FieldSelectorResult:枚舉，分別為
LOAD Document#getFieldable和Document#getField不會返回null
LAZY_LOAD :Lazy的Field意味著在搜索結果里這個Field的值缺省是不讀取的，只有當你真正對這個Field取值的時候才會去取。所以如果你要對它取值，你得保證IndexReader還沒有close。 Document#getField不能使用，只能使用Document#getFieldable
NO_LOAD Document#getField和Document#getFieldable都返回null，Document#add不被調用。
LOAD_AND_BREAK 類似LOAD，Document#getField和Document#getFieldable都可用，但返回后就結束，Document可能沒有完整的field的Set，參考LoadFirstFieldSelector 。
LOAD_FOR_MERGE 類似LOAD，但不壓縮任何數據。只被SegmentMerger的一個FieldSelector匿名內嵌實現類使用。Document#getField和Document#getFieldable可返回null.
SIZE 返回Field的size而不是value. Size表示存儲這個field需要的bytes數，string數值使用2*chars。size被存儲為a binary value，表現為as an int in a byte[]，with the higher order byte first in [0]。
SIZE_AND_BREAK 類似SIZE，但立刻break from the field loading loop, i.e. stop loading further fields, after the size is loaded
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Field中三大enum: Store Index和TermVector：
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Store.COMPRESS Store the original field value in the index in a compressed form. This is useful for long documents and for binary valued fields.壓縮存儲；
Store.YES Store the original field value in the index. This is useful for short texts like a document's title which should be displayed with the results. The value is stored in its original form, i.e. no analyzer is used before it is stored. 索引文件本來只存儲索引數據, 此設計將原文內容直接也存儲在索引文件中，如文檔的標題。
Store.NO Do not store the field value in the index. 原文不存儲在索引文件中，搜索結果命中后，再根據其他附加屬性如文件的Path，數據庫的主鍵等，重新連接打開原文，適合原文內容較大的情況。
決定了Field對象的 this.isStored 和 this.isCompressed
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Index.NO Do not index the field value. This field can thus not be searched, but one can still access its contents provided it is Field.Store stored. 不進行索引，存放不能被搜索的內容如文檔的一些附加屬性如文檔類型, URL等。
Index.TOKENIZED Index the field's value so it can be searched. An Analyzer will be used to tokenize and possibly further normalize the text before its terms will be stored in the index. This is useful for common text. 分詞索引
Index.UN_TOKENIZED Index the field's value without using an Analyzer, so it can be searched. As no analyzer is used the value will be stored as a single term. This is useful for unique Ids like product numbers. 不分詞進行索引，如作者名，日期等，Rod Johnson本身為一單詞，不再需要分詞。
Index.NO_NORMS 不分詞，建索引。norms是什么???字段值???。但是Field的值不像通常那樣被保存，而是只取一個byte，這樣節約存儲空間???? Index the field's value without an Analyzer, and disable the storing of norms. No norms means that index-time boosting and field length normalization will be disabled. The benefit is less memory usage as norms take up one byte per indexed field for every document in the index.Note that once you index a given field <i>with</i> norms enabled, disabling norms will have no effect. In other words, for NO_NORMS to have the above described effect on a field, all instances of that field must be indexed with NO_NORMS from the beginning.
決定了Field對象的 this.isIndexed this.isTokenized this.omitNorms
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Lucene 1.4.3新增的：
TermVector.NO Do not store term vectors. 不保存term vectors
TermVector.YES Store the term vectors of each document. A term vector is a list of the document's terms and their number of occurences in that document. 保存term vectors。
TermVector.WITH_POSITIONS Store the term vector + token position information 保存term vectors。（保存值和token位置信息）
TermVector.WITH_OFFSETS Store the term vector + Token offset information
TermVector.WITH_POSITIONS_OFFSETS Store the term vector + Token position and offset information 保存term vectors。（保存值和Token的offset）
決定了Field對象的this.storeTermVector this.storePositionWithTermVector this.storeOffsetWithTermVector