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Lucene 8.3.1 core API

Apache Lucene is a high-performance, full-featured text search engine library.

See: Description

Packages 
Package Description
org.apache.lucene
Top-level package.
org.apache.lucene.analysis
Text analysis.
org.apache.lucene.analysis.standard
Fast, general-purpose grammar-based tokenizer StandardTokenizer implements the Word Break rules from the Unicode Text Segmentation algorithm, as specified in Unicode Standard Annex #29.
org.apache.lucene.analysis.tokenattributes
General-purpose attributes for text analysis.
org.apache.lucene.codecs
Codecs API: API for customization of the encoding and structure of the index.
org.apache.lucene.codecs.blocktree
BlockTree terms dictionary.
org.apache.lucene.codecs.compressing
StoredFieldsFormat that allows cross-document and cross-field compression of stored fields.
org.apache.lucene.codecs.lucene50
Components from the Lucene 5.0 index format See org.apache.lucene.codecs.lucene80 for an overview of the index format.
org.apache.lucene.codecs.lucene60
Components from the Lucene 6.0 index format.
org.apache.lucene.codecs.lucene70
Components from the Lucene 7.0 index format.
org.apache.lucene.codecs.lucene80
Lucene 8.0 file format.
org.apache.lucene.codecs.perfield
Postings format that can delegate to different formats per-field.
org.apache.lucene.document
The logical representation of a Document for indexing and searching.
org.apache.lucene.geo
Geospatial Utility Implementations for Lucene Core
org.apache.lucene.index
Code to maintain and access indices.
org.apache.lucene.search
Code to search indices.
org.apache.lucene.search.similarities
This package contains the various ranking models that can be used in Lucene.
org.apache.lucene.search.spans
The calculus of spans.
org.apache.lucene.store
Binary i/o API, used for all index data.
org.apache.lucene.util
Some utility classes.
org.apache.lucene.util.automaton
Finite-state automaton for regular expressions.
org.apache.lucene.util.bkd
Block KD-tree, implementing the generic spatial data structure described in this paper.
org.apache.lucene.util.fst
Finite state transducers
org.apache.lucene.util.graph
Utility classes for working with token streams as graphs.
org.apache.lucene.util.mutable
Comparable object wrappers
org.apache.lucene.util.packed
Packed integer arrays and streams.

Apache Lucene is a high-performance, full-featured text search engine library. Here's a simple example how to use Lucene for indexing and searching (using JUnit to check if the results are what we expect):

    Analyzer analyzer = new StandardAnalyzer();

    Path indexPath = Files.createTempDirectory("tempIndex");
    Directory directory = FSDirectory.open(indexPath)
    IndexWriterConfig config = new IndexWriterConfig(analyzer);
    IndexWriter iwriter = new IndexWriter(directory, config);
    Document doc = new Document();
    String text = "This is the text to be indexed.";
    doc.add(new Field("fieldname", text, TextField.TYPE_STORED));
    iwriter.addDocument(doc);
    iwriter.close();
    
    // Now search the index:
    DirectoryReader ireader = DirectoryReader.open(directory);
    IndexSearcher isearcher = new IndexSearcher(ireader);
    // Parse a simple query that searches for "text":
    QueryParser parser = new QueryParser("fieldname", analyzer);
    Query query = parser.parse("text");
    ScoreDoc[] hits = isearcher.search(query, 10).scoreDocs;
    assertEquals(1, hits.length);
    // Iterate through the results:
    for (int i = 0; i < hits.length; i++) {
      Document hitDoc = isearcher.doc(hits[i].doc);
      assertEquals("This is the text to be indexed.", hitDoc.get("fieldname"));
    }
    ireader.close();
    directory.close();
    IOUtils.rm(indexPath);

The Lucene API is divided into several packages:

To use Lucene, an application should:
  1. Create Documents by adding Fields;
  2. Create an IndexWriter and add documents to it with addDocument();
  3. Call QueryParser.parse() to build a query from a string; and
  4. Create an IndexSearcher and pass the query to its search() method.
Some simple examples of code which does this are: To demonstrate these, try something like:
> java -cp lucene-core.jar:lucene-demo.jar:lucene-analyzers-common.jar org.apache.lucene.demo.IndexFiles -index index -docs rec.food.recipes/soups
adding rec.food.recipes/soups/abalone-chowder
  [ ... ]

> java -cp lucene-core.jar:lucene-demo.jar:lucene-queryparser.jar:lucene-analyzers-common.jar org.apache.lucene.demo.SearchFiles
Query: chowder
Searching for: chowder
34 total matching documents
1. rec.food.recipes/soups/spam-chowder
  [ ... thirty-four documents contain the word "chowder" ... ]

Query: "clam chowder" AND Manhattan
Searching for: +"clam chowder" +manhattan
2 total matching documents
1. rec.food.recipes/soups/clam-chowder
  [ ... two documents contain the phrase "clam chowder" and the word "manhattan" ... ]
    [ Note: "+" and "-" are canonical, but "AND", "OR" and "NOT" may be used. ]

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