10.term level 查询

文章目录

1. term level查询总结
2. 样例
- 1 . exists query
- 2 . fuzzy query
- 3 . ids query
- 4 . prefix query
- 5 . range query
- 6 . regexp query
- 7 . term query
- 8 . terms query
- 9 . terms_set query
- 10. type query
- 11. wildcard query

1. term level查询总结

term level 查询不会再对query进行analysis分词处理，直接将query当做一个一个单词处理

1 . exists query: 这个是针对某个field是否存在的查询，只要被查询doc的该field的值不是null,就会放回对应的doc
2 . fuzzy query: 使用利文斯顿编辑距离来支持模糊查询和近似查询
3 . ids query: 使用多个doc的_id值进行查询
4 . prefix query: 查找有特定prefix的doc
5 . range query: 范围查找
6 . regexp query: 正则表达式查找
7 . term query: 查找某个field包含某个term的doc,不仅能用于keyword,number等类型,测试发现也能够在text类型当中使用
8 . terms query: 查找doc的某个field包含某几个term的doc,该doc的对应的field值需要包含一个或者多个就会被认为命中查询
9 . terms_set query: 查找doc的某个field包含某几个term的doc,该doc的对应的field值需要包含一定数量查询中提供的term_set才会被认为命中查询,这里的一定数量是可以设置的
10. type query: 因为type已经过期了，所以这个查询也过期了
11. wildcard query: 使用模式通配符查询

2. 样例

1 . exists query

GET /_search
{"query": {"exists": {"field": "user"}}
}

2 . fuzzy query

GET /_search
{"query": {"fuzzy": {"user": {"value": "ki"}}}
}GET /_search
{"query": {"fuzzy": {"user": {"value": "ki","fuzziness": "AUTO","max_expansions": 50,"prefix_length": 0,"transpositions": true,"rewrite": "constant_score"}}}
}

3 . ids query

GET /_search
{"query": {"ids" : {"values" : ["1", "4", "100"]}}
}

4 . prefix query

GET /_search
{"query": {"prefix": {"user": {"value": "ki"}}}
}

5 . range query

GET _search
{"query": {"range" : {"age" : {"gte" : 10,"lte" : 20,"boost" : 2.0}}}
}

6 . regexp query

GET /_search
{"query": {"regexp": {"user": {"value": "k.*y","flags" : "ALL","max_determinized_states": 10000,"rewrite": "constant_score"}}}
}

7 . term query

GET /_search
{"query": {"term": {"user": {"value": "Kimchy","boost": 1.0}}}
}

8 . terms query

PUT my_index
{"mappings" : {"properties" : {"color" : { "type" : "keyword" }}}
}PUT my_index/_doc/1
{"color":   ["blue", "green"]
}PUT my_index/_doc/2
{"color":   "blue"
}GET my_index/_search?pretty
{"query": {"terms": {"color" : {"index" : "my_index","id" : "2","path" : "color"}}}
}

9 . terms_set query

这个稍微复杂一些

PUT /job-candidates
{"mappings": {"properties": {"name": {"type": "keyword"},"programming_languages": {"type": "keyword"},"required_matches": {"type": "long"}}}
}PUT /job-candidates/_doc/1?refresh
{"name": "Jane Smith","programming_languages": ["c++", "java"],"required_matches": 2
}PUT /job-candidates/_doc/2?refresh
{"name": "Jason Response","programming_languages": ["java", "php"],"required_matches": 2
}GET /job-candidates/_search
{"query": {"terms_set": {"programming_languages": {"terms": ["c++", "java", "python"],"minimum_should_match_field": "required_matches" # 这个字段等于是动态的}}}
}上面的查询，只有doc 1会被查出来GET /job-candidates/_search
{"query": {"terms_set": {"programming_languages": {"terms": ["c++", "java", "python"],"minimum_should_match_script":{"lang":"painless","source":"2"}}}}
}也可以使用script操作

10. type query

11. wildcard query

GET /_search
{"query": {"wildcard": {"user": {"value": "ki*y","boost": 1.0,"rewrite": "constant_score"}}}
}

对应的如果是 kiy, kity, or kimchy都会被命中