lucene IndexOptions可以设置DOCS_AND_FREQS_AND_POSITIONS_AND_OFFSETS DOCS，ES里也可以设置

org.apache.lucene.index

• 1. Enum Constant and Description

     DOCS_AND_FREQS

     Only documents and term frequencies are indexed: positions are omitted.
     DOCS_AND_FREQS_AND_POSITIONS

     Indexes documents, frequencies and positions.
     DOCS_AND_FREQS_AND_POSITIONS_AND_OFFSETS

     Indexes documents, frequencies, positions and offsets.
     DOCS_ONLY

     Only documents are indexed: term frequencies and positions are omitted.

Java Code Examples for org.apache.lucene.index.IndexOptions

Example 4

Project: languagetool   File: EmptyLuceneIndexCreator.java View source code

6 votes

public static void main(String[] args) throws IOException {
  if (args.length != 1) {
    System.out.println("Usage: " + EmptyLuceneIndexCreator.class.getSimpleName() + " <indexPath>");
    System.exit(1);
  }
  Analyzer analyzer = new StandardAnalyzer();
  IndexWriterConfig config = new IndexWriterConfig(analyzer);
  Directory directory = FSDirectory.open(new File(args[0]).toPath());
  IndexWriter writer = new IndexWriter(directory, config);

  FieldType fieldType = new FieldType();
  fieldType.setIndexOptions(IndexOptions.DOCS);
  fieldType.setStored(true);
  Field countField = new Field("totalTokenCount", String.valueOf(0), fieldType);
  Document doc = new Document();
  doc.add(countField);
  writer.addDocument(doc);

  writer.close();
}

 

ES里，

first of all index_options & term_vectors are two totally different things. 
index_options are "options" for the index you are searching on, a 
datastructure that holds "terms" to document lists (posting lists). 
TermVectors are a datastructure that gives you the "terms" for a given 
document and in addition their position in the document as well as their 
start and end character offsets. Now the index (each field has such an 
index) holds a sorted list of terms and each term points to a posting list. 
these posting lists are a list of documents that contain the term. On the 
posting list you can also store information like frequencies (how often did 
term Y occur in document X -> useful for scoring) as well as "positions" 
(at which position did term Y occur in document X -> this is required fo 
phrase & span queries). 

if you have for instance a field that you only use for filtering you don't 
need freqs and postions so documents only will do the job. In an index the 
position information is the biggest piece of data usually aside stored 
fields. If you don't do phrase queries or spans you don't need them at all 
so safe the disk space and improve perf by only use docs and freqs. In 
previous version it wasn't possible to have only freqs but no positions 
(index_options supersede omit_term_frequencies_and_positions) so this is an 
improvement overall since the most common usecase might only need freqs but 
no positions. 

 

附上一些选项：
1：term_vector
TermVector.YES: Only store number of occurrences.
TermVector.WITH_POSITIONS: Store number of occurrence and positions of terms, but no offset.
TermVector.WITH_OFFSETS: Store number of occurrence and offsets of terms, but no positions.
TermVector.WITH_POSITIONS_OFFSETS:number of occurrence and positions , offsets of terms.
TermVector.NO:Don't store any term vector information.
2: index_options
Allows to set the indexing options, possible values are docs (only doc numbers are indexed), freqs (doc numbers and term frequencies), and positions (doc numbers, term frequencies and positions). Defaults to positions for analyzed fields, and to docs for not_analyzed fields. It is also possible to set it to offsets (doc numbers, term frequencies, positions and offsets).

 

参考：https://lucene.apache.org/core/4_1_0/core/org/apache/lucene/index/FieldInfo.IndexOptions.html

http://elasticsearch.cn/question/119