS_WITH".toLowerCase()));
for(String term:getTerms(searchString)) {
titleStartsWithSearchString.add(new Term("title",term));
}
I believe the problem you are running into is that you are adding the entire phrase to your PhraseQuery as a single term. In the index, and in the query parsed by the QueryParser, this will be split into terms "starts_with" and "mer", which must be found consecutively. However, in the query you have constructed, you have a single term in your PhraseQuery instead, the term "starts_with mer", which doesn't exist as a single term in the index.
You should be able to change the bit where you are constructing the PhraseQuery to:
PhraseQuery titleStartsWithSearchString = new PhraseQuery();
titleStartsWithSearchString.add(new Term("title","STARTS_WITH".toLowerCase())
titleStartsWithSearchString.add(new Term("title",searchString));