索引架构
lucene索引基本组成结构 index、segment、document、field、term
index：就是一个目录
segment：段，一系列索引文件组成的抽象的该您
document：文档，可以在是一个网页一个或者多个document构成一个segment
field：类似数据库中的字段， 一个文档包含多个field, 比如一个网页包含： 标题、作者、内容。不同域的索引方式可以不一样
term： 索引的最小单位，是经过词法分析和语言处理后的字符串
Segment info. This contains metadata about a segment, such as the number of documents, what files it uses,
Field names. This contains the set of field names used in the index.
Stored Field values. This contains, for each document, a list of attribute-value pairs, where the attributes are field names. These are used to store auxiliary information about the document, such as its title, url, or an identifier to access a database. The set of stored fields are what is returned for each hit when searching. This is keyed by document number.
Term dictionary. A dictionary containing all of the terms used in all of the indexed fields of all of the documents. The dictionary also contains the number of documents which contain the term, and pointers to the term's frequency and proximity data.
Term Frequency data. For each term in the dictionary, the numbers of all the documents that contain that term, and the frequency of the term in that document, unless frequencies are omitted (IndexOptions.DOCS_ONLY)
Term Proximity data. For each term in the dictionary, the positions that the term occurs in each document. Note that this will not exist if all fields in all documents omit position data.
Normalization factors. For each field in each document, a value is stored that is multiplied into the score for hits on that field.
Term Vectors. For each field in each document, the term vector (sometimes called document vector) may be stored. A term vector consists of term text and term frequency. To add Term Vectors to your index see the Fieldconstructors
Per-document values. Like stored values, these are also keyed by document number, but are generally intended to be loaded into main memory for fast access. Whereas stored values are generally intended for summary results from searches, per-document values are useful for things like scoring factors.
Live documents. An optional file indicating which documents are live.
Point values. Optional pair of files, recording dimensionally indexed fields, to enable fast numeric range filtering and large numeric values like BigInteger and BigDecimal (1D) and geographic shape intersection (2D, 3D).
索引文件后缀和含义：
The following table summarizes the names and extensions of the files in Lucene:
名称 扩展名 说明
Segments Fil e segments_N 存储检查点
Lock File write.lock 写锁，防止不同IndexWriter 写同一个文件
Segment Info .si 存储段的meta信息
Compound File .cfs, .cfe 种后缀的文件存在也可不存在，只有IndexWriter “优化”过才会出现（将其他索引后缀文件合并，可以防止系统的文件句柄被消耗光）
Fields .fnm 域文件，存储field的信息
Field Index .fdx 指向 field data的指针
Field Data .fdt 域数据文件：包含文档中存储的域
Term Dictionary .tim The term dictionary, stores term info
Term Index .tip The index into the Term Dictionary
Frequencies .doc Contains the list of docs which contain each term along with frequency
Positions .pos Stores position information about where a term occurs in the index
Payloads .pay Stores additional per-position metadata information such as character offsets and user payloads
Norms .nvd, .nvm Encodes length and boost factors for docs and fields
Per-Document Values .dvd, .dvm Encodes additional scoring factors or other per-document information.
Term Vector Index .tvx Stores offset into the document data file
Term Vector Data .tvd Contains term vector data.
Live Documents .livInfo about what documents are live
Point values .dii, .dim Holds indexed points, if any
总结
Index –> Segments (segments.gen, segments_N) –> Field(fnm, fdx, fdt) –> Term (tvx, tvd, tvf)
参考：
https://lucene.apache.org/core/7_3_0/core/org/apache/lucene/codecs/lucene70/package-summary.html#package.description
https://blog.csdn.net/ghj1976/article/details/5586329
http://www.cnblogs.com/forfuture1978/archive/2009/12/14/1623599.html
