match查询会将查询词分词，然后对分词的结果进行term查询。
然后默认是将每个分词term查询之后的结果求交集，所以只要分词的结果能够命中，某条数据就可以被查询出来，而分词是在新建索引时指定的，只有text类型的数据才能设置分词策略。
新建索引，并指定分词策略：
PUT mail_test3 { "settings": { "index": { "refresh_interval": "30s", "number_of_shards": "1", "number_of_replicas": "0" } }, "mappings": { "default": { "_all": { "enabled": false }, "_source": { "enabled": true }, "properties": { "addressTude": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart", "copy_to": [ "commonText" ], "fielddata": true }, "captureTime": { "type": "long" }, "commonText": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart", "fielddata": true }, "commonNum":{ "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart", "fielddata": true }, "imsi": { "type": "keyword", "copy_to": ["commonNum"] }, "mailFrom": { "type": "keyword", "copy_to": ["commonText"] }, "mailSubject": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart", "copy_to": [ "commonText" ] }, "mcc": { "type": "integer", "copy_to": ["commonNum"] }, "rcptTo": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart", "copy_to": ["commonText"] }, "userName": { "type": "keyword", "copy_to": ["commonText"] }, "uuid": { "type": "keyword" } } } } }analyzer 指的是在建索引时的分词策略，search_analyzer 指的是在查询时的分词策略。ik分词器还有一种ik_smart 的分词策略，可以比较两种分词策略的差别：
ik_smart分词策略：
GET mail_test3/_analyze { "analyzer": "ik_smart", "text": "湖南省湘潭市江山路96号-11-8" }结果：
{ "tokens": [ { "token": "湖南省", "start_offset": 0, "end_offset": 3, "type": "CN_WORD", "position": 0 }, { "token": "湘潭市", "start_offset": 3, "end_offset": 6, "type": "CN_WORD", "position": 1 }, { "token": "江", "start_offset": 6, "end_offset": 7, "type": "CN_CHAR", "position": 2 }, { "token": "山路", "start_offset": 7, "end_offset": 9, "type": "CN_WORD", "position": 3 }, { "token": "96号", "start_offset": 9, "end_offset": 12, "type": "TYPE_CQUAN", "position": 4 }, { "token": "11-8", "start_offset": 13, "end_offset": 17, "type": "LETTER", "position": 5 } ] }ik_max_word分词策略：
GET mail_test1/_analyze { "analyzer": "ik_max_word", "text": "湖南省湘潭市江山路96号-11-8" }分词结果：
{ "tokens": [ { "token": "湖南省", "start_offset": 0, "end_offset": 3, "type": "CN_WORD", "position": 0 }, { "token": "湖南", "start_offset": 0, "end_offset": 2, "type": "CN_WORD", "position": 1 }, { "token": "省", "start_offset": 2, "end_offset": 3, "type": "CN_CHAR", "position": 2 }, { "token": "湘潭市", "start_offset": 3, "end_offset": 6, "type": "CN_WORD", "position": 3 }, { "token": "湘潭", "start_offset": 3, "end_offset": 5, "type": "CN_WORD", "position": 4 }, { "token": "市", "start_offset": 5, "end_offset": 6, "type": "CN_CHAR", "position": 5 }, { "token": "江山", "start_offset": 6, "end_offset": 8, "type": "CN_WORD", "position": 6 }, { "token": "山路", "start_offset": 7, "end_offset": 9, "type": "CN_WORD", "position": 7 }, { "token": "96", "start_offset": 9, "end_offset": 11, "type": "ARABIC", "position": 8 }, { "token": "号", "start_offset": 11, "end_offset": 12, "type": "COUNT", "position": 9 }, { "token": "11-8", "start_offset": 13, "end_offset": 17, "type": "LETTER", "position": 10 }, { "token": "11", "start_offset": 13, "end_offset": 15, "type": "ARABIC", "position": 11 }, { "token": "8", "start_offset": 16, "end_offset": 17, "type": "ARABIC", "position": 12 } ] }ik_max_word分词器的分词结果更多，分词的粒度更细，但是ik_smart的分词结果粒度更粗，一般的策略是建立索引使用ik_max_word，查询时使用ik_smart，这样就能尽可能多的查到结果，而且上文提到，match查询最终是转化为term查询，因此只要某个分词结果命中，结果中就会有该条数据。
如果对搜索结果的精度较高，可以在查询中加入operator参数，然后让分词结果的每个term查询结果之间求交集，这样能尽可能地提高精度。
这里的operator设置为or和and的差别较大，可以测试进行比较：
GET mail_test3/_search { "query": { "match": { "commonText": { "query": "湖北省宜昌市天台东二街", "operator": "and" } } } }