? 若在传统DBMS 关系型数据库中查询海量数据,特别是模糊查询,一般我们都是使用like %查询的值%,但这样会导致无法应用索引,从而形成全表扫描效率低下,即使是在有索引的字段精确值查找,面对海量数据,效率也是相对较低的,所以目前一般的互联网公司或大型公司,若要查询海量数据,最好的办法就是使用搜索引擎,目前比较主流的搜索引擎框架就是:Elasticsearch,故今天我这里总结了Elasticsearch必知必会的干货知识一:ES索引文档的CRUD,后面陆续还会有其它干货知识分享,敬请期待。
ES索引文档的CRUD(6.X与7.X有区别,6.X中支持一个index创建多个type,而7.X中及以上只支持1个固定的type,即:_doc,API用法上也稍有不同):
Create创建索引文档【POST index/type/id可选,如果index、type、id已存在则重建索引文档(先删除后创建索引文档,与Put index/type/id 原理相同),如果在指定id情况下需要限制自动更新,则可以使用:index/type/id?op_type=create 或 index/type/id/_create,指明操作类型为创建,这样当存在的记录的情况下会报错】
POST demo_users/_doc  或  demo_users/_doc/2vJKsm8BriJODA6s9GbQ/_create
Request Body:
{
"userId":1,
"username":"张三",
"role":"administrator",
"enabled":true,
"createdDate":"2020-01-01T12:00:00"
}
Response Body:
{
"_index": "demo_users",
"_type": "_doc",
"_id": "2vJKsm8BriJODA6s9GbQ",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}Get获取索引文档【Get index/type/id】
Get demo_users/_doc/123
Response Body:
{
"_index": "demo_users",
"_type": "_doc",
"_id": "123",
"_version": 1,
"found": true,
"_source": {
"userId": 1,
"username": "张三",
"role": "administrator",
"enabled": true,
"createdDate": "2020-01-01T12:00:00"
}
}Index Put重建索引文档【PUT index/type/id 或 index/type/id?op_type=index,id必传,如果id不存在文档则创建文档,否则先删除原有id文档后再重新创建文档,version加1】
Put/POST demo_users/_doc/123 或 demo_users/_doc/123?op_type=index
Request Body:
{
"userId":1,
"username":"张三",
"role":"administrator",
"enabled":true,
"createdDate":"2020-01-01T12:00:00",
"remark":"仅演示"
}
Response Body:
{
"_index": "demo_users",
"_type": "_doc",
"_id": "123",
"_version": 4,
"result": "updated",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 10,
"_primary_term": 1
}Update更新索引文档【POST index/type/id/_update 请求体必需是{"doc":{具体的文档JSON}},如果指定的键字段已存在则更新,如果指定的键字段不存在则附加新的键值对,支持多层级嵌套,多次请求,如果有字段值有更新则version加1,否则提示更新0条 】
POST demo_users/_doc/123/_update
Request Body:
{
  "doc": {
    "userId": 1,
    "username": "张三",
    "role": "administrator",
    "enabled": true,
    "createdDate": "2020-01-01T12:00:00",
    "remark": "仅演示POST更新5",
    "updatedDate": "2020-01-17T15:30:00"
  }
}
Response Body:
{
"_index": "demo_users",
"_type": "_doc",
"_id": "123",
"_version": 26,
"result": "updated",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 35,
"_primary_term": 1
}Delete删除索引文档【DELETE index/type/id】
DELETE demo_users/_doc/123
Response Body:
{
"_index": "demo_users",
"_type": "_doc",
"_id": "123",
"_version": 2,
"result": "deleted",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 39,
"_primary_term": 1
}Bulk批量操作文档【POST _bulk 或 index/_bulk 或 index/type/_bulk 一次请求支持进行多个索引、多个type的多种不同的CRUD操作,如果操作中有某个出现错误不会影响其它操作;】
POST _bulk
Request Body:(注意最后还得多一个换行,因为ES是根据换行符来识别多条命令的,如果缺少最后一条换行则会报错,注意请求体非标准的JSON,每行才是一个JSON,整体顶多可看成是\n区分的JSON对象数组)
{ "index" : { "_index" : "demo_users_test", "_type" : "_doc", "_id" : "1" } }
{ "bulk_field1" : "测试创建index" }
{ "delete" : { "_index" : "demo_users", "_type" : "_doc", "_id" : "123" } }
{ "create" : { "_index" : "demo_users", "_type" : "_doc", "_id" : "2" } }
{ "bulk_field2" : "测试创建index2" }
{ "update" : { "_index" : "demo_users_test","_type" : "_doc","_id" : "1" } }
{ "doc": {"bulk_field1" : "测试创建index1","bulk_field2" : "测试创建index2"} }
Response Body:
{
    "took": 162,
    "errors": true,
    "items": [
        {
            "index": {
                "_index": "demo_users_test",
                "_type": "_doc",
                "_id": "1",
                "_version": 8,
                "result": "updated",
                "_shards": {
                    "total": 2,
                    "successful": 2,
                    "failed": 0
                },
                "_seq_no": 7,
                "_primary_term": 1,
                "status": 200
            }
        },
        {
            "delete": {
                "_index": "demo_users",
                "_type": "_doc",
                "_id": "123",
                "_version": 2,
                "result": "not_found",
                "_shards": {
                    "total": 2,
                    "successful": 2,
                    "failed": 0
                },
                "_seq_no": 44,
                "_primary_term": 1,
                "status": 404
            }
        },
        {
            "create": {
                "_index": "demo_users",
                "_type": "_doc",
                "_id": "2",
                "status": 409,
                "error": {
                    "type": "version_conflict_engine_exception",
                    "reason": "[_doc][2]: version conflict, document already exists (current version [1])",
                    "index_uuid": "u7WE286CQnGqhHeuwW7oyw",
                    "shard": "2",
                    "index": "demo_users"
                }
            }
        },
        {
            "update": {
                "_index": "demo_users_test",
                "_type": "_doc",
                "_id": "1",
                "_version": 9,
                "result": "updated",
                "_shards": {
                    "total": 2,
                    "successful": 2,
                    "failed": 0
                },
                "_seq_no": 8,
                "_primary_term": 1,
                "status": 200
            }
        }
    ]
}mGet【POST _mget 或 index/_mget 或 index/type/_mget ,如果指定了index或type,则请求报文中则无需再指明index或type,可以通过_source指明要查询的include以及要排除exclude的字段】
POST _mget
Request Body:
{
  "docs": [
    {
      "_index": "demo_users",
      "_type": "_doc",
      "_id": "12345"
    },
    {
      "_index": "demo_users",
      "_type": "_doc",
      "_id": "1234567",
      "_source": [
        "userId",
        "username",
        "role"
      ]
    },
    {
      "_index": "demo_users",
      "_type": "_doc",
      "_id": "1234",
      "_source": {
        "include": [
          "userId",
          "username"
        ],
        "exclude": [
          "role"
        ]
      }
    }
  ]
}
Response Body:
{
    "docs":[
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"12345",
            "_version":1,
            "found":true,
            "_source":{
                "userId":1,
                "username":"张三",
                "role":"administrator",
                "enabled":true,
                "createdDate":"2020-01-01T12:00:00"
            }
        },
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"1234567",
            "_version":7,
            "found":true,
            "_source":{
                "role":"administrator",
                "userId":1,
                "username":"张三"
            }
        },
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"1234",
            "_version":1,
            "found":true,
            "_source":{
                "userId":1,
                "username":"张三"
            }
        }
    ]
}
POST demo_users/_doc/_mget
Request Body:
{
  "ids": [
    "1234",
    "12345",
    "123457"
  ]
}
Response Body:
{
    "docs":[
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"1234",
            "_version":1,
            "found":true,
            "_source":{
                "userId":1,
                "username":"张三",
                "role":"administrator",
                "enabled":true,
                "createdDate":"2020-01-01T12:00:00",
                "remark":"仅演示"
            }
        },
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"12345",
            "_version":1,
            "found":true,
            "_source":{
                "userId":1,
                "username":"张三",
                "role":"administrator",
                "enabled":true,
                "createdDate":"2020-01-01T12:00:00"
            }
        },
        {
            "_index":"demo_users",
            "_type":"_doc",
            "_id":"123457",
            "found":false
        }
    ]
}_update_by_query根据查询条件更新匹配到的索引文档的指定字段【POST index/_update_by_query 请求体写查询条件以及更新的字段,更新字段这里采用了painless脚本进行灵活更新】
POST demo_users/_update_by_query
Request Body:(意思是查询role=administrator【可能大家看到keyword,这是因为role字段为text类型,无法直接匹配,需要借助于子字段role.keyword,如果有不理解后面会有简要说明】,更新role为poweruser、remark为remark+采用_update_by_query更新)
{
    "script":{ "source":"ctx._source.role=params.role;ctx._source.remark=ctx._source.remark+params.remark",
        "lang":"painless",
        "params":{
            "role":"poweruser",
            "remark":"采用_update_by_query更新"
        }
    },
    "query":{
        "term":{
            "role.keyword":"administrator"
        }
    }
}
painless写法请具体参考:painless语法教程
Response Body:
{
"took": 114,
"timed_out": false,
"total": 6,
"updated": 6,
"deleted": 0,
"batches": 1,
"version_conflicts": 0,
"noops": 0,
"retries": {
"bulk": 0,
"search": 0
},
"throttled_millis": 0,
"requests_per_second": -1,
"throttled_until_millis": 0,
"failures": [ ]
}_delete_by_query根据查询条件删除匹配到的索引文档【 POST index/_delete_by_query 请求体写查询匹配条件】
POST demo_users/_delete_by_query
Request Body:(意思是查询enabled=false)
{
  "query": {
    "match": {
      "enabled": false
    }
  }
}
Response Body:
   {
           "took":29,
           "timed_out":false,
           "total":3,
           "deleted":3,
           "batches":1,
           "version_conflicts":0,
           "noops":0,
           "retries":{
               "bulk":0,
               "search":0
           },
           "throttled_millis":0,
           "requests_per_second":-1,
           "throttled_until_millis":0,
           "failures":[
           ]
      }search查询
URL GET查询(GET index/_search?q=query_string语法,注意中文内容默认分词器是一个汉字拆分成一个term)
A.Term Query:【即分词片段(词条)查询,注意这里讲的包含是指与分词片段匹配】
GET /demo_users/_search?q=role:poweruser //指定字段查询,即:字段包含查询的值
GET /demo_users/_search?q=poweruser //泛查询(没有指定查询的字段),即查询文档中所有字段包含poweruser的值,只要有一个字段符合,那么该文档将会被返回
B.Phrase Query【即分组查询】
操作符有:AND / OR  / NOT 或者表示为: && / || / ! 
+表示must -表示must_not 例如:field:(+a -b)意为field中必需包含a但不能包含b
GET /demo_users/_search?q=remark:(POST test) 
GET /demo_users/_search?q=remark:(POST OR test) 
GET /demo_users/_search?q=remark:"POST test" 
//分组查询,即:查询remark中包含POST 或 test的文档记录
GET /demo_users/_search?q=remark:(test AND POST) //remark同时包含test与POST
GET /demo_users/_search?q=remark:(test NOT POST) //remark包含test但不包含POST
C.范围查询
区间表示:[]闭区间,{}开区间
如:year:[2019 TO 2020] 或 {2019 TO 2020} 或 {2019 TO 2020] 或 [* TO 2020]
算数符号
year:>2019 或 (>2012 && <=2020) 或 (+>=2012 +<=2020)
GET /demo_users/_search?q=userId:>123 //查询userId字段大于123的文档记录
D.通配符查询
?表示匹配任意1个字符,*表示匹配0或多个字符 例如:role:power* , role:use?
GET /demo_users/_search?q=role:power* //查询role字段前面是power,后面可以是0或多个其它任意字符。
可使用正则表达式,如:username:张三\d+
可使用近似查询偏移量(slop)提高查询匹配结果【使用~N,N表示偏移量】
GET /demo_users/_search?q=remark:tett~1 //查询remark中包含test的文档,但实际写成了tett,故使用~1偏移近似查询,可以获得test的查询结果
GET /demo_users/_search?q=remark:"i like shenzhen"~2 //查询i like shenzhen但实际remark字段中值为:i like hubei and shenzhen,比查询值多了 hubei and,这里使用~2指定可偏移相隔2个term(这里即两个单词),最终也是可以查询出结果
DSL POST查询(POST index/_search)
POST demo_users/_search
Request Body:
{
    "query":{
        "bool":{
            "must":[
                {
                    "term":{
                        "enabled":"true"  #查询enabled=true
                    }
                },
                {
                    "term":{
                        "role.keyword":"poweruser" #且role=poweruser
                    }
                },
                {
                    "query_string":{
                        "default_field":"username.keyword",
                        "query":"张三" #且 username 包含张三
                    }
                }
            ],
            "must_not":[
            ],
            "should":[
            ]
        }
    },
    "from":0,
    "size":1000,
    "sort":[
        {
            "createdDate":"desc"  #根据createdDate倒序
        }
    ],
    "_source":{ #指明返回的字段,includes需返回字段,excludes不需要返回字段
        "includes":[
            "role",
            "username",
            "userId",
            "remark"
        ],
        "excludes":[
        ]
    }
}
具体用法可参见:
【Elasticsearch】query_string的各种用法
Elasticsearch中 match、match_phrase、query_string和term的区别
Indices APIs:负责索引Index的创建(create)、删除(delete)、获取(get)、索引存在(exist)等操作。
Document APIs:负责索引文档的创建(index)、删除(delete)、获取(get)等操作。
Search APIs:负责索引文档的search(查询),Document APIS根据doc_id进行查询,Search APIs]根据条件查询。
Aggregations:负责针对索引的文档各维度的聚合(Aggregation)。
cat APIs:负责查询索引相关的各类信息查询。
Cluster APIs:负责集群相关的各类信息查询。
Elasticsearch必知必会的干货知识一:ES索引文档的CRUD
原文:https://www.cnblogs.com/zuowj/p/12209702.html