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From Thomas Becker <thomas.bec...@net-m.de>
Subject Re: lucene 2.9.0RC4 slower than 2.4.1?
Date Tue, 15 Sep 2009 13:30:40 GMT
Missed the attachment, sorry.

Thomas Becker wrote:
> Hi all,
> 
> I'm experiencing a performance degradation after migrating to 2.9 and running
> some tests. I'm getting out of ideas and any help to identify the reasons why
> 2.9 is slower than 2.4 are highly appreciated.
> 
> We've had some issues with custom sorting in lucene 2.4.1. We worked around them
> by sorting the resultsets manually and caching the results after sorting (memory
> consuming but fast).
> 
> I now migrated to lucene 2.9.0RC4. Build some new FieldComparatorSource
> implementation for sorting and refactored all deprecated api calls to the new
> lucene 2.9 api.
> 
> Everything works fine from a functional perspective. But performance severly is
> (negatively) affected by lucene 2.9.
> 
> I profiled the application for a couple of hours, build a jmeter load test and
> compared the following scenarios:
> 
> 1. lucene 2.9 - new api
> 2. lucene 2.9 - old api and custom sorting after lucene
> 3. lucene 2.4.1 - old api and custom sorting after lucene (what we had up2now)
> 
> Please find attached an rrd graph showing the results. The lighter the color the
> faster the request has been served. y=# requests, x=time.
> 
> Most interestingly simply switching the lucene jars between 2.4 and 2.9 degraded
> response times and therefore throughput (see results of testcase 2 and 3).
> Adapting to the new api decreased performance again. The difference between
> testcase 1 and 2 is most probably due to precached custom sorted results.
> 
> The application under test is a dedicated lucene search engine doing nothing
> else, but serving search requests. We're running a cluster of them in prd and
> it's incredibly fast. With the old implementation and prd traffic we've above
> 98% of the requests served in 200ms.
> The index under test contains about 3 million documents (with lots of fields),
> consumes about 2,5gig disk space and is stored on a tmpfs RAMDISK provided by
> the linux kernel.
> 
> Most interesting methods used for searching are:
> 
> getHitsCount (is there a way to speed this up?):
> 
> 	public int getHitsCount(String query, Filter filter) throws
> LuceneServiceException {
> 		log.debug("getHitsCount('{}, {}')", query, filter);
> 		if (StringUtils.isBlank(query)) {
> 			log.warn("getHitsCount: empty lucene query");
> 			return 0;
> 		}
> 		long startTimeMillis = System.currentTimeMillis();
> 		int count = 0;
> 
> 		if (indexSearcher == null) {
> 			return 0;
> 		}
> 
> 		BooleanQuery.setMaxClauseCount(MAXCLAUSECOUNT);
> 		Query q = null;
> 		try {
> 			q = createQuery(query);
> 			TopScoreDocCollector tsdc = TopScoreDocCollector.create(1, true);
> 			indexSearcher.search(q, filter, tsdc);
> 			count = tsdc.getTotalHits();
> 			log.info("getHitsCount: count = {}",count);
> 		} catch (ParseException ex) {
> 			throw new LuceneServiceException("invalid lucene query:" + query, ex);
> 		} catch (IOException e) {
> 			throw new LuceneServiceException(" indexSearcher could be corrupted", e);
> 		} finally {
> 			long durationMillis = System.currentTimeMillis() - startTimeMillis;
> 			if (durationMillis > slowQueryLimit) {
> 				log.warn("getHitsCount: Slow query: {} ms, query={}", durationMillis, query);
> 			}
> 			log.debug("getHitsCount: query took {} ms", durationMillis);
> 		}
> 		return count;
> 	}
> 
> search:
> 	public List<Document> search(String query, Filter filter, Sort sort, int from,
> int size) throws LuceneServiceException {
> 		log.debug("{} search('{}', {}, {}, {}, {})", new Object[] { indexAlias, query,
> filter, sort, from, size });
> 		long startTimeMillis = System.currentTimeMillis();
> 
> 		List<Document> docs = new ArrayList<Document>();
> 		if (indexSearcher == null) {
> 			return docs;
> 		}
> 		Query q = null;
> 		try {
> 			if (query == null) {
> 				log.warn("search: lucene query is null...");
> 				return docs;
> 			}
> 			q = createQuery(query);
> 			BooleanQuery.setMaxClauseCount(MAXCLAUSECOUNT);
> 			if (size < 0 || size > maxNumHits) {
> 				// set hard limit for numHits
> 				size = maxNumHits;
> 				if (log.isDebugEnabled())
> 					log.debug("search: Size set to hardlimit: {} for query: {} with filter:
> {}", new Object[] { size, query, filter });
> 			}
> 			TopFieldCollector collector = TopFieldCollector.create(sort, size + from,
> true, false, false, true);
> 			indexSearcher.search(q, filter, collector);
> 			if(size > collector.getTotalHits())
> 				size = collector.getTotalHits();
> 			if (size > 100000)
> 				log.info("search: size: {} bigger than 100.000 for query: {} with filter:
> {}", new Object[] { size, query, filter });
> 			TopDocs td = collector.topDocs(from, size);
> 			ScoreDoc[] scoreDocs = td.scoreDocs;
> 			for (ScoreDoc scoreDoc : scoreDocs) {
> 				docs.add(indexSearcher.doc(scoreDoc.doc));
> 			}
> 		} catch (ParseException e) {
> 			log.warn("search: ParseException: {}", e.getMessage());
> 			if (log.isDebugEnabled())
> 				log.warn("search: ParseException: ", e);
> 			return Collections.emptyList();
> 		} catch (IOException e) {
> 			log.warn("search: IOException: ", e);
> 			return Collections.emptyList();
> 		} finally {
> 			long durationMillis = System.currentTimeMillis() - startTimeMillis;
> 			if (durationMillis > slowQueryLimit) {
> 				log.warn("search: Slow query: {} ms, query={}, indexUsed={}",
> 						new Object[] { durationMillis, query,
> indexSearcher.getIndexReader().directory() });
> 			}
> 			log.debug("search: query took {} ms", durationMillis);
> 		}
> 		return docs;
> 	}
> 
> I'm wondering why others are experiencing better performance with 2.9 and why
> our implementations performance is going bad. Maybe our way of using the 2.9 api
> is not the best and sorting is definetly expensive.
> 
> Any ideas are appreciated. I'm torning out my hair since hours and days to find
> the root cause. Also hints how I could find the bottlenecks myself are appreciated.
> 
> Cheers,
> Thomas
> 

-- 
Thomas Becker
Senior JEE Developer

net mobile AG
Zollhof 17
40221 Düsseldorf
GERMANY

Phone:    +49 211 97020-195
Fax:      +49 211 97020-949
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E-Mail:   mailto:thomas.becker@net-m.de
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