PUT /zoo/product/1 { "name":"monkey", "age":10, "content":"xiao small but ke ai" } PUT /zoo/product/2 { "name":"monkey", "age":13, "content":"xiao small but very big" } PUT /zoo/product/3 { "name":"dog", "age":13, "content":"xiao big but very small" } PUT /zoo/product/4 { "name":"cat", "age":18, "content":"xiao big but very small" } PUT /zoo/product/5 { "name":"tig", "age":30, "content":"xiao big but very big" }
2.搜索zoo下面product的所有document
GET /zoo/product/_search
took:耗费了几毫秒
timed_out:是否超时,这里是没有
_shards:数据拆成了5个分片,所以对于搜索请求,会打到所有的primary shard(或者是它的某个replica shard也可以)
hits.total:查询结果的数量,3个document
hits.max_score:score的含义,就是document对于一个search的相关度的匹配分数,越相关,就越匹配,分数也高
hits.hits:包含了匹配搜索的document的详细数据
3.查询所有动物
GET /zoo/product/_search { "query": { "match_all": {} } }
4.查询包含big的内容,并且按照age降序(desc是降序,asc是升序)
GET /zoo/product/_search { "query": { "match": { "content": "big" } }, "sort": [ { "age": { "order": "desc" } } ] }
5.从0下标开始查询出2包含big的动物
GET /zoo/product/_search { "query": { "match": { "content": "big" } }, "size": 2, "from": 0 }
6.查询出来的数据只要age和content属性
GET /zoo/product/_search { "_source": ["age","content"] }
7.查询出包含big but整段短语
GET /zoo/product/_search { "query": { "match_phrase": { "content": "big but" } } }
8.查询出来的数据进行高亮处理
GET /zoo/product/_search { "query": { "match": { "content": "big but" } }, "highlight": { "fields": { "content": {} } } }
PUT /zoo/product/1 { "name":"monkey", "age":10, "content":"xiao small but ke ai" } PUT /zoo/product/2 { "name":"monkey", "age":13, "content":"xiao small but very big" } PUT /zoo/product/3 { "name":"dog", "age":13, "content":"xiao big but very small" } PUT /zoo/product/4 { "name":"cat", "age":18, "content":"xiao big but very small" } PUT /zoo/product/5 { "name":"tig", "age":30, "content":"xiao big but very big" }
2.搜索zoo下面product的所有document
GET /zoo/product/_search
took:耗费了几毫秒
timed_out:是否超时,这里是没有
_shards:数据拆成了5个分片,所以对于搜索请求,会打到所有的primary shard(或者是它的某个replica shard也可以)
hits.total:查询结果的数量,3个document
hits.max_score:score的含义,就是document对于一个search的相关度的匹配分数,越相关,就越匹配,分数也高
hits.hits:包含了匹配搜索的document的详细数据
3.查询所有动物
GET /zoo/product/_search { "query": { "match_all": {} } }
4.查询包含big的内容,并且按照age降序(desc是降序,asc是升序)
GET /zoo/product/_search { "query": { "match": { "content": "big" } }, "sort": [ { "age": { "order": "desc" } } ] }
5.从0下标开始查询出2包含big的动物
GET /zoo/product/_search { "query": { "match": { "content": "big" } }, "size": 2, "from": 0 }
6.查询出来的数据只要age和content属性
GET /zoo/product/_search { "_source": ["age","content"] }
7.查询出包含big but整段短语
GET /zoo/product/_search { "query": { "match_phrase": { "content": "big but" } } }
8.查询出来的数据进行高亮处理
GET /zoo/product/_search { "query": { "match": { "content": "big but" } }, "highlight": { "fields": { "content": {} } } }