如何在分布式环境中提高Lucene的性能？

Question

在分布式环境中搜索master-shard实现时,我将面临长搜索时间(10秒的顺序).但是,通过Luke的相同查询以毫秒为单位返回.

该应用程序是一个分布式系统.所有节点共享索引所在的公共NFS装载.为简单起见,我们考虑两个节点Node1和Node2.该/etc/fstab项目如下.

nfs:/vol/indexes /opt/indexes nfs rw,suid,nodev,rsize=32768,wsize=32768,soft,intr,tcp 0 0

有多个Feed(比如说)Feed1和Feed2命中系统,每个节点的每个Feed都有一个分片,每个Feed都有一个分片.索引看起来像

Feed1-master
Feed1-shard-Node1.com
Feed1-shard-Node1.com0
Feed1-shard-Node1.com1

执行搜索的代码是

FeedIndexManager fim = getManager(feedCode);
searcher = fim.getSearcher();
TopDocs docs = searcher.search(q, filter, start + max, sort);

private FeedIndexManager getManager(String feedCode) throws IOException {
  if (!_managers.containsKey(feedCode)) {
    synchronized(_managers) {
      if (!_managers.containsKey(feedCode)) {
        File shard = getShardIndexFile(feedCode);
        File master = getMasterIndexFile(feedCode);
        _managers.put(feedCode, new FeedIndexManager(shard, master));
      }
    }
  }  
  return _managers.get(feedCode);
}

FeedIndexManager如下.

public class FeedIndexManager implements Closeable {

  private static final Analyzer WRITE_ANALYZER = makeWriterAnalyzer();
  private final Directory _master;
  private SearcherManager _searcherManager;
  private final IndexPair _pair;

  private int _numFailedMerges = 0;
  private DateTime _lastMergeTime = new DateTime();

  public FeedIndexManager(File shard, File master) throws IOException {
    _master = NIOFSDirectory.open(master, new SimpleFSLockFactory(master));

    IndexWriter writer = null;
    try {
      writer = new IndexWriter(_master,
                               WRITE_ANALYZER, 
                               MaxFieldLength.LIMITED);
    } finally {
      if (null != writer) {
        writer.close();
      }
      writer = null;
    }

    _searcherManager = new SearcherManager(_master);
    _pair = new IndexPair(_master,
                          shard, 
                          new IndexWriterBuilder(WRITE_ANALYZER));
  }

  public IndexPair getIndexWriter() {
    return _pair;
  }

  public IndexSearcher getSearcher() {
    try {
      return _searcherManager.get();
    }
    catch (IOException ioe) {
      throw new DatastoreRuntimeException(
        "When trying to get an IndexSearcher for " + _master, ioe);
    }
  }

  public void releaseSearcher(IndexSearcher searcher) {
    try {
      _searcherManager.release(searcher);
    }
    catch (IOException ioe) {
      throw new DatastoreRuntimeException(
        "When trying to release the IndexSearcher " + searcher
        + " for " + _master, ioe);
    }
  }

  /**
   * Merges the changes from the shard into the master.
   */
  public boolean tryFlush() throws IOException {
    LOG.debug("Trying to flush index manager at " + _master
              + " after " + _numFailedMerges + " failed merges.");
    if (_pair.tryFlush()) {
      LOG.debug("I succesfully flushed " + _master);
      _numFailedMerges = 0;
      _lastMergeTime = new DateTime();
      return true;
    }
    LOG.warn("I couldn't flush " + _master + " after " + _numFailedMerges
             + " failed merges.");
    _numFailedMerges++;
    return false;
  }

  public long getMillisSinceMerge() {
    return new DateTime().getMillis() - _lastMergeTime.getMillis();
  }

  public long getNumFailedMerges() {
    return _numFailedMerges;
  }

  public void close() throws IOException {
    _pair.close();
  }

  /**
   * Return the Analyzer used for writing to indexes.
   */
  private static Analyzer makeWriterAnalyzer() {
    PerFieldAnalyzerWrapper analyzer = 
      new PerFieldAnalyzerWrapper(new LowerCaseAnalyzer());

    analyzer.addAnalyzer(SingleFieldTag.ID.toString(), new KeywordAnalyzer());
    // we want tokenizing on the CITY_STATE field
    analyzer.addAnalyzer(AddressFieldTag.CITY_STATE.toString(),
            new StandardAnalyzer(Version.LUCENE_CURRENT));
    return analyzer;
  }
}

消耗大约95-98%延迟的杀手是这个调用,搜索需要大约20秒,而如果索引是通过Luke打开的,则是以毫秒为单位.

TopDocs docs = searcher.search(q, filter, start + max, sort);

我有以下问题

1. 每个饲料有多个母版是否合理,还是应该将它减少到只有一个母版？索引中的元素数量约为5000万.

2. 在实体数量少于一百万(次秒响应)的馈送上,延迟较低.实体超过200万的馈送大约需要20秒.我应该每个节点只保留1个Shard,每个节点每个节点保留1个Shard吗？

3. 每隔15秒就会尝试从碎片到主控的合并.这个参数应该调整吗？

我目前正在使用Lucene 3.1.0和JDK 1.6.这些盒子是两个64位内核,内存为8 GB.目前,JVM最大运行速度为4 GB.

任何提高性能的建议都受到高度赞赏.我已经执行了Lucene通常规定的所有标准性能调整.非常感谢阅读这篇冗长的帖子.

Answer 1

也许这不是您正在寻找的答案，但请看一下Elastic Search。它是围绕 Lucene 的分布式集群服务层，可以通过 HTTP 进行查询，也可以嵌入运行。

而且速度非常快，快得快得离谱。它似乎已经在幕后正确调整了 Lucene，同时仍然公开了完整的 Lucene 配置选项（如果您需要使用它们）。

让 Lucene 在分布式环境中执行是很困难的，正如您所发现的，您最终会遇到令人讨厌的锁定问题。ElasticSearch 旨在解决该特定问题，因此您可以解决其他问题。