lucene Index Store TermVector 说明

Posted 2020-09-06 将者，智、信、仁、勇、严也。

最新的lucene 3.0的field是这样的:

Field options for indexing
Index.ANALYZED – use the analyzer to break the Field’s value into a stream of separate tokens and make each token searchable.
Index.NOT_ANALYZED – do index the field, but do not analyze the String. Instead, treat the Field’s entire value as a single token and make that token searchable. 
Index.ANALYZED_NO_NORMS – an advanced variant of Index.ANALYZED which does not store norms information in the index. 
Index.NOT_ANALYZED_NO_NORMS – just like , but also do not store Norms.
Index.NO – don’t make this field’s value available for searching at all.

Field options for storing fields
Store.YES — store the value. When the value is stored, the original String in its entirety is recorded in the index and may be retrieved by an IndexReader.
Store.NO – do not store the value. This is often used along with Index.ANALYZED to index a large text field that doesn’t need to be retrieved in its original form.

Field options for term vectors
TermVector.YES – record the unique terms that occurred, and their counts, in each document, but do not store any positions or offsets information.
TermVector.WITH_POSITIONS – record the unique terms and their counts, and also the positions of each occurrence of every term, but no offsets.
TermVector.WITH_OFFSETS – record the unique terms and their counts, with the offsets (start & end character position) of each occurrence of every term, but no positions.
TermVector.WITH_POSITIONS_OFFSETS – store unique terms and their counts, along with positions and offsets.
TermVector.NO – do not store any term vector information.
If Index.NO is specified for a field, then you must also specify TermVector.NO.

具一些例子来说明这些怎么用
Index                   Store  TermVector                                Example usage 
NOT_ANALYZED     YES         NO                                        Identifiers (file names, primary keys),
                                                                                         Telephone and Social Security
                                                                                         numbers, URLs, personal names, Dates
ANALYZED              YES     WITH_POSITIONS_OFFSETS    Document title, document abstract
ANALYZED              NO      WITH_POSITIONS_OFFSETS    Document body
NO                         YES        NO                                        Document type, database primary key
NOT_ANALYZED     NO         NO                                         Hidden keywords

When Lucene builds the inverted index, by default it stores all necessary information to implement the Vector Space model. This model requires the count of every term that occurred in the document, as well as the positions of each occurrence (needed for phrase searches).
You can tell Lucene to skip indexing the term frequency and positions by calling:
Field.setOmitTermFreqAndPositions(true)

 

摘自：http://www.cnblogs.com/fxjwind/archive/2011/07/04/2097705.html