I tried it to index date with DateTools.dateToString() method. Its working properly for indexing as well as searching.
But my already indexed data which has some references is in such a way that it has indexed Date as a new Date().getTime().
So my problem is how to perform RangeSearch Query on this data...
Any solution to this???
Thanks in Advance.
You need to use a TermRangeQuery on your date field. That field always needs to be indexed with DateTools.dateToString() for it to work properly. Here's a full example of indexing and searching on a date range with Lucene 3.0:
public class LuceneDateRange {
public static void main(String[] args) throws Exception {
// setup Lucene to use an in-memory index
Directory directory = new RAMDirectory();
Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_30);
MaxFieldLength mlf = MaxFieldLength.UNLIMITED;
IndexWriter writer = new IndexWriter(directory, analyzer, true, mlf);
// use the current time as the base of dates for this example
long baseTime = System.currentTimeMillis();
// index 10 documents with 1 second between dates
for (int i = 0; i < 10; i++) {
Document doc = new Document();
String id = String.valueOf(i);
String date = buildDate(baseTime + i * 1000);
doc.add(new Field("id", id, Store.YES, Index.NOT_ANALYZED));
doc.add(new Field("date", date, Store.YES, Index.NOT_ANALYZED));
writer.addDocument(doc);
}
writer.close();
// search for documents from 5 to 8 seconds after base, inclusive
IndexSearcher searcher = new IndexSearcher(directory);
String lowerDate = buildDate(baseTime + 5000);
String upperDate = buildDate(baseTime + 8000);
boolean includeLower = true;
boolean includeUpper = true;
TermRangeQuery query = new TermRangeQuery("date",
lowerDate, upperDate, includeLower, includeUpper);
// display search results
TopDocs topDocs = searcher.search(query, 10);
for (ScoreDoc scoreDoc : topDocs.scoreDocs) {
Document doc = searcher.doc(scoreDoc.doc);
System.out.println(doc);
}
}
public static String buildDate(long time) {
return DateTools.dateToString(new Date(time), Resolution.SECOND);
}
}
You'll get much better search performance if you use a NumericField for your date, and then NumericRangeFilter/Query to do the range search.
You just have to encode your date as a long or int. One simple way is to call the .getTime() method of your Date, but this may be far more resolution (milli-seconds) than you need. If you only need down to the day, you can encode it as YYYYMMDD integer.
Then, at search time, do the same conversion on your start/end Dates and run NumericRangeQuery/Filter.
Related
I am trying to do autocomplete using lucene search functionality. I have the following code which searches by the query prefix but along with that it also gives me all the sentences containing that word while I want it to display only sentence or word starting exactly with that prefix.
ex: m
--holiday mansion houseboat
--eye muscles
--movies of all time
--machine
I want it to show only last 2 queries. How to do it am stucked here also I am new to lucene. Please can any one help me in this. Thanks in advance.
addDoc(IndexWriter w, String title, String isbn) throws IOException {
Document doc = new Document();
doc.add(new Field("title", title, Field.Store.YES, Field.Index.ANALYZED));
// use a string field for isbn because we don't want it tokenized
doc.add(new Field("isbn", isbn, Field.Store.YES, Field.Index.ANALYZED));
w.addDocument(doc);
}
Main:
try {
// 0. Specify the analyzer for tokenizing text.
// The same analyzer should be used for indexing and searching
StandardAnalyzer analyzer = new StandardAnalyzer();
// 1. create the index
Directory index = FSDirectory.open(new File(indexDir));
IndexWriter writer = new IndexWriter(index, new StandardAnalyzer(Version.LUCENE_30), true, IndexWriter.MaxFieldLength.UNLIMITED); //3
for (int i = 0; i < source.size(); i++) {
addDoc(writer, source.get(i), + (i + 1) + "z");
}
writer.close();
// 2. query
Term term = new Term("title", querystr);
//create the term query object
PrefixQuery query = new PrefixQuery(term);
// 3. search
int hitsPerPage = 20;
IndexReader reader = IndexReader.open(index);
IndexSearcher searcher = new IndexSearcher(reader);
TopScoreDocCollector collector = TopScoreDocCollector.create(hitsPerPage, true);
searcher.search(query, collector);
ScoreDoc[] hits = collector.topDocs().scoreDocs;
// 4. Get results
for (int i = 0; i < hits.length; ++i) {
int docId = hits[i].doc;
Document d = searcher.doc(docId);
System.out.println(d.get("title"));
}
reader.close();
} catch (Exception e) {
System.out.println("Exception (LuceneAlgo.getSimilarString()) : " + e);
}
}
}
I see two solutions:
as suggested by Yahnoosh, save the title field twice, Once as TextField (=analyzed) and once as StringField (not analyzed)
save it just as TextField, but When Querying use SpanFirstQuery
// 2. query
Term term = new Term("title", querystr);
//create the term query object
PrefixQuery pq = new PrefixQuery(term);
SpanQuery wrapper = new SpanMultiTermQueryWrapper<PrefixQuery>(pq);
Query final = new SpanFirstQuery(wrapper, 1);
If I understand your scenario correctly, you want to autocomplete on the title field.
The solution is to have two fields: one analyzed, to enable querying over it, one non-analyzed to have titles indexed without breaking them into individual terms.
Your autocomplete logic should issue prefix queries against the non-analyzed field to match only on the first word. Your term queries should be issued against the analyzed field for matches within the title.
I hope that makes sense.
I'm trying to create Term-Document matrix for a small corpus to further experiment with LSI. However, I couldn't find a way to do it with Lucene 4.4.
I know how to get TermVector for each document as following:
//create boolean query to search for a specific document (not shown)
TopDocs hits = searcher.search(query, 1);
Terms termVector = reader.getTermVector(hits.scoreDocs[0].doc, "contents");
System.out.println(termVector.size()); //just testing
I thought I can just union all the termVector together as columns in a matrix to get the matrix. However, termVector for different documents have different size. And we don't know how to pad 0 into the termVector. So, certainly, this method does not work.
Hence, I wonder if someone can show me how to create Term-Document vector with Lucene 4.4 please? (If possible, please show sample code).
If Lucene does not support this function, what is the other way you recommend to do it?
Many thanks,
I found the solution to my problem here. Very detail example given by Mr. Sujit, although the code is written in older version of Lucene so many things will have to be changed. I'll update details when I finish my code.
Here is my solution that works on Lucene 4.4
public class BuildTermDocumentMatrix {
public BuildTermDocumentMatrix(File index, File corpus) throws IOException{
reader = DirectoryReader.open(FSDirectory.open(index));
searcher = new IndexSearcher(reader);
this.corpus = corpus;
termIdMap = computeTermIdMap(reader);
}
/**
* Map term to a fix integer so that we can build document matrix later.
* It's used to assign term to specific row in Term-Document matrix
*/
private Map<String, Integer> computeTermIdMap(IndexReader reader) throws IOException {
Map<String,Integer> termIdMap = new HashMap<String,Integer>();
int id = 0;
Fields fields = MultiFields.getFields(reader);
Terms terms = fields.terms("contents");
TermsEnum itr = terms.iterator(null);
BytesRef term = null;
while ((term = itr.next()) != null) {
String termText = term.utf8ToString();
if (termIdMap.containsKey(termText))
continue;
//System.out.println(termText);
termIdMap.put(termText, id++);
}
return termIdMap;
}
/**
* build term-document matrix for the given directory
*/
public RealMatrix buildTermDocumentMatrix () throws IOException {
//iterate through directory to work with each doc
int col = 0;
int numDocs = countDocs(corpus); //get the number of documents here
int numTerms = termIdMap.size(); //total number of terms
RealMatrix tdMatrix = new Array2DRowRealMatrix(numTerms, numDocs);
for (File f : corpus.listFiles()) {
if (!f.isHidden() && f.canRead()) {
//I build term document matrix for a subset of corpus so
//I need to lookup document by path name.
//If you build for the whole corpus, just iterate through all documents
String path = f.getPath();
BooleanQuery pathQuery = new BooleanQuery();
pathQuery.add(new TermQuery(new Term("path", path)), BooleanClause.Occur.SHOULD);
TopDocs hits = searcher.search(pathQuery, 1);
//get term vector
Terms termVector = reader.getTermVector(hits.scoreDocs[0].doc, "contents");
TermsEnum itr = termVector.iterator(null);
BytesRef term = null;
//compute term weight
while ((term = itr.next()) != null) {
String termText = term.utf8ToString();
int row = termIdMap.get(termText);
long termFreq = itr.totalTermFreq();
long docCount = itr.docFreq();
double weight = computeTfIdfWeight(termFreq, docCount, numDocs);
tdMatrix.setEntry(row, col, weight);
}
col++;
}
}
return tdMatrix;
}
}
One can refer this code also. In the latest Lucene version It will be quite easy.
Example 15
public void testSparseFreqDoubleArrayConversion() throws Exception {
Terms fieldTerms = MultiFields.getTerms(index, "text");
if (fieldTerms != null && fieldTerms.size() != -1) {
IndexSearcher indexSearcher = new IndexSearcher(index);
for (ScoreDoc scoreDoc : indexSearcher.search(new MatchAllDocsQuery(), Integer.MAX_VALUE).scoreDocs) {
Terms docTerms = index.getTermVector(scoreDoc.doc, "text");
Double[] vector = DocToDoubleVectorUtils.toSparseLocalFreqDoubleArray(docTerms, fieldTerms);
assertNotNull(vector);
assertTrue(vector.length > 0);
}
}
}
I have a web application which stores customers usernames, emails and phone numbers.
I want customers to search for other users using email, phone or username for a start just to understand the whole lucene concept. then later on i will add functionality to search within a user an item he posts. I am following this example on www.lucenetutorial.com/lucene-in-5-minutes.html
public class HelloLucene {
public static void main(String[] args) throws IOException, ParseException {
// 0. Specify the analyzer for tokenizing text.
// The same analyzer should be used for indexing and searching
StandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_40);
// 1. create the index
Directory index = new RAMDirectory();
IndexWriterConfig config = new IndexWriterConfig(Version.LUCENE_40, analyzer);
IndexWriter w = new IndexWriter(index, config);
addDoc(w, "Lucene in Action", "193398817");
addDoc(w, "Lucene for Dummies", "55320055Z");
addDoc(w, "Managing Gigabytes", "55063554A");
addDoc(w, "The Art of Computer Science", "9900333X");
w.close();
// 2. query
String querystr = args.length > 0 ? args[0] : "lucene";
// the "title" arg specifies the default field to use
// when no field is explicitly specified in the query.
Query q = new QueryParser(Version.LUCENE_40, "title", analyzer).parse(querystr);
// 3. search
int hitsPerPage = 10;
IndexReader reader = DirectoryReader.open(index);
IndexSearcher searcher = new IndexSearcher(reader);
TopScoreDocCollector collector = TopScoreDocCollector.create(hitsPerPage, true);
searcher.search(q, collector);
ScoreDoc[] hits = collector.topDocs().scoreDocs;
// 4. display results
System.out.println("Found " + hits.length + " hits.");
for(int i=0;i<hits.length;++i) {
int docId = hits[i].doc;
Document d = searcher.doc(docId);
System.out.println((i + 1) + ". " + d.get("isbn") + "\t" + d.get("title"));
}
// reader can only be closed when there
// is no need to access the documents any more.
reader.close();
}
private static void addDoc(IndexWriter w, String title, String isbn) throws IOException {
Document doc = new Document();
doc.add(new TextField("title", title, Field.Store.YES));
// use a string field for isbn because we don't want it tokenized
doc.add(new StringField("isbn", isbn, Field.Store.YES));
w.addDocument(doc);
}
}
I want new customers to be added to index automatically on registration. customerId is timestamp. so should i add a new document for each field on the customers details or should i concatenate all fields into a string and add as a single document? Please go easy on me I am really new.
This is a good place to start with Lucene indexing mechanism
http://www.ibm.com/developerworks/library/wa-lucene/
In the bottom line when lucene index the document, it first converts it into lucene document form. This lucene document comprises of set of fields and each field is a set of terms. Term are nothing but stream of bytes.
The document which is to be index to pass to analyzer which forms these terms out of it, and these terms keywords which are match during searching process.
When we perform a search process the query is analyzed through the same analyzer and then is match against the terms.
So you dont have to create a document for each field, rather you should create a single document for each user.
i index one big database overview (just text fields) on which the user must be able to search (below in indexFields method). This search before was done in the database with ILIKE query, but was slow, so now search is done on index. Hovewer, when i compare search results from db query, and results i get with the index search, there is always much less results with search from index.
Im not sure if i am making mistake in indexing or in search process. To me all seems to make sense here. Any ideas?
Here is the code. All advices appreciated!
// INDEXING
StandardAnalyzer analyzer = new StandardAnalyzer(
Version.LUCENE_CURRENT, stopSet); // stop set is empty
IndexWriter writer = new IndexWriter(INDEX_DIR, analyzer, true,
IndexWriter.MaxFieldLength.UNLIMITED);
indexFields(writer);
writer.optimize();
writer.commit();
writer.close();
analyzer.close();
private void indexFields(IndexWriter writer) {
DetachedCriteria criteria = DetachedCriteria
.forClass(Activit.class);
int count = 0;
int max = 50000;
boolean existMoreToIndex = true;
List<Activit> result = new ArrayList<Activit>();
while (existMoreToIndex) {
try {
result = activitService.listPaged(count, max);
if (result.size() < max)
existMoreToIndex = false;
if (result.size() == 0)
return;
for (Activit ao : result) {
Document doc = new Document();
doc.add(new Field("id", String.valueOf(ao.getId()),
Field.Store.YES, Field.Index.ANALYZED));
if(ao.getActivitOwner()!=null)
doc.add(new Field("field1", ao.getActivityOwner(),Field.Store.YES, Field.Index.ANALYZED));
if(ao.getActivitResponsible() != null)
doc.add(new Field("field2", ao.getActivityResponsible(), Field.Store.YES,Field.Index.ANALYZED));
try {
writer.addDocument(doc);
} catch (CorruptIndexException e) {
e.printStackTrace();
}
count += max;
//SEARCH
public List<Activit> searchActivitiesInIndex(String searchCriteria) {
Set<String> stopSet = new HashSet<String>(); // empty because we do not want to remove stop words
Version version = Version.LUCENE_CURRENT;
String[] fields = {
"field1", "field2"};
try {
File tempFile = new File("C://testindex");
Directory INDEX_DIR = new SimpleFSDirectory(tempFile);
Searcher searcher = new IndexSearcher(INDEX_DIR, true);
QueryParser parser = new MultiFieldQueryParser(version, fields, new StandardAnalyzer(
version, stopSet));
Query query = parser.parse(searchCriteria);
TopDocs topDocs = searcher.search(query, 500);
ScoreDoc[] hits = topDocs.scoreDocs;
//here i always get smaller hits lenght
searcher.close();
} catch (Exception e) {
e.printStackTrace();
}
}
Most likely the analyzer is doing something that you aren't expecting.
Open your index using Luke, you can see what your (analyzed) indexed documents look like, as well as your parsed queries - should let you see what's going wrong.
Also, can you give an example of searchCriteria? And the corresponding SQL query? Without that, it's hard to know if the indexing is done correctly. You may also not need to use MultiFieldQueryParser, which is quite inefficient.
how do you get the matching fuzzy term and its offset when using Lucene Fuzzy Search?
IndexSearcher mem = ....(some standard code)
QueryParser parser = new QueryParser(Version.LUCENE_30, CONTENT_FIELD, analyzer);
TopDocs topDocs = mem.search(parser.parse("wuzzy~"), 1);
// the ~ triggers the fuzzy search as per "Lucene In Action"
The fuzzy search works fine. If a document contains the term "fuzzy" or "luzzy", it is matched. How do I get which term matched and what are their offsets?
I have made sure that all CONTENT_FIELDs are added with termVectorStored with positions and offsets .
There was no straight forward way of doing this, however I reconsidered Jared's suggestion and was able to get the solution working.
I am documenting this here just in case someone else has the same issue.
Create a class that implements org.apache.lucene.search.highlight.Formatter
public class HitPositionCollector implements Formatter
{
// MatchOffset is a simple DTO
private List<MatchOffset> matchList;
public HitPositionCollector(
{
matchList = new ArrayList<MatchOffset>();
}
// this ie where the term start and end offset as well as the actual term is captured
#Override
public String highlightTerm(String originalText, TokenGroup tokenGroup)
{
if (tokenGroup.getTotalScore() <= 0)
{
}
else
{
MatchOffset mo= new MatchOffset(tokenGroup.getToken(0).toString(), tokenGroup.getStartOffset(),tokenGroup.getEndOffset());
getMatchList().add(mo);
}
return originalText;
}
/**
* #return the matchList
*/
public List<MatchOffset> getMatchList()
{
return matchList;
}
}
Main Code
public void testHitsWithHitPositionCollector() throws Exception
{
System.out.println(" .... testHitsWithHitPositionCollector");
String fuzzyStr = "bro*";
QueryParser parser = new QueryParser(Version.LUCENE_30, "f", analyzer);
Query fzyQry = parser.parse(fuzzyStr);
TopDocs hits = searcher.search(fzyQry, 10);
QueryScorer scorer = new QueryScorer(fzyQry, "f");
HitPositionCollector myFormatter= new HitPositionCollector();
//Highlighter(Formatter formatter, Scorer fragmentScorer)
Highlighter highlighter = new Highlighter(myFormatter,scorer);
highlighter.setTextFragmenter(
new SimpleSpanFragmenter(scorer)
);
Analyzer analyzer2 = new SimpleAnalyzer();
int loopIndex=0;
//for (ScoreDoc sd : hits.scoreDocs) {
Document doc = searcher.doc( hits.scoreDocs[0].doc);
String title = doc.get("f");
TokenStream stream = TokenSources.getAnyTokenStream(searcher.getIndexReader(),
hits.scoreDocs[0].doc,
"f",
doc,
analyzer2);
String fragment = highlighter.getBestFragment(stream, title);
System.out.println(fragment);
assertEquals("the quick brown fox jumps over the lazy dog", fragment);
MatchOffset mo= myFormatter.getMatchList().get(loopIndex++);
assertTrue(mo.getEndPos()==15);
assertTrue(mo.getStartPos()==10);
assertTrue(mo.getToken().equals("brown"));
}