I am intrigued by this and decided to mock a quick and dirty example
of such an IndexReader. After a little trial-and-error I got it
working at least for TermQuery and WildcardQuery. I've pasted my code
below as an example, but there is much room for improvement,
especially in terms of performance and also in keeping track of term
frequency, and also it would be nicer if it handled the analysis
internally.
I think something like this would make a handy addition to our contrib
area at least. I'd be happy to receive improvements to this and then
add it to a contrib subproject.
Perhaps this would be a handy way to handle situations where users
have queries saved in a system and need to be alerted whenever a new
document arrives matching the saved queries?
Erik
-----Original Message-----
From: Wolfgang Hoschek [mailto:[EMAIL PROTECTED]
Sent: Thursday, April 14, 2005 4:04 PM
To: java-dev@lucene.apache.org
Subject: Re: [Performance] Streaming main memory indexing of single
strings
This seems to be a promising avenue worth exploring. My gutfeeling is
that this could easily be 10-100 times faster.
The drawback is that it requires a fair amount of understanding of
intricate Lucene internals, pulling those pieces together and adapting
them as required for the seemingly simple "float match(String text,
Query query)".
I might give it a shot but I'm not sure I'll be able to pull this off!
Is there any similar code I could look at as a starting point?
Wolfgang.
On Apr 14, 2005, at 1:13 PM, Robert Engels wrote:
I think you are not approaching this the correct way.
Pseudo code:
Subclass IndexReader.
Get tokens from String 'document' using Lucene analyzers.
Build simple hash-map based data structures using tokens for terms,
and term
positions.
reimplement termDocs() and termPositions() to use the structures from
above.
run searches.
start again with next document.
-----Original Message-----
From: Wolfgang Hoschek [mailto:[EMAIL PROTECTED]
Sent: Thursday, April 14, 2005 2:56 PM
To: java-dev@lucene.apache.org
Subject: Re: [Performance] Streaming main memory indexing of single
strings
Otis, this might be a misunderstanding.
- I'm not calling optimize(). That piece is commented out you if look
again at the code.
- The *streaming* use case requires that for each query I add one
(and
only one) document (aka string) to an empty index:
repeat N times (where N is millions or billions):
add a single string (aka document) to an empty index
query the index
drop index (or delete it's document)
with the following API being called N times: float match(String text,
Query query)
So there's no possibility of adding many documents and thereafter
running the query. This in turn seems to mean that the IndexWriter
can't be kept open - unless I manually delete each document after
each
query to repeatedly reuse the RAMDirectory, which I've also tried
before without any significant performance gain - deletion seems to
have substantial overhead in itself. Perhaps it would be better if
there were a Directory.deleteAllDocuments() or similar. Did you have
some other approach in mind?
As I said, Lucene's design doesn't seem to fit this streaming use
case
pattern well. In *this* scenario one could easily do without any
locking, and without byte level organization in RAMDirectory and
RAMFile, etc because a single small string isn't a large persistent
multi-document index.
For some background, here's a small example for the kind of XQuery
functionality Nux/Lucene integration enables:
(: An XQuery that finds all books authored by James that have
something
to do with "fish", sorted by relevance :)
declare namespace lucene = "java:nux.xom.xquery.XQueryUtil";
declare variable $query := "fish*~";
for $book in /books/book[author="James" and lucene:match(string(.),
$query) > 0.0]
let $score := lucene:match(string($book), $query)
order by $score descending
return (<score>{$score}</score>, $book)
More interestingly one can use this for classifying and routing XML
messages based on rules (i.e. queries) inspecting their content...
Any other clues about potential improvements would be greatly
appreciated.
Wolfgang.
On Apr 13, 2005, at 10:09 PM, Otis Gospodnetic wrote:
It looks like you are calling that IndexWriter code in some loops,
opening it and closing it in every iteration of the loop and also
calling optimize. All of those things could be improved.
Keep your IndexWriter open, don't close it, and optimize the index
only
once you are done adding documents to it.
See the highlights and the snipets in the first hit:
http://www.lucenebook.com/search?query=when+to+optimize
Otis
--- Wolfgang Hoschek <[EMAIL PROTECTED]> wrote:
Hi,
I'm wondering if anyone could let me know how to improve Lucene
performance for "streaming main memory indexing of single strings".
This would help to effectively integrate Lucene with the Nux XQuery
engine.
Below is a small microbenchmark simulating STREAMING XQuery
fulltext
search as typical for XML network routers, message queuing system,
P2P
networks, etc. In this on-the-fly main memory indexing scenario,
each
individual string is immediately matched as soon as it becomes
available without any persistance involved. This usage scenario and
corresponding performance profile is quite different in comparison
to
fulltext search over persistent (read-mostly) indexes.
The benchmark runs at some 3000 lucene queries/sec (lucene-1.4.3)
which
is unfortunate news considering the XQuery engine can easily walk
hundreds of thousands of XML nodes per second. Ideally I'd like to
run
at some 100000 queries/sec. Runnning this through the JDK 1.5
profiler
it seems that most time is spent in and below the following calls:
writer = new IndexWriter(dir, analyzer, true);
writer.addDocument(...);
writer.close();
I tried quite a few variants of the benchmark with various options,
unfortunately with little or no effect.
Lucene just does not seem to designed to do this sort of "transient
single string index" thing. All code paths related to opening,
closing,
reading, writing, querying and object creation seem to be designed
for
large persistent indexes.
Any advice on what I'm missing or what could be done about it would
be
greatly appreciated.
Wolfgang.
P.S. the benchmark code is attached as a file below:
package nux.xom.pool;
import java.io.IOException;
//import java.io.Reader;
import org.apache.lucene.analysis.Analyzer;
//import org.apache.lucene.analysis.LowerCaseTokenizer;
//import org.apache.lucene.analysis.PorterStemFilter;
//import org.apache.lucene.analysis.SimpleAnalyzer;
//import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
//import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.queryParser.ParseException;
import org.apache.lucene.queryParser.QueryParser;
import org.apache.lucene.search.Hits;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.Searcher;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;
public final class LuceneMatcher { // TODO: make non-public
private final Analyzer analyzer;
// private final Directory dir = new RAMDirectory();
public LuceneMatcher() {
this(new StandardAnalyzer());
// this(new SimpleAnalyzer());
// this(new StopAnalyzer());
// this(new Analyzer() {
// public final TokenStream tokenStream(String fieldName,
Reader
reader) {
// return new PorterStemFilter(new
LowerCaseTokenizer(reader));
// }
// });
}
public LuceneMatcher(Analyzer analyzer) {
if (analyzer == null)
throw new IllegalArgumentException("analyzer must not be
null");
this.analyzer = analyzer;
}
public Query parseQuery(String expression) throws ParseException {
QueryParser parser = new QueryParser("content", analyzer);
// parser.setPhraseSlop(0);
return parser.parse(expression);
}
/**
* Returns the relevance score by matching the given index against
the given
* Lucene query expression. The index must not contain more than
one
Lucene
* "document" (aka string to be searched).
*/
public float match(Directory index, Query query) {
Searcher searcher = null;
try {
searcher = new IndexSearcher(index);
Hits hits = searcher.search(query);
float score = hits.length() > 0 ? hits.score(0) : 0.0f;
return score;
} catch (IOException e) { // should never happen (RAMDirectory)
throw new RuntimeException(e);
} finally {
try {
if (searcher != null) searcher.close();
} catch (IOException e) { // should never happen (RAMDirectory)
throw new RuntimeException(e);
}
}
}
// public float match(String text, Query query) {
// return match(createIndex(text), query);
// }
public Directory createIndex(String text) {
Directory dir = new RAMDirectory();
IndexWriter writer = null;
try {
writer = new IndexWriter(dir, analyzer, true);
// writer.setUseCompoundFile(false);
// writer.mergeFactor = 2;
// writer.minMergeDocs = 1;
// writer.maxMergeDocs = 1;
writer.addDocument(createDocument(text));
// writer.optimize();
return dir;
} catch (IOException e) { // should never happen (RAMDirectory)
throw new RuntimeException(e);
} finally {
try {
if (writer != null) writer.close();
} catch (IOException e) { // should never happen
(RAMDirectory)
throw new RuntimeException(e);
}
}
}
private Document createDocument(String content) {
Document doc = new Document();
doc.add(Field.UnStored("content", content));
// doc.add(Field.Text("x", content));
return doc;
}
/**
* Lucene microbenchmark simulating STREAMING XQuery fulltext
search
as
* typical for XML network routers, message queuing system, P2P
networks,
* etc. In this on-the-fly main memory indexing scenario, each
individual
* string is immediately matched as soon as it becomes available
without any
* persistance involved. This usage scenario and corresponding
performance
* profile is quite different in comparison to fulltext search
over
* persistent (read-mostly) indexes.
*
* Example XPath:
count(/table/row[lucene:match(string(./firstname),
* "James") > 0.0])
*/
public static void main(String[] args) throws Exception {
int k = -1;
int runs = 5;
if (args.length > ++k) runs = Integer.parseInt(args[k]);
int nodes = 10000;
if (args.length > ++k) nodes = Integer.parseInt(args[k]);
String content = "James is out in the woods";
if (args.length > ++k) content = args[k];
String expression = "James";
if (args.length > ++k) expression = args[k];
LuceneMatcher matcher = new LuceneMatcher();
Query query = matcher.parseQuery(expression); // to be reused N
times
for (int r = 0; r < runs; r++) {
long start = System.currentTimeMillis();
int matches = 0;
for (int i = 0; i < nodes; i++) {
// if (LuceneUtil.match(content + i, expression) >
0.0f) {
if (matcher.match(matcher.createIndex(content +
i), query) >
0.0f) {
matches++;
}
}
long end = System.currentTimeMillis();
System.out.println("matches=" + matches);
System.out.println("secs=" + ((end-start) / 1000.0f));
System.out.println("queries/sec=" + (nodes /
((end-start) /
1000.0f)));
System.out.println();
}
}
}
public class StringIndexReader extends IndexReader {
private List terms;
public StringIndexReader(String strings[]) {
super(null);
terms = Arrays.asList(strings);
Collections.sort(terms);
}
public TermFreqVector[] getTermFreqVectors(int docNumber) throws
IOException {
System.out.println("StringIndexReader.getTermFreqVectors");
return new TermFreqVector[0];
}
public TermFreqVector getTermFreqVector(int docNumber, String field)
throws IOException {
System.out.println("StringIndexReader.getTermFreqVector");
return null;
}
public int numDocs() {
System.out.println("StringIndexReader.numDocs");
return 1;
}
public int maxDoc() {
System.out.println("StringIndexReader.maxDoc");
return 1;
}
public Document document(int n) throws IOException {
System.out.println("StringIndexReader.document");
return null;
}
public boolean isDeleted(int n) {
System.out.println("StringIndexReader.isDeleted");
return false;
}
public boolean hasDeletions() {
System.out.println("StringIndexReader.hasDeletions");
return false;
}
public byte[] norms(String field) throws IOException {
// TODO: what value to use for this?
System.out.println("StringIndexReader.norms: " + field);
return new byte[] { 1 };
}
public void norms(String field, byte[] bytes, int offset) throws
IOException {
System.out.println("StringIndexReader.norms: " + field + "*");
}
protected void doSetNorm(int doc, String field, byte value) throws
IOException {
System.out.println("StringIndexReader.doSetNorm");
}
public TermEnum terms() throws IOException {
System.out.println("StringIndexReader.terms");
return terms(null);
}
public TermEnum terms(final Term term) throws IOException {
System.out.println("StringIndexReader.terms: " + term);
TermEnum termEnum = new TermEnum() {
private String currentTerm;
private Iterator iter;
public boolean next() {
System.out.println("TermEnum.next");
if (iter.hasNext())
currentTerm = (String) iter.next();
return iter.hasNext();
}
public Term term() {
if (iter == null) {
iter = terms.iterator();
while (next()) {
if (currentTerm.startsWith(term.text()))
break;
}
}
System.out.println("TermEnum.term: " + currentTerm);
return new Term(term.field(), currentTerm);
}
public int docFreq() {
System.out.println("TermEnum.docFreq");
return 1;
}
public void close() {
System.out.println("TermEnum.close");
}
};
return termEnum;
}
public int docFreq(Term term) throws IOException {
System.out.println("StringIndexReader.docFreq: " + term);
return terms.contains(term.text()) ? 1 : 0;
}
public TermDocs termDocs() throws IOException {
System.out.println("StringIndexReader.termDocs");
TermDocs td = new TermDocs() {
private boolean done = false;
String currentTerm;
public void seek(Term term) {
System.out.println(".seek: " + term);
currentTerm = term.text();
done = false;
}
public void seek(TermEnum termEnum) {
seek(termEnum.term());
}
public int doc() {
System.out.println(".doc");
return 0;
}
public int freq() {
System.out.println(".freq");
return 1;
}
public boolean next() {
System.out.println(".next");
return false;
}
public int read(int[] docs, int[] freqs) {
System.out.println(".read: " + docs.length);
if (done) return 0;
done = true;
docs[0] = 0;
freqs[0] = freq();
return 1;
}
public boolean skipTo(int target) {
System.out.println(".skipTo");
return false;
}
public void close() {
System.out.println(".close");
}
};
return td;
}
public TermPositions termPositions() throws IOException {
System.out.println("StringIndexReader.termPositions");
return null;
}
protected void doDelete(int docNum) throws IOException {
System.out.println("StringIndexReader.doDelete");
}
protected void doUndeleteAll() throws IOException {
System.out.println("StringIndexReader.doUndeleteAll");
}
protected void doCommit() throws IOException {
System.out.println("StringIndexReader.doCommit");
}
protected void doClose() throws IOException {
System.out.println("StringIndexReader.doClose");
}
public Collection getFieldNames() throws IOException {
System.out.println("StringIndexReader.getFieldNames");
return null;
}
public Collection getFieldNames(boolean indexed) throws IOException {
System.out.println("StringIndexReader.getFieldNames");
return null;
}
public Collection getIndexedFieldNames(Field.TermVector tvSpec) {
System.out.println("StringIndexReader.getIndexedFieldNames");
return null;
}
public Collection getFieldNames(FieldOption fldOption) {
System.out.println("StringIndexReader.getFieldNames");
return null;
}
public static void main(String[] args) {
IndexReader reader = new StringIndexReader(new String[] {"foo",
"bar", "baz"});
IndexSearcher searcher = new IndexSearcher(reader);
Hits hits = null;
try {
hits = searcher.search(new WildcardQuery(new
Term("field","ba*")));
} catch (IOException e) {
e.printStackTrace();
}
System.out.println("found " + hits.length());
}
}
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