elasticsearch 增删改查
索引名称为：test
PUT http://192.168.12.137:9200/test/ { "setting":{ "number_of_shards":5, "number_of_replicas":1 }, "mappings":{ "person":{ "properties":{ "name":{ "type":"text" }, "age":{ "type":"integer" }, "sex":{ "type":"string" }, "birthday":{ "type":"date", "format":"yyyy-MM-dd HH:mm:ss || yyyy-MM-dd || epoch_millis" }, "introduce":{ "type":"text" } } } } }给文档person 新增数据
POST http://192.168.12.137:9200/test/person/ { "name":"jieke", "age":20 }POST http://192.168.12.137:9200/test/person/1 { "name":"pede", "age":20 }GET http://192.168.12.137:9201/test/_settingsGET http://192.168.12.137:9201/test,robot/_settingshttp://192.168.12.137:9201/_all/_settingsGET http://192.168.12.137:9200/test/person/1GET http://192.168.12.137:9200/test/person/_search?q=name:jieke只查询 name 字段的数据
GET http://192.168.12.137:9200/test/person/1?_source=namePOST http://localhost:9200/test/_search { "query":{ "match_all":{} } }POST http://localhost:9200/test/_search { "query":{ "match_all":{} } "from":1, "size":2 }# 排序 POST http://localhost:9200/test/_search { "query":{ "match":{ "name":"lrshuai" } } "sort":[ {"age":{"order":"desc"}} ] }# 统计个数 POST http://localhost:9200/test/_search { "aggs":{ "group_by_age":{ "terms":{ "field":"age" } }, "group_by_name":{ "terms":{ "field":"name" } } } } # stats POST http://localhost:9200/test/_search { "aggs":{ "group_by_age":{ "stats":{ "field":"age" } }, } } # 最小值 POST http://localhost:9200/test/_search { "aggs":{ "group_by_age":{ "min":{ "field":"age" } }, } }# 匹配name POST http://localhost:9200/test/_search { "query":{ "match":{ "name":"lrshuai" } } } # match_phrase 全部匹配，不进行分词 http://localhost:9200/test/_search { "query":{ "match_phrase":{ "introduce":"人见" } } } # slop 是quick dog 相隔的距离有多少。 # 通过设置一个像 50 或者 100 这样的高 slop 值, 你能够排除单词距离太远的文档， 但是也给予了那些单词临近的的文档更高的分数 http://localhost:9200/test/_search { "query": { "match_phrase": { "title": { "query": "quick dog", "slop": 50 } } } } # multi_match 多个字段匹配 POST http://localhost:9200/test/_search { "query":{ "multi_match":{ "query":"见", "fields":["name","introduce"] } } } # 语法查询 http://localhost:9200/test/_search { "query":{ "query_string":{ "query":"见 or 我" } } } # 语法查询指定字段 POST http://localhost:9200/test/_search { "query":{ "query_string":{ "query":"见 or 我", "fields":["name","introduce"] } } } # 字段完全相等的查询 POST http://localhost:9200/test/_search { "query":{ "term":{ "name":"lrshuai" } } } { "query":{ "range":{ "age":{ "gte":20, "lte":25 } } } } POST http://localhost:9200/test/_search { "query":{ "range" : { "create_time" : { "gt" : "2017-01-01 00:00:00", "lt" : "2017-12-07 00:00:00" } } } } # 多一个月 POST http://localhost:9200/test/_search { "query":{ "range" : { "create_time" : { "gt" : "2017-01-01 00:00:00", "lt" : "2017-12-07 00:00:00||+1M" } } } }should 满足其中一个就可以
POST http://localhost:9200/test/_search { "query":{ "bool":{ "should":[ { "match":{ "name":"tyro" } },{ "range":{ "age":{ "gt":20, "lte":25 } } } ] } } }POST http://localhost:9200/test/_search { "query":{ "bool":{ "filter":{ "term":{ "name":"rstyro" } } } } }# must 必须满足所有条件 POST http://localhost:9200/test/_search { "query":{ "bool":{ "must":[ { "match":{ "sex":"女" } }, { "range":{ "age":{ "lte":30 } } } ] } } } # 加上filter 过滤 POST http://localhost:9200/test/_search { "query":{ "bool":{ "must":[ { "match":{ "sex":"女" } } ], "filter":[ { "term":{ "introduce":"人" } } ] } } } # must_not 必须不满足所有条件 POST http://localhost:9200/test/_search { "query":{ "bool":{ "must_not":[ { "match":{ "sex":"女" } }, { "range":{ "age":{ "lte":20 } } } ] } } }{ "query": { "bool": { "must": { "match": { "content": { "query": "full text search", "operator": "and" } } }, "should": [ { "match": { "content": "Elasticsearch" }}, { "match": { "content": "Lucene" }} ] } } }GET /_search { "query": { "bool": { "must": { "match": { "content": { "query": "full text search", "operator": "and" } } }, "should": [ { "match": { "content": { "query": "Elasticsearch", "boost": 3 } }}, { "match": { "content": { "query": "Lucene", "boost": 2 } }} ] } } }{ "query": { "boosting": { "positive": { "match": { "content": "Elasticsearch" } }, "negative": { "match": { "content": "Lucene" } }, "negative_boost": 0.5 } } }它接受 positive 和 negative 查询。只有那些匹配 positive 查询的文档罗列出来，对于那些同时还匹配 negative 查询的文档将通过文档的原始 _score 与 negative_boost 相乘的方式降级后的结果。
为了达到效果， negative_boost 的值必须小于 1.0 。在这个示例中，所有包含负向词的文档评分 _score 都会减半。
PUT /my_index/my_type/1 { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } PUT /my_index/my_type/2 { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." }我们进行查询
{ "query": { "bool": { "should": [ { "match": { "title": "Brown fox" }}, { "match": { "body": "Brown fox" }} ] } } }但返回的结果：发现查询的结果是文档 1 的评分更高：
{ "hits": [ { "_id": "1", "_score": 0.14809652, "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } }, { "_id": "2", "_score": 0.09256032, "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } } ] }{ "query": { "dis_max": { "queries": [ { "match": { "title": "Brown fox" }}, { "match": { "body": "Brown fox" }} ] } } }{ "hits": [ { "_id": "2", "_score": 0.21509302, "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } }, { "_id": "1", "_score": 0.12713557, "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } } ] }multi_match 多匹配查询的类型有多种，其中的三种恰巧与 了解我们的数据 中介绍的三个场景对应，即： best_fields 、 most_fields 和 cross_fields （最佳字段、多数字段、跨字段）
bool查询
{ "query": { "bool": { "should": [ { "match": { "street": "Poland Street W1V" }}, { "match": { "city": "Poland Street W1V" }}, { "match": { "country": "Poland Street W1V" }}, { "match": { "postcode": "Poland Street W1V" }} ] } } }换成multi_match 查询
{ "query": { "multi_match": { "query": "Poland Street W1V", "type": "most_fields", "fields": [ "street", "city", "country", "postcode" ] } } }修改文档person id为1 的name属性为 ‘杰克’
POST http://192.168.12.137:9201/test/person/1/_update { "doc":{ "name":"杰克" } }POST http://192.168.12.137:9201/test/person/1/_update { "script":{ "lang":"painless", "inline":"ctx._source.age += 10" } } //或者这样的 POST http://192.168.12.137:9201/test/person/1/_update { "script":{ "lang":"painless", "inline":"ctx._source.age =params.age" "params":{ "age":30 } } }删除test 索引
DELETE http://192.168.12.137:9201/testid 为1 的数据
DELETE http://192.168.12.137:9201/test/person/1POST twitter/_delete_by_query { "query": { "match": { "message": "some message" } } }https://www.elastic.co/guide/en/elasticsearch/reference/5.6/docs-delete-by-query.html#docs-delete-by-query
删除 person 文档里的field 字段
POST http://192.168.12.137:9201/test/person/_update { "script":{ "lang":"painless", "inline":"ctx._source.remove(\"field\")" } }在创建索引的时候，可以预先定义字段的类型与相关属性，分为静态映射和动态映射
每个字段可添加的属性有：
| 属性 | 说明 | 适用类型 |
|---|---|---|
| store | 可选值有：yes、no ,设为yes就是存储，no 不存储 | all |
| index | string ,其他类型只能设置 not_analyzed、no | |
| null_value | 当字段为空时，可以为它设置一个默认值：比如 “null_value”:”NAN” | all |
| boost | 字段的权重。默认值：1.0 | all |
| index_analyzer | 设置一个索引时用的分析器 | all |
| search_analyzer | 设置一个搜索时用的分析器 | all |
| analyzer | 可以设置索引和搜索时用到的分析器，默认使用 standard 分析器，除外，你还可以使用 whitespace、simple、english 这3个内置的分析器 | all |
| include_in_all | 它的作用是每个字段默认都搜索到，如果你不想让某个字段被搜索到，那么将这个字段设置为false 即可。默认值:true | all |
| index_name | 定义字段的名称，默认值是字段本身的名字 | all |
| norms | 作用是根据各种规范化因素去计算权值，这样方便查询，在analyzed 定义字段里，值为true、not-analyzed 是 false。 | all |
PUT http://192.168.12.137:9201/person { "setting":{ "number_of_shards":5, "number_of_replicas":1 }, "mappings":{ "man":{ "properties":{ "name":{ "type":"string", "index":"not_analyzed" }, "age":{ "type":"integer" }, "sex":{ "type":"string" }, "money":{ "type":"double" } } } } }GET http://192.168.12.137:9201/person/_mappingDELETE http://192.168.12.137:9201/person/man/_mapping参考文献：https://www.elastic.co/guide/cn/elasticsearch/guide/current/index.html
文章来源: Elasticsearch 的语法