• 谷粒商城分布式高级(二)—— ElasticSearch全文检索


    一、ElasticSearch-全文检索

    1、简介

    https://www.elastic.co/cn/what-is/elasticsearch 
    全文搜索属于最常见的需求,开源的 Elasticsearch 是目前全文搜索引擎的首选。 
    它可以快速地储存、搜索和分析海量数据。维基百科、Stack Overflow、Github 都采用它
      Elastic 的底层是开源库 Lucene。但是,你没法直接用 Lucene,必须自己写代码去调用它的接口。Elastic 是 Lucene 的封装,提供了 REST API 的操作接口,开箱即用。
      
      REST API:天然的跨平台。
      官方文档:https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
      官方中文:https://www.elastic.co/guide/cn/elasticsearch/guide/current/foreword_id.html
      社区中文:
          https://es.xiaoleilu.com/index.html
          http://doc.codingdict.com/elasticsearch/0/

    2、基本概念

    1、Index(索引)
        动词,相当于 MySQL 中的 insert; 
        名词,相当于 MySQL 中的 Database
    2、Type(类型)
        在 Index(索引)中,可以定义一个或多个类型。 
        类似于 MySQL 中的 Table;每一种类型的数据放在一起;
    3、Document(文档) 
        保存在某个索引(Index)下,某种类型(Type)的一个数据(Document),文档是 JSON 格 式的,
    Document 就像是 MySQL 中的某个 Table 里面的内容;
    4、倒排索引机制

    3、Docker 安装 Es

    1、下载镜像文件
      docker pull elasticsearch:7.4.2 存储和检索数据
      docker pull kibana:7.4.2 可视化检索数据 
      注意:版本要统一
    先检查一下虚拟机的可用内存
    2、安装 ElasticSearch
    (1)创建挂载目录
        mkdir -p /mydata/elasticsearch/plugins
        mkdir -p /mydata/elasticsearch/config
        mkdir -p /mydata/elasticsearch/data

     (2)设置es可以被远程任何机器访问

         echo "http.host: 0.0.0.0" >> /mydata/elasticsearch/config/elasticsearch.yml

     (3)递归更改权限,es需要访问

        chmod -R 777 /mydata/elasticsearch

        注意:一定要授权,否则后面启动的时候会访问拒绝,没权限

              

     (4)创建实例,启动 Elastic search

        docker run --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" \-e ES_JAVA_OPTS="-Xms64m -Xmx128m" -v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /mydata/elasticsearch/data:/usr/share/elasticsearch/data -v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins -d elasticsearch:7.4.2

      注意:

        # 9200是用户交互端口 9300是集群心跳端口

        # -e指定是单阶段运行

        # -e指定占用的内存大小,生产时可以设置32G 

      以后再外面装好插件重启即可;

      特别注意:

        -e ES_JAVA_OPTS="-Xms64m -Xmx128m" \ 测试环境下,设置 ES 的初始内存和最大内存,否则导致过大启动不了 ES 

    (5)设置随docker自启动
       docker update elasticsearch --restart=always

     (6)测试访问

        查看elasticsearch版本信息:http://192.168.56.10:9200/

      显示elasticsearch 节点信息http://192.168.11.129:9200/_cat/nodes

      127.0.0.1 69 99 9 1.07 0.78 0.56 dilm * 79966af1bf0e

      79966af1bf0e代表上面的节点,*代表是主节点

    3、安装 kibana
    (1)创建实例并启动
        docker run --name kibana -e ELASTICSEARCH_HOSTS=http://192.168.56.10:9200 -p 5601:5601 -d kibana:7.4.2 
      注意:http://192.168.56.10:9200 一定改为自己虚拟机的地址
     (2)设置随docker自启动
       docker update kibana --restart=always
     (3)测试
      访问:http://192.168.56.10:5601/app/kibana

    4、初步检索

    1、_cat
    (1)GET /_cat/nodes:查看所有节点
        请求:http://192.168.56.10:9200/_cat/nodes
         返回:127.0.0.1 53 99 18 1.64 1.34 0.89 dilm * 79966af1bf0e
         注意:79966af1bf0e代表上面的节点,*代表是主节点
    (2)GET /_cat/health:查看es健康状况
        请求:http://192.168.56.10:9200/_cat/health
        返回:1639660246 13:10:46 elasticsearch green 1 1 2 2 0 0 0 0 - 100.0%
        注意:green表示健康值正常
    (3)GET /_cat/master:查看主节点
        请求:http://192.168.56.10:9200/_cat/master
        返回:yV_3GAgSRlCZRbsaZGmwvg 127.0.0.1 127.0.0.1 79966af1bf0e
        注意:主节点唯一编号、虚拟机地址
    (4)GET /_cat/indices:查看所有索引,等价于mysql的show database;
        请求:http://192.168.56.10:9200/_cat/indices
        返回:green open .kibana_task_manager_1 TgtHkBPEQa27TRzx7csj_A 1 0 2 0 38.3kb 38.3kb
           green open .kibana_1 WX3cdamiRh-ylxDECyU5qg 1 0 3 0 14.8kb 14.8kb
    2、索引一个文档(保存)
      保存一个数据,保存在哪个索引的哪个类型下,指定用哪个唯一标识
      (1)PUT customer/external/1;在 customer 索引下的 external 类型下保存 1 号数据为 
          请求:http://192.168.56.10:9200/customer/external/1
             在customer索引下的external类型下保存1号数据为
             { "name":"John Doe" }
        注意:
          PUT和POST都可以 POST新增。如果不指定id,会自动生成id。指定id就会修改这个数据,并新增版本号;
          PUT可以新增也可以修改。PUT必须指定id;由于PUT需要指定id,我们一般用来做修改操作,不指定id会报错。 唯一区分是post不指定id时永远为创建
    创建数据成功后,显示201 created表示插入记录成功。
    返回数据:
    带有下划线开头的,称为元数据,反映了当前的基本信息。  
    {
        "_index": "customer", 表明该数据在哪个数据库下;
        "_type": "external", 表明该数据在哪个类型下;
        "_id": "1",  表明被保存数据的id;
        "_version": 1,  被保存数据的版本
        "result": "created", 这里是创建了一条数据,如果重新put一条数据,则该状态会变为updated,并且版本号也会发生变化。
        "_shards": {
            "total": 2,
            "successful": 1,
            "failed": 0
        },
        "_seq_no": 0,
        "_primary_term": 1
    }
    
    下面选用POST方式:
    添加数据的时候,不指定ID,会自动的生成id,并且类型是新增:
    {
        "_index": "customer",
        "_type": "external",
        "_id": "5MIjvncBKdY1wAQm-wNZ",
        "_version": 1,
        "result": "created",
        "_shards": {
            "total": 2,
            "successful": 1,
            "failed": 0
        },
        "_seq_no": 11,
        "_primary_term": 6
    }
    
    再次使用POST插入数据,不指定ID,仍然是新增的:
    {
        "_index": "customer",
        "_type": "external",
        "_id": "5cIkvncBKdY1wAQmcQNk",
        "_version": 1,
        "result": "created",
        "_shards": {
            "total": 2,
            "successful": 1,
            "failed": 0
        },
        "_seq_no": 12,
        "_primary_term": 6
    }
    
    
    添加数据的时候,指定ID,会使用该id,并且类型是新增:
    {
        "_index": "customer",
        "_type": "external",
        "_id": "2",
        "_version": 1,
        "result": "created",
        "_shards": {
            "total": 2,
            "successful": 1,
            "failed": 0
        },
        "_seq_no": 13,
        "_primary_term": 6
    }
    
    
    再次使用POST插入数据,指定同样的ID,类型为updated
    {
        "_index": "customer",
        "_type": "external",
        "_id": "2",
        "_version": 2,
        "result": "updated",
        "_shards": {
            "total": 2,
            "successful": 1,
            "failed": 0
        },
        "_seq_no": 14,
        "_primary_term": 6
    }
    3、查询文档 & 乐观锁字段
    (1)GET /customer/external/1:查询文档
        请求:http://192.168.56.10:9200/customer/external/1
         返回:{        "_index": "customer",        "_type": "external",        "_id": "1",        "_version": 10,        "_seq_no": 18,//并发控制字段,每次更新都会+1,用来做乐观锁        "_primary_term": 6,//同上,主分片重新分配,如重启,就会变化        "found": true,         "_source": {         "name": "John Doe"        }        }
     通过“if_seq_no=1&if_primary_term=1”,当序列号匹配的时候,才进行修改,否则不修改。 

    (2)实例:将id=1的数据更新为name=1,然后再次更新为name=2,起始1_seq_no=24,_primary_term=1
      (a)将name更新为1
         PUT http://192.168.56.10:9200/customer/external/1

      (b)将name更新为2,更新过程中使用seq_no=24

         PUT http://192.168.56.10:9200/customer/external/1?if_seq_no=24&if_primary_term=1

      出现更新错误

      查询新的数据,发现_seq_no=25,是第一次更新完毕之后的_seq_no

      再次更新,更新成功

      PUT http://192.168.56.10:9200/customer/external/1?if_seq_no=26&if_primary_term=1

    4、更新文档
    (1)更新文档_update
      (a)带有update的POST
        POST customer
    /externel/1/_update     {     "doc":{      "name":"111"     }     }     或者   (b)不带update的POST
        POST customer
    /externel/1     {     "doc":{      "name":"222"     }     }     或者   (c)不带update的PUT
        PUT customer
    /externel/1     {     "doc":{       "name":"222"     }     }
    (2)不同
      (a)POST操作会对比源文档数据,如果相同不会有什么操作,文档version不增加。
      (b)PUT操作总会将数据重新保存并增加version版本
      (3)POST时带_update对比元数据如果一样就不进行任何操作。
    (3)看场景
      (a)对于大并发更新,不带update
      (b)对于大并发查询偶尔更新,带update;对比更新,重新计算分配规则
    (4)实例
     

      如果再次执行更新,则不执行任何操作,序列号也不发生变化,返回:

      {
        "_index": "customer",
          "_type": "external",
        "_id": "1",
        "_version": 9,
        "result": "noop",
        "_shards": {
          "total": 0,
          "successful": 0,
          "failed": 0
        },
        "_seq_no": 28,
        "_primary_term": 2
      }

      POST更新方式,会对比原来的数据,和原来的相同,则不执行任何操作(version和_seq_no)都不变。

     POST更新文档,不带_update 
     在更新过程中,重复执行更新操作,数据也能够更新成功,不会和原来的数据进行对比。_seq_no会变化

      {
        "_index": "customer",
        "_type": "external",
        "_id": "1",
        "_version": 13,
        "result": "updated",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "_seq_no": 32,
        "_primary_term": 2
      }

    5、删除文档 & 索引
    (1)语法
        DELETE customer/external/1
        DELETE customer
      注:elasticsearch并没有提供删除类型的操作,只提供了删除索引和文档的操作。
    (2)实例
      删除id=1的数据,删除后继续查询
      DELETE http://192.168.56.10:9200/customer/external/1

      {
        "_index": "customer",
        "_type": "external",
        "_id": "1",
        "_version": 14,
        "result": "deleted",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "_seq_no": 33,
        "_primary_term": 2
      }

        再次执行DELETE http://192.168.56.10:9200/customer/external/1

      {
        "_index": "customer",
        "_type": "external",
        "_id": "1",
        "_version": 1,
        "result": "not_found",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "_seq_no": 34,
        "_primary_term": 2
      }

        GET http://192.168.56.10:9200/customer/external/1

      {
        "_index": "customer",
        "_type": "external",
        "_id": "1",
        "found": false
      }

     (3)删除整个customer索引数据

        删除前,所有的索引http://192.168.56.10:9200/_cat/indices

      green open .kibana_task_manager_1 TgtHkBPEQa27TRzx7csj_A 1 0 2 0 30.4kb 30.4kb
      green open .kibana_1 WX3cdamiRh-ylxDECyU5qg 1 0 5 0 18.3kb 18.3kb
      yellow open customer Vaet8xVXTOSEnDQzcmfnyw 1 1 6 4 13.9kb 13.9kb

      删除“ customer ”索引 DELTE http://192.168.56.10:9200/customer
      响应

      {
        "acknowledged": true
      }

        删除后,所有的索引http://192.168.56.10:9200/_cat/indices

      green open .kibana_task_manager_1 TgtHkBPEQa27TRzx7csj_A 1 0 2 0 30.4kb 30.4kb
      green open .kibana_1 WX3cdamiRh-ylxDECyU5qg 1 0 5 0 18.3kb 18.3kb

    6、bulk 批量 API
     (1)匹配导入数据   POST http://192.168.56.10:9200/customer/external/_bulk   两行为一个整体   {"index":{"_id":"1"}}   {"name":"a"}   {"index":{"_id":"2"}}   {"name":"b"} 注意格式json和text均不可,要去kibana里Dev Tools

    语法格式:

      { action: { metadata }}\n
      { request body}\n
      { action: { metadata }}\n
      { request body}\n
      bulk API 以此按顺序执行所有的 action(动作)。如果一个单个的动作因任何原因而失败,它将继续处理它后面剩余的动作。当 bulk API 返回时,它将提供每个动作的状态(与发送的顺序相同),所以您可以检查是否一个指定的动作是不是失败了。
     
    (2)实例1:执行多条数据
    POST /customer/external/_bulk
    {"index":{"_id":"1"}}
    {"name":"John Doe"}
    {"index":{"_id":"2"}}
    {"name":"John Doe"}
      执行结果:
    #! Deprecation: [types removal] Specifying types in bulk requests is deprecated.
    {
      "took" : 105,
      "errors" : false,
      "items" : [
        {
          "index" : {
            "_index" : "customer",
            "_type" : "external",
            "_id" : "1",
            "_version" : 2,
            "result" : "updated",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 2,
            "_primary_term" : 1,
            "status" : 200
          }
        },
        {
          "index" : {
            "_index" : "customer",
            "_type" : "external",
            "_id" : "2",
            "_version" : 2,
            "result" : "updated",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 3,
            "_primary_term" : 1,
            "status" : 200
          }
        }
      ]
    }
    (3)实例2:对于整个索引执行批量操作
    POST /_bulk
    {"delete":{"_index":"website","_type":"blog","_id":"123"}}
    {"create":{"_index":"website","_type":"blog","_id":"123"}}
    {"title":"my first blog post"}
    {"index":{"_index":"website","_type":"blog"}}
    {"title":"my second blog post"}
    {"update":{"_index":"website","_type":"blog","_id":"123"}}
    {"doc":{"title":"my updated blog post"}}
      执行结果:
    #! Deprecation: [types removal] Specifying types in bulk requests is deprecated.
    {
      "took" : 625,
      "errors" : false,
      "items" : [
        {
          "delete" : {
            "_index" : "website",
            "_type" : "blog",
            "_id" : "123",
            "_version" : 1,
            "result" : "not_found",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 0,
            "_primary_term" : 1,
            "status" : 404
          }
        },
        {
          "create" : {
            "_index" : "website",
            "_type" : "blog",
            "_id" : "123",
            "_version" : 2,
            "result" : "created",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 1,
            "_primary_term" : 1,
            "status" : 201
          }
        },
        {
          "index" : {
            "_index" : "website",
            "_type" : "blog",
            "_id" : "u3xrxn0BOYHMBBh2yP0L",
            "_version" : 1,
            "result" : "created",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 2,
            "_primary_term" : 1,
            "status" : 201
          }
        },
        {
          "update" : {
            "_index" : "website",
            "_type" : "blog",
            "_id" : "123",
            "_version" : 3,
            "result" : "updated",
            "_shards" : {
              "total" : 2,
              "successful" : 1,
              "failed" : 0
            },
            "_seq_no" : 3,
            "_primary_term" : 1,
            "status" : 200
          }
        }
      ]
    }
    7、样本测试数据
      准备了一份顾客银行账户信息的虚构的JSON文档样本。每个文档都有下列的schema(模式)。
    { "account_number": 1, "balance": 39225, "firstname": "Amber", "lastname": "Duke", "age": 32, "gender": "M", "address": "880 Holmes Lane", "employer": "Pyrami", "email": "amberduke@pyrami.com", "city": "Brogan", "state": "IL" }
    https://gitee.com/xlh_blog/common_content/blob/master/es%E6%B5%8B%E8%AF%95%E6%95%B0%E6%8D%AE.json,导入数据
    POST bank/account/_bulk 上面的数据
    http://192.168.56.10:9200/_cat/indices 刚导入了1000条 yellow open bank GAry5upkQga9NZ6gY2Gyfw 1 1 1000 0 427.7kb 427.7kb

     数据内容

    {"index":{"_id":"1"}}
    {"account_number":1,"balance":39225,"firstname":"Amber","lastname":"Duke","age":32,"gender":"M","address":"880 Holmes Lane","employer":"Pyrami","email":"amberduke@pyrami.com","city":"Brogan","state":"IL"}
    {"index":{"_id":"6"}}
    {"account_number":6,"balance":5686,"firstname":"Hattie","lastname":"Bond","age":36,"gender":"M","address":"671 Bristol Street","employer":"Netagy","email":"hattiebond@netagy.com","city":"Dante","state":"TN"}
    {"index":{"_id":"13"}}
    {"account_number":13,"balance":32838,"firstname":"Nanette","lastname":"Bates","age":28,"gender":"F","address":"789 Madison Street","employer":"Quility","email":"nanettebates@quility.com","city":"Nogal","state":"VA"}
    {"index":{"_id":"18"}}
    {"account_number":18,"balance":4180,"firstname":"Dale","lastname":"Adams","age":33,"gender":"M","address":"467 Hutchinson Court","employer":"Boink","email":"daleadams@boink.com","city":"Orick","state":"MD"}
    {"index":{"_id":"20"}}
    {"account_number":20,"balance":16418,"firstname":"Elinor","lastname":"Ratliff","age":36,"gender":"M","address":"282 Kings Place","employer":"Scentric","email":"elinorratliff@scentric.com","city":"Ribera","state":"WA"}
    {"index":{"_id":"25"}}
    {"account_number":25,"balance":40540,"firstname":"Virginia","lastname":"Ayala","age":39,"gender":"F","address":"171 Putnam Avenue","employer":"Filodyne","email":"virginiaayala@filodyne.com","city":"Nicholson","state":"PA"}
    {"index":{"_id":"32"}}
    {"account_number":32,"balance":48086,"firstname":"Dillard","lastname":"Mcpherson","age":34,"gender":"F","address":"702 Quentin Street","employer":"Quailcom","email":"dillardmcpherson@quailcom.com","city":"Veguita","state":"IN"}
    {"index":{"_id":"37"}}
    {"account_number":37,"balance":18612,"firstname":"Mcgee","lastname":"Mooney","age":39,"gender":"M","address":"826 Fillmore Place","employer":"Reversus","email":"mcgeemooney@reversus.com","city":"Tooleville","state":"OK"}
    {"index":{"_id":"44"}}
    {"account_number":44,"balance":34487,"firstname":"Aurelia","lastname":"Harding","age":37,"gender":"M","address":"502 Baycliff Terrace","employer":"Orbalix","email":"aureliaharding@orbalix.com","city":"Yardville","state":"DE"}
    {"index":{"_id":"49"}}
    {"account_number":49,"balance":29104,"firstname":"Fulton","lastname":"Holt","age":23,"gender":"F","address":"451 Humboldt Street","employer":"Anocha","email":"fultonholt@anocha.com","city":"Sunriver","state":"RI"}
    {"index":{"_id":"51"}}
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    {"account_number":849,"balance":16200,"firstname":"Barry","lastname":"Chapman","age":26,"gender":"M","address":"931 Dekoven Court","employer":"Darwinium","email":"barrychapman@darwinium.com","city":"Whitestone","state":"WY"}
    {"index":{"_id":"851"}}
    {"account_number":851,"balance":22026,"firstname":"Henderson","lastname":"Price","age":33,"gender":"F","address":"530 Hausman Street","employer":"Plutorque","email":"hendersonprice@plutorque.com","city":"Brutus","state":"RI"}
    {"index":{"_id":"856"}}
    {"account_number":856,"balance":27583,"firstname":"Alissa","lastname":"Knox","age":25,"gender":"M","address":"258 Empire Boulevard","employer":"Geologix","email":"alissaknox@geologix.com","city":"Hartsville/Hartley","state":"MN"}
    {"index":{"_id":"863"}}
    {"account_number":863,"balance":23165,"firstname":"Melendez","lastname":"Fernandez","age":40,"gender":"M","address":"661 Johnson Avenue","employer":"Vixo","email":"melendezfernandez@vixo.com","city":"Farmers","state":"IL"}
    {"index":{"_id":"868"}}
    {"account_number":868,"balance":27624,"firstname":"Polly","lastname":"Barron","age":22,"gender":"M","address":"129 Frank Court","employer":"Geofarm","email":"pollybarron@geofarm.com","city":"Loyalhanna","state":"ND"}
    {"index":{"_id":"870"}}
    {"account_number":870,"balance":43882,"firstname":"Goff","lastname":"Phelps","age":21,"gender":"M","address":"164 Montague Street","employer":"Digigen","email":"goffphelps@digigen.com","city":"Weedville","state":"IL"}
    {"index":{"_id":"875"}}
    {"account_number":875,"balance":19655,"firstname":"Mercer","lastname":"Pratt","age":24,"gender":"M","address":"608 Perry Place","employer":"Twiggery","email":"mercerpratt@twiggery.com","city":"Eggertsville","state":"MO"}
    {"index":{"_id":"882"}}
    {"account_number":882,"balance":10895,"firstname":"Mari","lastname":"Landry","age":39,"gender":"M","address":"963 Gerald Court","employer":"Kenegy","email":"marilandry@kenegy.com","city":"Lithium","state":"NC"}
    {"index":{"_id":"887"}}
    {"account_number":887,"balance":31772,"firstname":"Eunice","lastname":"Watts","age":36,"gender":"F","address":"707 Stuyvesant Avenue","employer":"Memora","email":"eunicewatts@memora.com","city":"Westwood","state":"TN"}
    {"index":{"_id":"894"}}
    {"account_number":894,"balance":1031,"firstname":"Tyler","lastname":"Fitzgerald","age":32,"gender":"M","address":"787 Meserole Street","employer":"Jetsilk","email":"tylerfitzgerald@jetsilk.com","city":"Woodlands","state":"WV"}
    {"index":{"_id":"899"}}
    {"account_number":899,"balance":32953,"firstname":"Carney","lastname":"Callahan","age":23,"gender":"M","address":"724 Kimball Street","employer":"Mangelica","email":"carneycallahan@mangelica.com","city":"Tecolotito","state":"MT"}
    {"index":{"_id":"902"}}
    {"account_number":902,"balance":13345,"firstname":"Hallie","lastname":"Jarvis","age":23,"gender":"F","address":"237 Duryea Court","employer":"Anixang","email":"halliejarvis@anixang.com","city":"Boykin","state":"IN"}
    {"index":{"_id":"907"}}
    {"account_number":907,"balance":12961,"firstname":"Ingram","lastname":"William","age":36,"gender":"M","address":"826 Overbaugh Place","employer":"Genmex","email":"ingramwilliam@genmex.com","city":"Kimmell","state":"AK"}
    {"index":{"_id":"914"}}
    {"account_number":914,"balance":7120,"firstname":"Esther","lastname":"Bean","age":32,"gender":"F","address":"583 Macon Street","employer":"Applica","email":"estherbean@applica.com","city":"Homeworth","state":"MN"}
    {"index":{"_id":"919"}}
    {"account_number":919,"balance":39655,"firstname":"Shauna","lastname":"Hanson","age":27,"gender":"M","address":"557 Hart Place","employer":"Exospace","email":"shaunahanson@exospace.com","city":"Outlook","state":"LA"}
    {"index":{"_id":"921"}}
    {"account_number":921,"balance":49119,"firstname":"Barbara","lastname":"Wade","age":29,"gender":"M","address":"687 Hoyts Lane","employer":"Roughies","email":"barbarawade@roughies.com","city":"Sattley","state":"CO"}
    {"index":{"_id":"926"}}
    {"account_number":926,"balance":49433,"firstname":"Welch","lastname":"Mcgowan","age":21,"gender":"M","address":"833 Quincy Street","employer":"Atomica","email":"welchmcgowan@atomica.com","city":"Hampstead","state":"VT"}
    {"index":{"_id":"933"}}
    {"account_number":933,"balance":18071,"firstname":"Tabitha","lastname":"Cole","age":21,"gender":"F","address":"916 Rogers Avenue","employer":"Eclipto","email":"tabithacole@eclipto.com","city":"Lawrence","state":"TX"}
    {"index":{"_id":"938"}}
    {"account_number":938,"balance":9597,"firstname":"Sharron","lastname":"Santos","age":40,"gender":"F","address":"215 Matthews Place","employer":"Zenco","email":"sharronsantos@zenco.com","city":"Wattsville","state":"VT"}
    {"index":{"_id":"940"}}
    {"account_number":940,"balance":23285,"firstname":"Melinda","lastname":"Mendoza","age":38,"gender":"M","address":"806 Kossuth Place","employer":"Kneedles","email":"melindamendoza@kneedles.com","city":"Coaldale","state":"OK"}
    {"index":{"_id":"945"}}
    {"account_number":945,"balance":23085,"firstname":"Hansen","lastname":"Hebert","age":33,"gender":"F","address":"287 Conduit Boulevard","employer":"Capscreen","email":"hansenhebert@capscreen.com","city":"Taycheedah","state":"AK"}
    {"index":{"_id":"952"}}
    {"account_number":952,"balance":21430,"firstname":"Angelique","lastname":"Weeks","age":33,"gender":"M","address":"659 Reeve Place","employer":"Exodoc","email":"angeliqueweeks@exodoc.com","city":"Turpin","state":"MD"}
    {"index":{"_id":"957"}}
    {"account_number":957,"balance":11373,"firstname":"Michael","lastname":"Giles","age":31,"gender":"M","address":"668 Court Square","employer":"Yogasm","email":"michaelgiles@yogasm.com","city":"Rosburg","state":"WV"}
    {"index":{"_id":"964"}}
    {"account_number":964,"balance":26154,"firstname":"Elena","lastname":"Waller","age":34,"gender":"F","address":"618 Crystal Street","employer":"Insurety","email":"elenawaller@insurety.com","city":"Gallina","state":"NY"}
    {"index":{"_id":"969"}}
    {"account_number":969,"balance":22214,"firstname":"Briggs","lastname":"Lynn","age":30,"gender":"M","address":"952 Lester Court","employer":"Quinex","email":"briggslynn@quinex.com","city":"Roland","state":"ID"}
    {"index":{"_id":"971"}}
    {"account_number":971,"balance":22772,"firstname":"Gabrielle","lastname":"Reilly","age":32,"gender":"F","address":"964 Tudor Terrace","employer":"Blanet","email":"gabriellereilly@blanet.com","city":"Falmouth","state":"AL"}
    {"index":{"_id":"976"}}
    {"account_number":976,"balance":31707,"firstname":"Mullen","lastname":"Tanner","age":26,"gender":"M","address":"711 Whitney Avenue","employer":"Pulze","email":"mullentanner@pulze.com","city":"Mooresburg","state":"MA"}
    {"index":{"_id":"983"}}
    {"account_number":983,"balance":47205,"firstname":"Mattie","lastname":"Eaton","age":24,"gender":"F","address":"418 Allen Avenue","employer":"Trasola","email":"mattieeaton@trasola.com","city":"Dupuyer","state":"NJ"}
    {"index":{"_id":"988"}}
    {"account_number":988,"balance":17803,"firstname":"Lucy","lastname":"Castro","age":34,"gender":"F","address":"425 Fleet Walk","employer":"Geekfarm","email":"lucycastro@geekfarm.com","city":"Mulino","state":"VA"}
    {"index":{"_id":"990"}}
    {"account_number":990,"balance":44456,"firstname":"Kelly","lastname":"Steele","age":35,"gender":"M","address":"809 Hoyt Street","employer":"Eschoir","email":"kellysteele@eschoir.com","city":"Stewartville","state":"ID"}
    {"index":{"_id":"995"}}
    {"account_number":995,"balance":21153,"firstname":"Phelps","lastname":"Parrish","age":25,"gender":"M","address":"666 Miller Place","employer":"Pearlessa","email":"phelpsparrish@pearlessa.com","city":"Brecon","state":"ME"}
    

    5、进阶检索

    1、SearchAPI
      ES支持两种基本方式检索;
      (a)通过REST request uri 发送搜索参数 (uri +检索参数);
      (b)通过REST request body 来发送它们(uri+请求体);
    (1)检索信息
    (a)一切检索从_search开始

     (b)uri+请求体进行检索

    2、Query DSL
    (1)基本语法格式
      Elasticsearch 提供了一个可以执行查询的 Json 风格的 DSL(domain-specific language 领域特定语言)。这个被称为 Query DSL。该查询语言非常全面,
    并且刚开始的时候感觉有点复杂,真正学好它的方法是从一些基础的示例开始的
    (a)一个查询语句 的典型结构

     (b)如果是针对某个字段,那么它的结构如下:

    (2)返回部分字段

    (3)match【匹配查询】 

      (a)基本类型(非字符串),精确匹配

      (b)字符串,全文检索

      (c)字符换,多个单词(分词+全文检索)

    (4)match_phrase【短语匹配】

      文本字段的匹配,使用keyword,匹配的条件就是要显示字段的全部值,要进行精确匹配的。

      match_phrase是做短语匹配,只要文本中包含匹配条件,就能匹配到。

    (5)multi_match【多字段匹配】

    (6)bool【复合查询】

      复合语句可以合并 任何 其它查询语句,包括复合语句,了解这一点是很重要的。这就意味着,复合语句之间可以互相嵌套,
    可以表达非常复杂的逻辑。
     (a)must:必须达到 must 列举的所有条件
      实例:查询gender=m,并且address=mill的数据

     (b)should:应该达到 should 列举的条件,如果达到会增加相关文档的评分,并不会改变查询的结果。如果 query 中只有 should 且只有一种匹配规则,那么 should 的条件就会被作为默认匹配条件而去改变查询结果

     (c)must_not 必须不是指定的情况

    (7)filter【结果过滤】

    (8)term

      和 match 一样。匹配某个属性的值。全文检索字段用 match,其他非 text 字段匹配用 term。

      不要使用term来进行文本字段查询

      es默认存储text值时用分词分析,所以要搜索text值,使用match

      字段.keyword:要一一匹配到

      match_phrase:子串包含即可

    (9)aggregations(执行聚合)

      聚合提供了从数据中分组和提取数据的能力。最简单的聚合方法大致等于 SQL GROUP BY 和 SQL 聚合函数。在 Elasticsearch 中,您有执行搜索返回 hits(命中结果),
    并且同时返回聚合结果,把一个响应中的所有 hits(命中结果)分隔开的能力。这是非常强大且有效的,您可以执行查询和多个聚合,并且在一次使用中得到各自的(任何一个的)返回结果,使用
    一次简洁和简化的 API 来避免网络往返。
     (a)搜索 address 中包含 mill 的所有人的年龄分布以及平均年龄,但不显示这些人的详情

    运行结果:

    {
      "took" : 274,
      "timed_out" : false,
      "_shards" : {
        "total" : 1,
        "successful" : 1,
        "skipped" : 0,
        "failed" : 0
      },
      "hits" : {
        "total" : {
          "value" : 4,
          "relation" : "eq"
        },
        "max_score" : null,
        "hits" : [ ]
      },
      "aggregations" : {
        "ageAvg" : {
          "value" : 34.0
        },
        "group_by_state" : {
          "doc_count_error_upper_bound" : 0,
          "sum_other_doc_count" : 0,
          "buckets" : [
            {
              "key" : 38,
              "doc_count" : 2
            },
            {
              "key" : 28,
              "doc_count" : 1
            },
            {
              "key" : 32,
              "doc_count" : 1
            }
          ]
        }
      }
    }

     (b)复杂:按照年龄聚合,并且请求这些年龄段的这些人的平均薪资

     (c)复杂:查出所有年龄分布,并且这些年龄段中 M 的平均薪资和 F 的平均薪资以及这个年龄段的总体平均薪资

    3、Mappig
      映射定义文档如何被存储检索的
    1)字段类型

    (2) 映射

     (a)查看 mapping 信息

        GET bank/_mapping

     (b)修改 mapping 信息
        https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html

    (3)新版本改变

    1、创建映射

      输出:

    {
      "acknowledged" : true,
      "shards_acknowledged" : true,
      "index" : "my_index"
    }

      查看映射 GET /my_index

    {
      "my_index" : {
        "aliases" : { },
        "mappings" : {
          "properties" : {
            "age" : {
              "type" : "integer"
            },
            "email" : {
              "type" : "keyword"
            },
            "name" : {
              "type" : "text"
            }
          }
        },
        "settings" : {
          "index" : {
            "creation_date" : "1639723434557",
            "number_of_shards" : "1",
            "number_of_replicas" : "1",
            "uuid" : "O71P-B5WRa6z9YkMLt3vMg",
            "version" : {
              "created" : "7040299"
            },
            "provided_name" : "my_index"
          }
        }
      }
    }

    2、添加新的字段映射

      输出:

    {
      "acknowledged" : true
    }

      注意:这里的 “index”: false,表明新增的字段不能被检索,只是一个冗余字段。

    3、更新映射

      对于已经存在的映射字段,我们不能更新。更新必须创建新的索引进行数据迁移

    4、数据迁移

      先创建出 new_twitter 的正确映射。然后使用如下方式进行数据迁移 

    4、分词
      一个 tokenizer(分词器)接收一个字符流,将之分割为独立的 tokens(词元,通常是独立的单词),然后输出 tokens 流。
      例如,whitespace tokenizer 遇到空白字符时分割文本。它会将文本 "Quick brown fox!" 分割为 [Quick, brown, fox!]。
      该 tokenizer(分词器)还负责记录各个 term(词条)的顺序或 position 位置(用于 phrase 短语和 word proximity 词近邻查询),
    以及 term(词条)所代表的原始 word(单词)的 start(起始)和 end(结束)的 character offsets(字符偏移量)(用于高亮显示搜索的内容)。
      Elasticsearch 提供了很多内置的分词器,可以用来构建 custom analyzers(自定义分词器)。
     
    (1)安装 ik 分词器
      注意:不能用默认 elasticsearch-plugin install xxx.zip 进行自动安装 
      https://github.com/medcl/elasticsearch-analysis-ik/releases?after=v6.4.2 对应 es 版本安装
     
     (a)进入es容器内部 plugins 目录
        docker exec -it 容器 id /bin/bash
        注意:由于我们在安装 es 的时候,已经将容器内部的 plugins 目录映射到 /mydata/elasticsearch/plugins/,所以我们直接切换到映射目录即可

      (b)下载 ik 分词器

        wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.4.2/elasticsearch-analysis-ik-7.4.2.zip

      注意:

      (1)这一步可以使用wget命令下载,也可以直接下载下来使用xshell命令上传

      (2)关于wget和unzip命令找不到的问题,查看 谷粒商城分布式基础(二)—— 环境搭建(虚拟机 & JDK & Maven & docker & mysql & redis & vue) 中 “1、安装 Linux 虚拟机” 的 第13点

      我们还可以进入es的容器中,可以看到映射对应的文件目录里面也可以看到

      (c)解压下载文件

      最后,记得删除掉原下载的压缩包

      (d)设置权限

      (e)确认是否安装好了分词器

      (f)重启 es

    2)测试分词器

    {
      "tokens" : [
        {
          "token" : "我",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "<IDEOGRAPHIC>",
          "position" : 0
        },
        {
          "token" : "是",
          "start_offset" : 1,
          "end_offset" : 2,
          "type" : "<IDEOGRAPHIC>",
          "position" : 1
        },
        {
          "token" : "中",
          "start_offset" : 2,
          "end_offset" : 3,
          "type" : "<IDEOGRAPHIC>",
          "position" : 2
        },
        {
          "token" : "国",
          "start_offset" : 3,
          "end_offset" : 4,
          "type" : "<IDEOGRAPHIC>",
          "position" : 3
        },
        {
          "token" : "人",
          "start_offset" : 4,
          "end_offset" : 5,
          "type" : "<IDEOGRAPHIC>",
          "position" : 4
        }
      ]
    }

    {
      "tokens" : [
        {
          "token" : "我",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "CN_CHAR",
          "position" : 0
        },
        {
          "token" : "是",
          "start_offset" : 1,
          "end_offset" : 2,
          "type" : "CN_CHAR",
          "position" : 1
        },
        {
          "token" : "中国人",
          "start_offset" : 2,
          "end_offset" : 5,
          "type" : "CN_WORD",
          "position" : 2
        }
      ]
    }

    {
      "tokens" : [
        {
          "token" : "我",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "CN_CHAR",
          "position" : 0
        },
        {
          "token" : "是",
          "start_offset" : 1,
          "end_offset" : 2,
          "type" : "CN_CHAR",
          "position" : 1
        },
        {
          "token" : "中国人",
          "start_offset" : 2,
          "end_offset" : 5,
          "type" : "CN_WORD",
          "position" : 2
        },
        {
          "token" : "中国",
          "start_offset" : 2,
          "end_offset" : 4,
          "type" : "CN_WORD",
          "position" : 3
        },
        {
          "token" : "国人",
          "start_offset" : 3,
          "end_offset" : 5,
          "type" : "CN_WORD",
          "position" : 4
        }
      ]
    }

      能够看出不同的分词器,分词有明显的区别,所以以后定义一个索引不能再使用默认的 mapping 了,要手工建立 mapping, 因为要选择分词器。
    3)自定义词库
      注意:请先按照 谷粒商城分布式高级(一)—— 环境搭建(高级篇补充)(ElasticSearch) 中的 “2、Nginx” 安装好nginx
       (a)修改/mydata/elasticsearch/plugins/ik/config/中的 IKAnalyzer.cfg.xml
        原来的xml

        修改后的xml

      (b)然后重启 es 服务,重启 nginx

        查看是否启动成功:

          http://192.168.56.10:9200/

          http://192.168.56.10:5601/app/kibana

      (c)在 kibana 中测试分词效果

    6、Elasticsearch-Rest-Client

    最终选择 Elasticsearch-Rest-Client(elasticsearch-rest-high-level-client)

    https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high.html
    1、SpringBoot 整合 ElasticSearch
      创建检索服务 gulimall-search
    (1)New Module,选择Spring Initiializr

      选择 Web——Spring Web

    (2)我们修改一下pom.xml,版本环境保持一致 

    (3)引入公共依赖 gulimall-common

      gulimll-common中已经引入了服务的注册发现和配置中心的依赖包

    <dependency>
    <groupId>com.atguigu.gulimall</groupId>
    <artifactId>gulimall-common</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <exclusions>
    <exclusion>
    <groupId>com.baomidou</groupId>
    <artifactId>mybatis-plus-boot-starter</artifactId>
    </exclusion>
    </exclusions>
    </dependency>

    (4)导入 es 的依赖

    <dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-high-level-client</artifactId>
    <version>7.4.2</version>
    </dependency>

    在spring-boot-dependencies中所依赖的ES版本位6.8.5,要改掉
    <properties>
    <java.version>1.8</java.version>
    <spring-cloud.version>Greenwich.SR3</spring-cloud.version>
    <elasticsearch.version>7.4.2</elasticsearch.version>
    </properties>

    (5)配置注册中心

      (a)修改application.yml

      (b)启用服务的注册/发现

    (6)添加 es 配置类

    package com.atguigu.gulimall.search.config;


    import org.apache.http.HttpHost;
    import org.elasticsearch.client.RestClient;
    import org.elasticsearch.client.RestHighLevelClient;
    import org.springframework.boot.SpringBootConfiguration;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;

    /**
    * 1、导入依赖
    * 2、编写配置,给容器中注入一个RestHighLevelClient
    * 3、参考API
    */
    @Configuration
    public class GulimallElasticSearchConfig {

    @Bean
    public RestHighLevelClient esRestClient(){
    RestHighLevelClient client = new RestHighLevelClient(
    RestClient.builder(
    new HttpHost("192.168.56.10", 9200, "http")));
    return client;
    }

    }

    (7)单元测试获取 client对象

    package com.atguigu.gulimall.search;

    import org.elasticsearch.client.RestHighLevelClient;
    import org.junit.Test;
    import org.junit.runner.RunWith;
    import org.springframework.beans.factory.annotation.Autowired;
    import org.springframework.boot.test.context.SpringBootTest;
    import org.springframework.test.context.junit4.SpringRunner;

    import javax.annotation.Resource;

    @RunWith(SpringRunner.class)
    @SpringBootTest
    public class GulimallSearchApplicationTests {

    @Resource
    private RestHighLevelClient client;

    @Test
    public void contextLoads() {
    System.out.println("客户端"+client);
    }

    }

    运行结果:
    2、测试
      请求测试项,比如es添加了安全访问规则,访问es需要添加一个安全头,就可以通过requestOptions设置
      官方建议把requestOptions创建成单实例
    package com.atguigu.gulimall.search.config;


    import org.apache.http.HttpHost;
    import org.elasticsearch.client.RequestOptions;
    import org.elasticsearch.client.RestClient;
    import org.elasticsearch.client.RestHighLevelClient;
    import org.springframework.boot.SpringBootConfiguration;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;

    /**
    * 1、导入依赖
    * 2、编写配置,给容器中注入一个RestHighLevelClient
    * 3、参考API
    */
    @Configuration
    public class GulimallElasticSearchConfig {

    public static final RequestOptions COMMON_OPTIONS;
    static {
    RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
    COMMON_OPTIONS = builder.build();
    }

    @Bean
    public RestHighLevelClient esRestClient(){
    RestHighLevelClient client = new RestHighLevelClient(
    RestClient.builder(
    new HttpHost("192.168.56.10", 9200, "http")));
    return client;
    }

    }
    (1)测试保存数据
      保存方式分为同步和异步,异步方式多了个listener回调
    /**
    * 测试存储数据到es
    */
    @Test
    public void indexData() throws IOException {
    //设置索引
    IndexRequest indexRequest = new IndexRequest("users");
    indexRequest.id("1");//数据的id

    User user = new User();
    user.setUserName("张三");
    user.setAge(20);
    user.setGender("男");
    String jsonString = JSON.toJSONString(user);

    //设置要保存的内容,指定数据和类型
    indexRequest.source(jsonString, XContentType.JSON);

    //执行创建索引和保存数据
    IndexResponse index = client.index(indexRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);

    System.out.println(index);
    }


    @Data
    class User{
    private String userName;
    private String gender;
    private Integer age;
    }
     运行结果:

      查看kibana

    (2) 测试获取数据

      https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high-search.html

    @Test
    public void find() throws IOException{
    //1 创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    searchRequest.indices("bank");
    SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
    // 构造检索条件
    //sourceBuilder.query();
    //sourceBuilder.from();
    //sourceBuilder.size();
    //sourceBuilder.aggregation();
    sourceBuilder.query(QueryBuilders.matchQuery("address","mill"));
    System.out.println(sourceBuilder.toString());

    searchRequest.source(sourceBuilder);

    // 2 执行检索
    SearchResponse response = client.search(searchRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);
    // 3 分析响应结果
    System.out.println(response.toString());
    }

    查询结果:

    {"query":{"match":{"address":{"query":"mill","operator":"OR","prefix_length":0,"max_expansions":50,"fuzzy_transpositions":true,"lenient":false,"zero_terms_query":"NONE","auto_generate_synonyms_phrase_query":true,"boost":1.0}}}}
    {"took":11,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":4,"relation":"eq"},"max_score":5.4032025,"hits":[{"_index":"bank","_type":"account","_id":"970","_score":5.4032025,"_source":{"account_number":970,"balance":19648,"firstname":"Forbes","lastname":"Wallace","age":28,"gender":"M","address":"990 Mill Road","employer":"Pheast","email":"forbeswallace@pheast.com","city":"Lopezo","state":"AK"}},{"_index":"bank","_type":"account","_id":"136","_score":5.4032025,"_source":{"account_number":136,"balance":45801,"firstname":"Winnie","lastname":"Holland","age":38,"gender":"M","address":"198 Mill Lane","employer":"Neteria","email":"winnieholland@neteria.com","city":"Urie","state":"IL"}},{"_index":"bank","_type":"account","_id":"345","_score":5.4032025,"_source":{"account_number":345,"balance":9812,"firstname":"Parker","lastname":"Hines","age":38,"gender":"M","address":"715 Mill Avenue","employer":"Baluba","email":"parkerhines@baluba.com","city":"Blackgum","state":"KY"}},{"_index":"bank","_type":"account","_id":"472","_score":5.4032025,"_source":{"account_number":472,"balance":25571,"firstname":"Lee","lastname":"Long","age":32,"gender":"F","address":"288 Mill Street","employer":"Comverges","email":"leelong@comverges.com","city":"Movico","state":"MT"}}]}}

    @Test
    public void find() throws IOException{
    //1 创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    searchRequest.indices("bank");
    SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
    // 构造检索条件
    //sourceBuilder.query();
    //sourceBuilder.from();
    //sourceBuilder.size();
    //sourceBuilder.aggregation();

    sourceBuilder.query(QueryBuilders.matchQuery("address","mill"));

    //AggregationBuilders工具类构建AggregationBuilder
    // 构建第一个聚合条件:按照年龄的值分布
    TermsAggregationBuilder agg1 = AggregationBuilders.terms("agg1").field("age").size(10);// 聚合名称
    // 参数为AggregationBuilder
    sourceBuilder.aggregation(agg1);

    // 构建第二个聚合条件:平均薪资
    AvgAggregationBuilder agg2 = AggregationBuilders.avg("agg2").field("balance");
    sourceBuilder.aggregation(agg2);

    System.out.println("检索条件"+sourceBuilder.toString());

    searchRequest.source(sourceBuilder);

    // 2 执行检索
    SearchResponse response = client.search(searchRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);
    // 3 分析响应结果
    System.out.println(response.toString());
    }

     运行结果:

    检索条件{"query":{"match":{"address":{"query":"mill","operator":"OR","prefix_length":0,"max_expansions":50,"fuzzy_transpositions":true,"lenient":false,"zero_terms_query":"NONE","auto_generate_synonyms_phrase_query":true,"boost":1.0}}},"aggregations":{"agg1":{"terms":{"field":"age","size":10,"min_doc_count":1,"shard_min_doc_count":0,"show_term_doc_count_error":false,"order":[{"_count":"desc"},{"_key":"asc"}]}},"agg2":{"avg":{"field":"balance"}}}}
    {"took":5,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":4,"relation":"eq"},"max_score":5.4032025,"hits":[{"_index":"bank","_type":"account","_id":"970","_score":5.4032025,"_source":{"account_number":970,"balance":19648,"firstname":"Forbes","lastname":"Wallace","age":28,"gender":"M","address":"990 Mill Road","employer":"Pheast","email":"forbeswallace@pheast.com","city":"Lopezo","state":"AK"}},{"_index":"bank","_type":"account","_id":"136","_score":5.4032025,"_source":{"account_number":136,"balance":45801,"firstname":"Winnie","lastname":"Holland","age":38,"gender":"M","address":"198 Mill Lane","employer":"Neteria","email":"winnieholland@neteria.com","city":"Urie","state":"IL"}},{"_index":"bank","_type":"account","_id":"345","_score":5.4032025,"_source":{"account_number":345,"balance":9812,"firstname":"Parker","lastname":"Hines","age":38,"gender":"M","address":"715 Mill Avenue","employer":"Baluba","email":"parkerhines@baluba.com","city":"Blackgum","state":"KY"}},{"_index":"bank","_type":"account","_id":"472","_score":5.4032025,"_source":{"account_number":472,"balance":25571,"firstname":"Lee","lastname":"Long","age":32,"gender":"F","address":"288 Mill Street","employer":"Comverges","email":"leelong@comverges.com","city":"Movico","state":"MT"}}]},"aggregations":{"avg#agg2":{"value":25208.0},"lterms#agg1":{"doc_count_error_upper_bound":0,"sum_other_doc_count":0,"buckets":[{"key":38,"doc_count":2},{"key":28,"doc_count":1},{"key":32,"doc_count":1}]}}}

    (3)把检索结果封装为java bean 

    @Test
    public void find() throws IOException{
    //1 创建检索请求
    SearchRequest searchRequest = new SearchRequest();
    searchRequest.indices("bank");
    SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
    // 构造检索条件
    //sourceBuilder.query();
    //sourceBuilder.from();
    //sourceBuilder.size();
    //sourceBuilder.aggregation();

    sourceBuilder.query(QueryBuilders.matchQuery("address","mill"));

    //AggregationBuilders工具类构建AggregationBuilder
    // 构建第一个聚合条件:按照年龄的值分布
    TermsAggregationBuilder agg1 = AggregationBuilders.terms("agg1").field("age").size(10);// 聚合名称
    // 参数为AggregationBuilder
    sourceBuilder.aggregation(agg1);

    // 构建第二个聚合条件:平均薪资
    AvgAggregationBuilder agg2 = AggregationBuilders.avg("agg2").field("balance");
    sourceBuilder.aggregation(agg2);

    //System.out.println("检索条件"+sourceBuilder.toString());

    searchRequest.source(sourceBuilder);

    // 2 执行检索
    SearchResponse response = client.search(searchRequest, GulimallElasticSearchConfig.COMMON_OPTIONS);
    // 3 分析响应结果
    //System.out.println(response.toString());
    //Map map = JSON.parseObject(response.toString(), Map.class);
    //3.1 获取所有查到的数据
    SearchHits hits = response.getHits();
    SearchHit[] searchHits = hits.getHits();
    for (SearchHit hit : searchHits){
    hit.getId();hit.getType();hit.getIndex();
    String sourceAsString = hit.getSourceAsString();
    Account account = JSON.parseObject(sourceAsString, Account.class);
    System.out.println("account:"+account);
    }
    }

    @Data
    static class Account{
    private int account_number;
    private int balance;
    private String firstname;
    private String lastname;
    private int age;
    private String gender;
    private String address;
    private String employer;
    private String email;
    private String city;
    private String state;
    }

    运行结果:

    account:GulimallSearchApplicationTests.Account(account_number=970, balance=19648, firstname=Forbes, lastname=Wallace, age=28, gender=M, address=990 Mill Road, employer=Pheast, email=forbeswallace@pheast.com, city=Lopezo, state=AK)
    account:GulimallSearchApplicationTests.Account(account_number=136, balance=45801, firstname=Winnie, lastname=Holland, age=38, gender=M, address=198 Mill Lane, employer=Neteria, email=winnieholland@neteria.com, city=Urie, state=IL)
    account:GulimallSearchApplicationTests.Account(account_number=345, balance=9812, firstname=Parker, lastname=Hines, age=38, gender=M, address=715 Mill Avenue, employer=Baluba, email=parkerhines@baluba.com, city=Blackgum, state=KY)
    account:GulimallSearchApplicationTests.Account(account_number=472, balance=25571, firstname=Lee, lastname=Long, age=32, gender=F, address=288 Mill Street, employer=Comverges, email=leelong@comverges.com, city=Movico, state=MT)

     

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  • 原文地址:https://www.cnblogs.com/javahr/p/15699634.html
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