Encodes the five per-document value types (Numeric,Binary,Sorted,SortedSet,SortedNumeric) with these strategies:

NUMERIC:

• Delta-compressed: per-document integers written as deltas from the minimum value, compressed with bitpacking. For more information, see DirectWriter.
• Table-compressed: when the number of unique values is very small (< 256), and when there are unused "gaps" in the range of values used (such as SmallFloat), a lookup table is written instead. Each per-document entry is instead the ordinal to this table, and those ordinals are compressed with bitpacking (DirectWriter).
• GCD-compressed: when all numbers share a common divisor, such as dates, the greatest common denominator (GCD) is computed, and quotients are stored using Delta-compressed Numerics.
• Monotonic-compressed: when all numbers are monotonically increasing offsets, they are written as blocks of bitpacked integers, encoding the deviation from the expected delta.
• Const-compressed: when there is only one possible non-missing value, only the missing bitset is encoded.
• Sparse-compressed: only documents with a value are stored, and lookups are performed using binary search.

BINARY:

• Fixed-width Binary: one large concatenated byte[] is written, along with the fixed length. Each document's value can be addressed directly with multiplication (docID * length).
• Variable-width Binary: one large concatenated byte[] is written, along with end addresses for each document. The addresses are written as Monotonic-compressed numerics.
• Prefix-compressed Binary: values are written in chunks of 16, with the first value written completely and other values sharing prefixes. chunk addresses are written as Monotonic-compressed numerics. A reverse lookup index is written from a portion of every 1024th term.

SORTED:

• Sorted: a mapping of ordinals to deduplicated terms is written as Binary, along with the per-document ordinals written using one of the numeric strategies above.

SORTED_SET:

• Single: if all documents have 0 or 1 value, then data are written like SORTED.
• SortedSet table: when there are few unique sets of values (< 256) then each set is assigned an id, a lookup table is written and the mapping from document to set id is written using the numeric strategies above.
• SortedSet: a mapping of ordinals to deduplicated terms is written as Binary, an ordinal list and per-document index into this list are written using the numeric strategies above.

SORTED_NUMERIC:

• Single: if all documents have 0 or 1 value, then data are written like NUMERIC.
• SortedSet table: when there are few unique sets of values (< 256) then each set is assigned an id, a lookup table is written and the mapping from document to set id is written using the numeric strategies above.
• SortedNumeric: a value list and per-document index into this list are written using the numeric strategies above.

Files:

1. .dvd: DocValues data
2. .dvm: DocValues metadata

转自：http://lucene.apache.org/core/6_4_2/core/org/apache/lucene/codecs/lucene54/Lucene54DocValuesFormat.html

可以看到占用空间非常小！！！

du -sm elasticsearch/nodes/0/indices/hec_test2/0/index/*
299     elasticsearch/nodes/0/indices/hec_test2/0/index/_e.fdt
1       elasticsearch/nodes/0/indices/hec_test2/0/index/_e.fdx
1       elasticsearch/nodes/0/indices/hec_test2/0/index/_e.fnm
148     elasticsearch/nodes/0/indices/hec_test2/0/index/_e_Lucene50_0.doc
130     elasticsearch/nodes/0/indices/hec_test2/0/index/_e_Lucene50_0.tim
5       elasticsearch/nodes/0/indices/hec_test2/0/index/_e_Lucene50_0.tip
1       elasticsearch/nodes/0/indices/hec_test2/0/index/_e_Lucene54_0.dvd
1       elasticsearch/nodes/0/indices/hec_test2/0/index/_e_Lucene54_0.dvm
1       elasticsearch/nodes/0/indices/hec_test2/0/index/_e.si
1       elasticsearch/nodes/0/indices/hec_test2/0/index/segments_7
0       elasticsearch/nodes/0/indices/hec_test2/0/index/write.lock

本文转自张昺华-sky博客园博客，原文链接：http://www.cnblogs.com/bonelee/p/6669414.html，如需转载请自行联系原作者