Urm and uploaded here:
http://ankeschwarzer.de/tmp/graph.jpg
Sorry.
Thomas Becker wrote:
> 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
>>
>
>
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Thomas Becker
Senior JEE Developer
net mobile AG
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40221 Düsseldorf
GERMANY
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