Apache Lucene Demo

Posted on | Edited on | In

IndexFiles

As we discussed in the previous walk-through, the IndexFiles class creates a Lucene Index. Let’s take a look at how it does this.

The main() method parses the command-line parameters, then in preparation for instantiating IndexWriter, opens a Directory, and instantiates StandardAnalyzer and IndexWriterConfig.

1
2
3
4
5
6
7
8
9
10
11
for(int i=0;i<args.length;i++) {
  if ("-index".equals(args[i])) {
    indexPath = args[i+1];
    i++;
  } else if ("-docs".equals(args[i])) {
    docsPath = args[i+1];
    i++;
  } else if ("-update".equals(args[i])) {
    create = false;
  }
}

The value of the -index command-line parameter is the name of the filesystem directory where all index information should be stored. If IndexFiles is invoked with a relative path given in the -index command-line parameter, or if the -index command-line parameter is not given, causing the default relative index path “index” to be used, the index path will be created as a subdirectory of the current working directory (if it does not already exist). On some platforms, the index path may be created in a different directory (such as the user’s home directory).

The -docs command-line parameter value is the location of the directory containing files to be indexed .

The -update command-line parameter tells IndexFiles not to delete the index if it already exists. When -update is not given, IndexFiles will first wipe the slate clean before indexing any documents.

Lucene Directorys are used by the IndexWriter to store information in the index. In addition to the FSDirectory implementation we are using, there are several other Directory subclasses that can write to RAM, to databases, etc.
(索引可以放在文件/内存/数据库…)

1
Directory dir = FSDirectory.open(Paths.get(indexPath));

Lucene Analyzers are processing pipelines that break up text into indexed tokens, a.k.a. terms, and optionally perform other operations on these tokens, e.g. downcasing, synonym insertion, filtering out unwanted tokens, etc. The Analyzer we are using is StandardAnalyzer, which creates tokens using the Word Break rules from the Unicode Text Segmentation algorithm specified in Unicode Standard Annex #29; converts tokens to lowercase; and then filters out stopwords. Stopwords are common language words such as articles (a, an, the, etc.) and other tokens that may have less value for searching. It should be noted that there are different rules for every language, and you should use the proper analyzer for each. Lucene currently provides Analyzers for a number of different languages (see the javadocs under lucene/analysis/common/src/java/org/apache/lucene/analysis).

The IndexWriterConfig instance holds all configuration for IndexWriter. For example, we set the OpenMode to use here based on the value of the -update command-line parameter.

Looking further down in the file, after IndexWriter is instantiated, you should see the indexDocs() code. This recursive function crawls the directories and creates Document objects. The Document is simply a data object to represent the text content from the file as well as its creation time and location. These instances are added to the IndexWriter. If the -update command-line parameter is given, the IndexWriterConfig OpenMode will be set to OpenMode.CREATE_OR_APPEND, and rather than adding documents to the index, the IndexWriter will update them in the index by attempting to find an already-indexed document with the same identifier (in our case, the file path serves as the identifier); deleting it from the index if it exists; and then adding the new document to the index.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
/** Indexes a single document */
static void indexDoc(IndexWriter writer, Path file, long lastModified) throws IOException {
  try (InputStream stream = Files.newInputStream(file)) {
    // make a new, empty document
    Document doc = new Document();

    // Add the path of the file as a field named "path".  Use a
    // field that is indexed (i.e. searchable), but don't tokenize
    // the field into separate words and don't index term frequency
    // or positional information:
    Field pathField = new StringField("path", file.toString(), Field.Store.YES);
    doc.add(pathField);

    // Add the last modified date of the file a field named "modified".
    // Use a LongPoint that is indexed (i.e. efficiently filterable with
    // PointRangeQuery).  This indexes to milli-second resolution, which
    // is often too fine.  You could instead create a number based on
    // year/month/day/hour/minutes/seconds, down the resolution you require.
    // For example the long value 2011021714 would mean
    // February 17, 2011, 2-3 PM.
    doc.add(new LongPoint("modified", lastModified));

    // Add the contents of the file to a field named "contents".  Specify a Reader,
    // so that the text of the file is tokenized and indexed, but not stored.
    // Note that FileReader expects the file to be in UTF-8 encoding.
    // If that's not the case searching for special characters will fail.
    doc.add(new TextField("contents", new BufferedReader(new InputStreamReader(stream, StandardCharsets.UTF_8))));

    if (writer.getConfig().getOpenMode() == OpenMode.CREATE) {
      // New index, so we just add the document (no old document can be there):
      System.out.println("adding " + file);
      writer.addDocument(doc);
    } else {
      // Existing index (an old copy of this document may have been indexed) so
      // we use updateDocument instead to replace the old one matching the exact
      // path, if present:
      System.out.println("updating " + file);
      writer.updateDocument(new Term("path", file.toString()), doc);
    }
  }
}

Searching Files

The SearchFiles class is quite simple. It primarily collaborates with an IndexSearcher, StandardAnalyzer, (which is used in the IndexFiles class as well) and a QueryParser. The query parser is constructed with an analyzer used to interpret your query text in the same way the documents are interpreted: finding word boundaries, downcasing, and removing useless words like ‘a’, ‘an’ and ‘the’. The Query object contains the results from the QueryParser which is passed to the searcher. Note that it’s also possible to programmatically construct a rich Query object without using the query parser. The query parser just enables decoding the Lucene query syntax into the corresponding Query object.

SearchFiles uses the IndexSearcher.search(query,n) method that returns TopDocs with max n hits. The results are printed in pages, sorted by score (i.e. relevance).

1
2
3
// Collect enough docs to show 5 pages
TopDocs results = searcher.search(query, 5 * hitsPerPage);
ScoreDoc[] hits = results.scoreDocs;