一、概念

1. 基础概念

image.png

  • 索引:类似于MySQL中的数据库
  • 类型:类似于MySQL中的表
  • 文档:类似于MySQL中的一条记录
  • 属性:类似于MySQL中的一个字段

2. 安装

2.1 Docker方式

2.1.1 下载镜像文件

  1. // root用户可以在命令前加sudo
  2. // 存储和检索数据
  3. docker pull elasticsearch:7.4.2
  4. // 可视化检索数据
  5. docker pull kibana:7.4.2

2.1.2 创建容器

1. ElasticSearch
  1. 创建挂载目录

    1. mkdir -p /opt/docker/elasticsearch/config
    2. mkdir -p /opt/docker/elasticsearch/data
    3. mkdir -p /opt/docker/elasticsearch/plugins
  2. 创建配置文件并写入配置

    1. // 此配置暂时不知道何用,可能是集群相关
    2. echo "http.host: 0.0.0.0" >> /opt/docker/elasticsearch/config/elasticsearch.yml
  3. 处理挂载目录权限

    1. // 保证权限
    2. chmod -R 777 /opt/docker/elasticsearch/
  4. 运行容器 ```bash // 多行命令一定要注意,末尾不要有空格,否则贴到cmd里会报错

docker run \ —name elasticsearch742 \ -p 9200:9200 \ -p 9300:9300 \ -e “discovery.type=single-node” \ -e ES_JAVA_OPTS=”-Xms64m -Xmx512m” \ —mount type=bind,src=/opt/docker/elasticsearch/config/elasticsearch.yml,dst=/usr/share/elasticsearch/config/elasticsearch.yml \ —mount type=bind,src=/opt/docker/elasticsearch/data,dst=/usr/share/elasticsearch/data \ —mount type=bind,src=/opt/docker/elasticsearch/plugins,dst=/usr/share/elasticsearch/plugins \ -d elasticsearch:7.4.2

  1. 参数说明:
  2. - `–name` es实例起名字
  3. - `-p` 端口映射 9200:9200 冒号左边的端口号是主机端口,右边的端口号是docker容器端口,切忌千万不要弄反了,9200是向es发送http请求的端口,9300是分布式集群下es节点之间通信的端口
  4. - `discovery.type=single-node` 以单节点模式运行
  5. - `ES_JAVA_OPTS` 指定运行内存,初始64m,最大128m
  6. - `-mount` 挂载 : 左边是主机目录 ,右边是docer实例内部目录
  7. - `-d` 后台运行容器
  8. 以后在宿主机装好插件重启ES即可。<br />特别注意: <br />`-e ES_JAVA_OPTS="-Xms64m -Xmx256m"` 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
  9. 5. 测试
  10. 使用ip+9200端口,在浏览器访问,出现下面json数据即安装成功。
  11. ```json
  12. {
  13. "name" : "4bf313e3fb40",
  14. "cluster_name" : "elasticsearch",
  15. "cluster_uuid" : "yPjSPUr1RxeimNJ-77XMHQ",
  16. "version" : {
  17. "number" : "7.4.2",
  18. "build_flavor" : "default",
  19. "build_type" : "docker",
  20. "build_hash" : "2f90bbf7b93631e52bafb59b3b049cb44ec25e96",
  21. "build_date" : "2019-10-28T20:40:44.881551Z",
  22. "build_snapshot" : false,
  23. "lucene_version" : "8.2.0",
  24. "minimum_wire_compatibility_version" : "6.8.0",
  25. "minimum_index_compatibility_version" : "6.0.0-beta1"
  26. },
  27. "tagline" : "You Know, for Search"
  28. }
  1. 安全性配置

    1. elasticsearch.yml中增加如下配置:

      1. xpack.security.enabled: true
      2. xpack.security.transport.ssl.enabled: true
    2. 重启es重启

      1. docker restart elasticsearch742
    3. 进入容器内部

      1. docker exec -it elasticsearch742 /bin/bash
    4. 配置密码

方式一:自动生成

  1. // 运行此命令,es会自动生成随机密码
  2. elasticsearch-setup-passwords auto

生成如下:

  1. Changed password for user apm_system
  2. PASSWORD apm_system = t7R97a1jwydHo1EraxNX
  3. Changed password for user kibana
  4. PASSWORD kibana = b9VLaZrh3q3G05OgeKhc
  5. Changed password for user logstash_system
  6. PASSWORD logstash_system = 0Y1oBhEfZUqnQNDNvF5L
  7. Changed password for user beats_system
  8. PASSWORD beats_system = a9II6E3mYCSzpnggNlxA
  9. Changed password for user remote_monitoring_user
  10. PASSWORD remote_monitoring_user = 0AlWhN0X92INjx1GaZJb
  11. Changed password for user elastic
  12. PASSWORD elastic = IyKmRPh2I3EkK47OGiwI

方式二:手动指定

  1. // 运行此命令,手动指定
  2. elasticsearch-setup-passwords interactive

不匹配还可以重试。。
image.png
打开浏览器,访问ip:9200 会提示你输入用户名密码。至此,密码设置完成。

2. Kibana
  1. 创建挂载目录

    1. mkdir -p /opt/docker/elasticsearch/config
  2. 创建配置文件

    1. touch kibana.yml

    ```json #

    THIS IS AN AUTO-GENERATED FILE

    #

Default Kibana configuration for docker target

server.name: kibana server.host: “0” elasticsearch.hosts: [ “http://elasticsearch:9200“ ] xpack.monitoring.ui.container.elasticsearch.enabled: true

下边两项只有es配置了密码才需要

elasticsearch.username: “kibana” elasticsearch.password: “你的es密码”

  1. 3. 运行容器
  2. ```json
  3. docker run \
  4. --name kibana742 \
  5. -e ELASTICSEARCH_HOSTS=http://x.x.x.x:9200 \
  6. --mount type=bind,src=/opt/docker/kibana/config/kibana.yml,dst=/usr/share/kibana/config/kibana.yml \
  7. -p 5601:5601 \
  8. -d kibana:7.4.2
  1. 访问

访问ip:5601,输入之前es中配置的账号密码,即可。

  • 账户:elastic
  • 密码:你的密码

3. 基本操作

3.1 查看状态

  1. GET /_cat/nodes:查看所有节点
  2. GET /_cat/health:查看 es 健康状况
  3. GET /_cat/master:查看主节点
  4. GET /_cat/indices:查看所有索引

前缀为ip:9200

  1. 查看_cat命令列表

image.png

  1. 查看所有节点

image.png

  1. 查看健康状态

image.png

  1. 查看主节点

image.png

  1. 查看所有索引

image.png

3.2 数据操作

3.2.1 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
模板:PUT customer/external/1
在 customer 索引下的 external 类型下保存 1 号数据为:

  1. { "name": "John Doe" }

image.png
image.png
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 可以新增可以修改。
    • PUT 必须指定 id;
    • 由于 PUT 需要指定 id,我们一般都用来做修改操作,不指定 id 会报错。

3.2.2 查询

模板:GET customer/external/1

  1. {
  2. "_index": "customer", //在哪个索引
  3. "_type": "external", //在哪个类型
  4. "_id": "1", //记录 id
  5. "_version": 2, //版本号
  6. "_seq_no": 1, //并发控制字段,每次更新就会+1,用来做乐观锁
  7. "_primary_term": 1, //同上,主分片重新分配,如重启,就会变化
  8. "found": true,
  9. "_source": { //真正的内容
  10. "name": "John Doe"
  11. }
  12. }

image.png
更新携带 ?if_seq_no=0&if_primary_term=1可以做到乐观锁修改:
image.png
image.png

3.2.3 更新

  1. 普通更新
    1. POST customer/external/1/_update
    2. {
    3. "doc":{
    4. "name": "John Doew"
    5. }
    6. }
    1. POST customer/external/1
    2. {
    3. "name": "John Doe2"
    4. }
    1. PUT customer/external/1
    2. {
    3. "name": "John Doe"
    4. }
    image.png
    image.png
    不同点:
  • 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
  • PUT 操作总会将数据重新保存并增加 version 版本;
  • 带_update 对比元数据如果一样就不进行任何操作。

看场景:

  • 对于大并发更新,不带 update;
  • 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。
  1. 更新同时增加属性
    1. POST customer/external/1/_update
    2. {
    3. "doc": {
    4. "name": "Jane Doe",
    5. "age": 20
    6. }
    7. }
    PUT 和 POST 不带_update 也可以。

3.2.4 删除索引、文档

  1. DELETE customer/external/1
  2. DELETE customer

多次删除文档:
image.png
多次删除索引:
image.png

3.2.5 bulk批量操作

语法格式:

  1. { action: { metadata }}
  2. { request body }
  3. { action: { metadata }}
  4. { request body }

apipost不支持这种操作,在kibana中进行

  1. POST customer/external/_bulk
  2. {"index":{"_id":"1"}}
  3. {"name": "John Doe" }
  4. {"index":{"_id":"2"}}
  5. {"name": "Jane Doe" }

image.png
复杂实例:

  1. POST /_bulk
  2. { "delete": { "_index": "website", "_type": "blog", "_id": "123" }}
  3. { "create": { "_index": "website", "_type": "blog", "_id": "123" }}
  4. { "title": "My first blog post" }
  5. { "index": { "_index": "website", "_type": "blog" }}
  6. { "title": "My second blog post" }
  7. { "update": { "_index": "website", "_type": "blog", "_id": "123"} }
  8. { "doc" : {"title" : "My updated blog post"} }

image.png

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。

3.2.6 测试数据导入

测试的银行账户信息,使用POST /bank/account/_bulk做批量插入。

  1. {"index":{"_id":"1"}}
  2. {"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"}
  3. {"index":{"_id":"6"}}
  4. {"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"}
  5. {"index":{"_id":"13"}}
  6. {"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"}
  7. {"index":{"_id":"18"}}
  8. {"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"}
  9. {"index":{"_id":"20"}}
  10. {"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"}
  11. {"index":{"_id":"25"}}
  12. {"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"}
  13. {"index":{"_id":"32"}}
  14. {"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"}
  15. {"index":{"_id":"37"}}
  16. {"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"}
  17. {"index":{"_id":"44"}}
  18. {"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"}
  19. {"index":{"_id":"49"}}
  20. {"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"}
  21. {"index":{"_id":"51"}}
  22. {"account_number":51,"balance":14097,"firstname":"Burton","lastname":"Meyers","age":31,"gender":"F","address":"334 River Street","employer":"Bezal","email":"burtonmeyers@bezal.com","city":"Jacksonburg","state":"MO"}
  23. {"index":{"_id":"56"}}
  24. {"account_number":56,"balance":14992,"firstname":"Josie","lastname":"Nelson","age":32,"gender":"M","address":"857 Tabor Court","employer":"Emtrac","email":"josienelson@emtrac.com","city":"Sunnyside","state":"UT"}
  25. {"index":{"_id":"63"}}
  26. {"account_number":63,"balance":6077,"firstname":"Hughes","lastname":"Owens","age":30,"gender":"F","address":"510 Sedgwick Street","employer":"Valpreal","email":"hughesowens@valpreal.com","city":"Guilford","state":"KS"}
  27. {"index":{"_id":"68"}}
  28. {"account_number":68,"balance":44214,"firstname":"Hall","lastname":"Key","age":25,"gender":"F","address":"927 Bay Parkway","employer":"Eventex","email":"hallkey@eventex.com","city":"Shawmut","state":"CA"}
  29. {"index":{"_id":"70"}}
  30. {"account_number":70,"balance":38172,"firstname":"Deidre","lastname":"Thompson","age":33,"gender":"F","address":"685 School Lane","employer":"Netplode","email":"deidrethompson@netplode.com","city":"Chestnut","state":"GA"}
  31. {"index":{"_id":"75"}}
  32. {"account_number":75,"balance":40500,"firstname":"Sandoval","lastname":"Kramer","age":22,"gender":"F","address":"166 Irvington Place","employer":"Overfork","email":"sandovalkramer@overfork.com","city":"Limestone","state":"NH"}
  33. {"index":{"_id":"82"}}
  34. {"account_number":82,"balance":41412,"firstname":"Concetta","lastname":"Barnes","age":39,"gender":"F","address":"195 Bayview Place","employer":"Fitcore","email":"concettabarnes@fitcore.com","city":"Summerfield","state":"NC"}
  35. {"index":{"_id":"87"}}
  36. {"account_number":87,"balance":1133,"firstname":"Hewitt","lastname":"Kidd","age":22,"gender":"M","address":"446 Halleck Street","employer":"Isologics","email":"hewittkidd@isologics.com","city":"Coalmont","state":"ME"}
  37. {"index":{"_id":"94"}}
  38. {"account_number":94,"balance":41060,"firstname":"Brittany","lastname":"Cabrera","age":30,"gender":"F","address":"183 Kathleen Court","employer":"Mixers","email":"brittanycabrera@mixers.com","city":"Cornucopia","state":"AZ"}
  39. {"index":{"_id":"99"}}
  40. {"account_number":99,"balance":47159,"firstname":"Ratliff","lastname":"Heath","age":39,"gender":"F","address":"806 Rockwell Place","employer":"Zappix","email":"ratliffheath@zappix.com","city":"Shaft","state":"ND"}
  41. {"index":{"_id":"102"}}
  42. {"account_number":102,"balance":29712,"firstname":"Dena","lastname":"Olson","age":27,"gender":"F","address":"759 Newkirk Avenue","employer":"Hinway","email":"denaolson@hinway.com","city":"Choctaw","state":"NJ"}
  43. {"index":{"_id":"107"}}
  44. {"account_number":107,"balance":48844,"firstname":"Randi","lastname":"Rich","age":28,"gender":"M","address":"694 Jefferson Street","employer":"Netplax","email":"randirich@netplax.com","city":"Bellfountain","state":"SC"}
  45. {"index":{"_id":"114"}}
  46. {"account_number":114,"balance":43045,"firstname":"Josephine","lastname":"Joseph","age":31,"gender":"F","address":"451 Oriental Court","employer":"Turnabout","email":"josephinejoseph@turnabout.com","city":"Sedley","state":"AL"}
  47. {"index":{"_id":"119"}}
  48. {"account_number":119,"balance":49222,"firstname":"Laverne","lastname":"Johnson","age":28,"gender":"F","address":"302 Howard Place","employer":"Senmei","email":"lavernejohnson@senmei.com","city":"Herlong","state":"DC"}
  49. {"index":{"_id":"121"}}
  50. {"account_number":121,"balance":19594,"firstname":"Acevedo","lastname":"Dorsey","age":32,"gender":"M","address":"479 Nova Court","employer":"Netropic","email":"acevedodorsey@netropic.com","city":"Islandia","state":"CT"}
  51. {"index":{"_id":"126"}}
  52. {"account_number":126,"balance":3607,"firstname":"Effie","lastname":"Gates","age":39,"gender":"F","address":"620 National Drive","employer":"Digitalus","email":"effiegates@digitalus.com","city":"Blodgett","state":"MD"}
  53. {"index":{"_id":"133"}}
  54. {"account_number":133,"balance":26135,"firstname":"Deena","lastname":"Richmond","age":36,"gender":"F","address":"646 Underhill Avenue","employer":"Sunclipse","email":"deenarichmond@sunclipse.com","city":"Austinburg","state":"SC"}
  55. {"index":{"_id":"138"}}
  56. {"account_number":138,"balance":9006,"firstname":"Daniel","lastname":"Arnold","age":39,"gender":"F","address":"422 Malbone Street","employer":"Ecstasia","email":"danielarnold@ecstasia.com","city":"Gardiner","state":"MO"}
  57. {"index":{"_id":"140"}}
  58. {"account_number":140,"balance":26696,"firstname":"Cotton","lastname":"Christensen","age":32,"gender":"M","address":"878 Schermerhorn Street","employer":"Prowaste","email":"cottonchristensen@prowaste.com","city":"Mayfair","state":"LA"}
  59. {"index":{"_id":"145"}}
  60. {"account_number":145,"balance":47406,"firstname":"Rowena","lastname":"Wilkinson","age":32,"gender":"M","address":"891 Elton Street","employer":"Asimiline","email":"rowenawilkinson@asimiline.com","city":"Ripley","state":"NH"}
  61. {"index":{"_id":"152"}}
  62. {"account_number":152,"balance":8088,"firstname":"Wolfe","lastname":"Rocha","age":21,"gender":"M","address":"457 Guernsey Street","employer":"Hivedom","email":"wolferocha@hivedom.com","city":"Adelino","state":"MS"}
  63. {"index":{"_id":"157"}}
  64. {"account_number":157,"balance":39868,"firstname":"Claudia","lastname":"Terry","age":20,"gender":"F","address":"132 Gunnison Court","employer":"Lumbrex","email":"claudiaterry@lumbrex.com","city":"Castleton","state":"MD"}
  65. {"index":{"_id":"164"}}
  66. {"account_number":164,"balance":9101,"firstname":"Cummings","lastname":"Little","age":26,"gender":"F","address":"308 Schaefer Street","employer":"Comtrak","email":"cummingslittle@comtrak.com","city":"Chaparrito","state":"WI"}
  67. {"index":{"_id":"169"}}
  68. {"account_number":169,"balance":45953,"firstname":"Hollie","lastname":"Osborn","age":34,"gender":"M","address":"671 Seaview Court","employer":"Musaphics","email":"hollieosborn@musaphics.com","city":"Hanover","state":"GA"}
  69. {"index":{"_id":"171"}}
  70. {"account_number":171,"balance":7091,"firstname":"Nelda","lastname":"Hopper","age":39,"gender":"M","address":"742 Prospect Place","employer":"Equicom","email":"neldahopper@equicom.com","city":"Finderne","state":"SC"}
  71. {"index":{"_id":"176"}}
  72. {"account_number":176,"balance":18607,"firstname":"Kemp","lastname":"Walters","age":28,"gender":"F","address":"906 Howard Avenue","employer":"Eyewax","email":"kempwalters@eyewax.com","city":"Why","state":"KY"}
  73. {"index":{"_id":"183"}}
  74. {"account_number":183,"balance":14223,"firstname":"Hudson","lastname":"English","age":26,"gender":"F","address":"823 Herkimer Place","employer":"Xinware","email":"hudsonenglish@xinware.com","city":"Robbins","state":"ND"}
  75. {"index":{"_id":"188"}}
  76. {"account_number":188,"balance":41504,"firstname":"Tia","lastname":"Miranda","age":24,"gender":"F","address":"583 Ainslie Street","employer":"Jasper","email":"tiamiranda@jasper.com","city":"Summerset","state":"UT"}
  77. {"index":{"_id":"190"}}
  78. {"account_number":190,"balance":3150,"firstname":"Blake","lastname":"Davidson","age":30,"gender":"F","address":"636 Diamond Street","employer":"Quantasis","email":"blakedavidson@quantasis.com","city":"Crumpler","state":"KY"}
  79. {"index":{"_id":"195"}}
  80. {"account_number":195,"balance":5025,"firstname":"Kaye","lastname":"Gibson","age":31,"gender":"M","address":"955 Hopkins Street","employer":"Zork","email":"kayegibson@zork.com","city":"Ola","state":"WY"}
  81. {"index":{"_id":"203"}}
  82. {"account_number":203,"balance":21890,"firstname":"Eve","lastname":"Wyatt","age":33,"gender":"M","address":"435 Furman Street","employer":"Assitia","email":"evewyatt@assitia.com","city":"Jamestown","state":"MN"}
  83. {"index":{"_id":"208"}}
  84. {"account_number":208,"balance":40760,"firstname":"Garcia","lastname":"Hess","age":26,"gender":"F","address":"810 Nostrand Avenue","employer":"Quiltigen","email":"garciahess@quiltigen.com","city":"Brooktrails","state":"GA"}
  85. {"index":{"_id":"210"}}
  86. {"account_number":210,"balance":33946,"firstname":"Cherry","lastname":"Carey","age":24,"gender":"M","address":"539 Tiffany Place","employer":"Martgo","email":"cherrycarey@martgo.com","city":"Fairacres","state":"AK"}
  87. {"index":{"_id":"215"}}
  88. {"account_number":215,"balance":37427,"firstname":"Copeland","lastname":"Solomon","age":20,"gender":"M","address":"741 McDonald Avenue","employer":"Recognia","email":"copelandsolomon@recognia.com","city":"Edmund","state":"ME"}
  89. {"index":{"_id":"222"}}
  90. {"account_number":222,"balance":14764,"firstname":"Rachelle","lastname":"Rice","age":36,"gender":"M","address":"333 Narrows Avenue","employer":"Enaut","email":"rachellerice@enaut.com","city":"Wright","state":"AZ"}
  91. {"index":{"_id":"227"}}
  92. {"account_number":227,"balance":19780,"firstname":"Coleman","lastname":"Berg","age":22,"gender":"M","address":"776 Little Street","employer":"Exoteric","email":"colemanberg@exoteric.com","city":"Eagleville","state":"WV"}
  93. {"index":{"_id":"234"}}
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  1904. {"account_number":755,"balance":43878,"firstname":"Bartlett","lastname":"Conway","age":22,"gender":"M","address":"453 Times Placez","employer":"Konnect","email":"bartlettconway@konnect.com","city":"Belva","state":"VT"}
  1905. {"index":{"_id":"762"}}
  1906. {"account_number":762,"balance":10291,"firstname":"Amanda","lastname":"Head","age":20,"gender":"F","address":"990 Ocean Parkway","employer":"Zentury","email":"amandahead@zentury.com","city":"Hegins","state":"AR"}
  1907. {"index":{"_id":"767"}}
  1908. {"account_number":767,"balance":26220,"firstname":"Anthony","lastname":"Sutton","age":27,"gender":"F","address":"179 Fayette Street","employer":"Xiix","email":"anthonysutton@xiix.com","city":"Iberia","state":"TN"}
  1909. {"index":{"_id":"774"}}
  1910. {"account_number":774,"balance":35287,"firstname":"Lynnette","lastname":"Alvarez","age":38,"gender":"F","address":"991 Brightwater Avenue","employer":"Gink","email":"lynnettealvarez@gink.com","city":"Leola","state":"NC"}
  1911. {"index":{"_id":"779"}}
  1912. {"account_number":779,"balance":40983,"firstname":"Maggie","lastname":"Pace","age":32,"gender":"F","address":"104 Harbor Court","employer":"Bulljuice","email":"maggiepace@bulljuice.com","city":"Floris","state":"MA"}
  1913. {"index":{"_id":"781"}}
  1914. {"account_number":781,"balance":29961,"firstname":"Sanford","lastname":"Mullen","age":26,"gender":"F","address":"879 Dover Street","employer":"Zanity","email":"sanfordmullen@zanity.com","city":"Martinez","state":"TX"}
  1915. {"index":{"_id":"786"}}
  1916. {"account_number":786,"balance":3024,"firstname":"Rene","lastname":"Vang","age":33,"gender":"M","address":"506 Randolph Street","employer":"Isopop","email":"renevang@isopop.com","city":"Vienna","state":"NJ"}
  1917. {"index":{"_id":"793"}}
  1918. {"account_number":793,"balance":16911,"firstname":"Alford","lastname":"Compton","age":36,"gender":"M","address":"186 Veronica Place","employer":"Zyple","email":"alfordcompton@zyple.com","city":"Sugartown","state":"AK"}
  1919. {"index":{"_id":"798"}}
  1920. {"account_number":798,"balance":3165,"firstname":"Catherine","lastname":"Ward","age":30,"gender":"F","address":"325 Burnett Street","employer":"Dreamia","email":"catherineward@dreamia.com","city":"Glenbrook","state":"SD"}
  1921. {"index":{"_id":"801"}}
  1922. {"account_number":801,"balance":14954,"firstname":"Molly","lastname":"Maldonado","age":37,"gender":"M","address":"518 Maple Avenue","employer":"Straloy","email":"mollymaldonado@straloy.com","city":"Hebron","state":"WI"}
  1923. {"index":{"_id":"806"}}
  1924. {"account_number":806,"balance":36492,"firstname":"Carson","lastname":"Riddle","age":31,"gender":"M","address":"984 Lois Avenue","employer":"Terrago","email":"carsonriddle@terrago.com","city":"Leland","state":"MN"}
  1925. {"index":{"_id":"813"}}
  1926. {"account_number":813,"balance":30833,"firstname":"Ebony","lastname":"Bishop","age":20,"gender":"M","address":"487 Ridge Court","employer":"Optique","email":"ebonybishop@optique.com","city":"Fairmount","state":"WA"}
  1927. {"index":{"_id":"818"}}
  1928. {"account_number":818,"balance":24433,"firstname":"Espinoza","lastname":"Petersen","age":26,"gender":"M","address":"641 Glenwood Road","employer":"Futurity","email":"espinozapetersen@futurity.com","city":"Floriston","state":"MD"}
  1929. {"index":{"_id":"820"}}
  1930. {"account_number":820,"balance":1011,"firstname":"Shepard","lastname":"Ramsey","age":24,"gender":"F","address":"806 Village Court","employer":"Mantro","email":"shepardramsey@mantro.com","city":"Tibbie","state":"NV"}
  1931. {"index":{"_id":"825"}}
  1932. {"account_number":825,"balance":49000,"firstname":"Terra","lastname":"Witt","age":21,"gender":"F","address":"590 Conway Street","employer":"Insectus","email":"terrawitt@insectus.com","city":"Forbestown","state":"AR"}
  1933. {"index":{"_id":"832"}}
  1934. {"account_number":832,"balance":8582,"firstname":"Laura","lastname":"Gibbs","age":39,"gender":"F","address":"511 Osborn Street","employer":"Corepan","email":"lauragibbs@corepan.com","city":"Worcester","state":"KS"}
  1935. {"index":{"_id":"837"}}
  1936. {"account_number":837,"balance":14485,"firstname":"Amy","lastname":"Villarreal","age":35,"gender":"M","address":"381 Stillwell Place","employer":"Fleetmix","email":"amyvillarreal@fleetmix.com","city":"Sanford","state":"IA"}
  1937. {"index":{"_id":"844"}}
  1938. {"account_number":844,"balance":26840,"firstname":"Jill","lastname":"David","age":31,"gender":"M","address":"346 Legion Street","employer":"Zytrax","email":"jilldavid@zytrax.com","city":"Saticoy","state":"SC"}
  1939. {"index":{"_id":"849"}}
  1940. {"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"}
  1941. {"index":{"_id":"851"}}
  1942. {"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"}
  1943. {"index":{"_id":"856"}}
  1944. {"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"}
  1945. {"index":{"_id":"863"}}
  1946. {"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"}
  1947. {"index":{"_id":"868"}}
  1948. {"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"}
  1949. {"index":{"_id":"870"}}
  1950. {"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"}
  1951. {"index":{"_id":"875"}}
  1952. {"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"}
  1953. {"index":{"_id":"882"}}
  1954. {"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"}
  1955. {"index":{"_id":"887"}}
  1956. {"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"}
  1957. {"index":{"_id":"894"}}
  1958. {"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"}
  1959. {"index":{"_id":"899"}}
  1960. {"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"}
  1961. {"index":{"_id":"902"}}
  1962. {"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"}
  1963. {"index":{"_id":"907"}}
  1964. {"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"}
  1965. {"index":{"_id":"914"}}
  1966. {"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"}
  1967. {"index":{"_id":"919"}}
  1968. {"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"}
  1969. {"index":{"_id":"921"}}
  1970. {"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"}
  1971. {"index":{"_id":"926"}}
  1972. {"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"}
  1973. {"index":{"_id":"933"}}
  1974. {"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"}
  1975. {"index":{"_id":"938"}}
  1976. {"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"}
  1977. {"index":{"_id":"940"}}
  1978. {"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"}
  1979. {"index":{"_id":"945"}}
  1980. {"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"}
  1981. {"index":{"_id":"952"}}
  1982. {"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"}
  1983. {"index":{"_id":"957"}}
  1984. {"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"}
  1985. {"index":{"_id":"964"}}
  1986. {"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"}
  1987. {"index":{"_id":"969"}}
  1988. {"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"}
  1989. {"index":{"_id":"971"}}
  1990. {"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"}
  1991. {"index":{"_id":"976"}}
  1992. {"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"}
  1993. {"index":{"_id":"983"}}
  1994. {"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"}
  1995. {"index":{"_id":"988"}}
  1996. {"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"}
  1997. {"index":{"_id":"990"}}
  1998. {"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"}
  1999. {"index":{"_id":"995"}}
  2000. {"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"}

插入成功:
image.png
这时,我们调用/_cat/indices接口,可以获取到当前所有的索引信息:
image.png

3.3 复杂检索

3.3.1 SearchAPI

ES 支持两种基本方式检索 :

  • 一个是通过使用 REST request URI 发送搜索参数(uri+检索参数)
  • 另一个是通过使用 REST request body 来发送它们(uri+请求体)
  1. 一切检索从_search开始:
  • GET bank/_search:检索 bank 下所有信息,包括 type 和 docs
    • image.png
  • GET bank/_search?q=*&sort=account_number:asc:请求参数方式检索
    • image.png

响应结果解释:

  • took - Elasticsearch 执行搜索的时间(毫秒)
  • time_out - 告诉我们搜索是否超时
  • _shards - 告诉我们多少个分片被搜索了,以及统计了成功/失败的搜索分片
  • hits - 搜索结果
  • hits.total - 搜索结果
  • hits.hits - 实际的搜索结果数组(默认为前 10 的文档)
  • sort - 结果的排序 key(键)(没有则按 score 排序)
  • scoremax_score –相关性得分和最高得分(全文检索用)
  1. uri + 请求体进行检索
    GET bank/_search 
    { 
    "query": { 
     "match_all": {} 
    },
    "sort": [ 
     { 
       "account_number": { 
         "order": "desc" 
       } 
     } 
    ] 
    }
    
    image.png
    HTTP 客户端工具,get 请求不能携带请求体,我们变为 post 也是一样的 我们 POST 一个 JSON 风格的查询请求体到 _search API。 需要了解,一旦搜索的结果被返回,Elasticsearch 就完成了这次请求,并且不会维护任何 服务端的资源或者结果的 cursor(游标)。

3.3.2 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。

  1. 一个查询语句的典型结构

    { 
    QUERY_NAME: { 
    ARGUMENT: VALUE, 
    ARGUMENT: VALUE,... 
    } 
    }
    
  2. 如果是针对某个字段,那么它的结构如下:

    { 
    QUERY_NAME: { 
    FIELD_NAME: { 
    ARGUMENT: VALUE, 
    ARGUMENT: VALUE,... 
    } 
    } 
    }
    
  3. 示例

    GET bank/_search 
    { 
    "query": { 
    "match_all": {} 
    },
    "from": 0, 
    "size": 5, 
    "sort": [ 
    { 
    "account_number": { 
      "order": "desc" 
    } 
    } 
    ] 
    }
    

    image.png
    image.png
    query 定义如何查询:

  • match_all 查询类型【代表查询所有的所有】,es中可以在 query 中组合非常多的查询类型完成复杂查询
  • 除了 query 参数之外,我们也可以传递其它的参数以改变查询结果。如 sort,size
  • from+size 限定,完成分页功能
  • sort 排序,多字段排序,会在前序字段相等时后续字段内部排序,否则以前序为准

2. 返回部分字段

通过_source来指定返回的字段。

GET bank/_search 
{ 
  "query": {
    "match_all": {} 
  },
  "from": 0, 
  "size": 5, 
  "_source": ["age","balance"] 
}

image.png

3. 匹配查询 match
  1. 基本类型(非字符串),精确匹配

match 返回 account_number=20 的:

GET bank/_search
{ 
  "query": { 
    "match": { 
      "account_number": 20 
    } 
  } 
}

image.png

  1. 字符串,全文检索

    GET bank/_search 
    { 
    "query": { 
     "match": { 
       "address": "mill" 
     } 
    } 
    }
    

    image.png
    最终查询出 address 中包含 mill 单词的所有记录 match 当搜索字符串类型的时候,会进行全文检索,并且每条记录有相关性得分。

  2. 字符串,多个单词(分词+全文检索)

    GET bank/_search 
    { 
    "query": { 
     "match": { 
       "address": "mill road" 
     } 
    } 
    }
    

    最终查询出 address 中包含 mill 或者 road 或者 mill road 的所有记录,并给出相关性得分。

4. 短语匹配 match_phrase

将需要匹配的值当成一个整体单词(不分词)进行检索。

GET bank/_search 
{ 
  "query": { 
    "match_phrase": { 
      "address": "mill road" 
    } 
  } 
}

查出 address 中包含 mill road 的所有记录,并给出相关性得分。
image.png

5. 多字段匹配 multi_match
GET bank/_search 
{ 
  "query": { 
    "multi_match": { 
      "query": "mill", 
      "fields": ["state","address"] 
    } 
  } 
}

image.png

6. 复合查询 bool

bool 用来做复合查询: 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。

1. must

必须达到 must 列举的所有条件。

GET bank/_search 
{ 
  "query": { 
    "bool": { 
      "must": [ 
        { 
          "match": { 
            "address": "mill" 
          } 
        },
        { 
          "match": { 
            "gender": "M" 
          } 
        } 
      ] 
    } 
  } 
}

2. 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。

GET bank/_search 
{ 
  "query": { 
    "bool": { 
      "must": [ 
        { 
          "match": { 
            "address": "mill" 
          } 
        }, 
        { 
          "match": { 
            "gender": "M" 
          } 
        } 
      ],
      "should": [ 
        {
          "match": { 
            "address": "lane" 
          }
        } 
      ] 
    } 
  } 
}

3. must_not

必须不是指定的情况。

GET bank/_search 
{ 
  "query": { 
    "bool": { 
      "must": [ 
        { 
          "match": { 
            "address": "mill" 
          } 
        }, 
        { 
          "match": { 
            "gender": "M" 
          } 
        } 
      ],
      "should": [ 
        {
          "match": { 
            "address": "lane" 
          }
        } 
      ],
      "must_not": [ 
        {
          "match": { 
            "email": "baluba.com" 
          }
        } 
      ] 
    } 
  }
}

address 包含 mill,并且 gender 是 M,如果 address 里面有 lane 最好不过,但是 email 必 须不包含 baluba.com。
image.png

7. 结果过滤 filter

并不是所有的查询都需要产生分数,特别是那些仅用于 “filtering”(过滤)的文档。为了不 计算分数 Elasticsearch 会自动检查场景并且优化查询的执行。

GET bank/_search 
{ 
  "query": { 
    "bool": { 
      "must": [ 
        {
          "match": { 
            "address": "mill"
          }
        } 
      ],
      "filter": { 
        "range": { 
          "balance": { 
            "gte": 10000, 
            "lte": 20000 
          } 
        }
      } 
    } 
  } 
}

image.png

8. 精确匹配 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
image.png

GET bank/_search 
{ 
  "query": { 
    "bool": { 
      "must": [ 
        {
          "term": { 
            "age": { 
              "value": "28" 
            } 
          }
        }, 
        {
          "match": { 
            "address": "990 Mill Road" 
          }
        } 
      ] 
    } 
  } 
}

使用term为精确匹配且不分词:
image.png
使用match_phrase虽不分词,但可以部分匹配:
image.png

9. 执行聚合 aggregations

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。

  1. 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。
GET bank/_search
{
  "query": {
    "match": {
      "address": "mill"
    }
  },
  "aggs": {
    "ageAgg": {
      "terms": {
        "field": "age",
        "size": 10
      }
    },
    "ageAvg": {
      "avg": {
        "field": "age"
      }
    }
  },
  "size": 0
}

image.png
语法分析:

size:0 不显示搜索数据 

aggs:执行聚合。聚合语法如下 

"aggs": { 
  "aggs_name 这次聚合的名字,方便展示在结果集中": { 
    "AGG_TYPE 聚合的类型(avg,term,terms)": {} 
  } 
}
  1. 按照年龄聚合,并且请求这些年龄段的这些人的平均薪资

    GET bank/_search
    {
    "query": {
     "match_all": {}
    },
    "aggs": {
     "ageAgg": {
       "terms": {
         "field": "age",
         "size": 100
       },
       "aggs": {
         "salaryAgg": {
           "avg": {
             "field": "balance"
           }
         }
       }
     }
    },
    "size": 0
    }
    

    image.png

  2. 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

    GET bank/_search
    {
    "query": {
     "match_all": {}
    },
    "aggs": {
     "ageAgg": {
       "terms": {
         "field": "age",
         "size": 100
       },
       "aggs": {
         "genderAgg": {
           "terms": {
             "field": "gender.keyword",
             "size": 10
           },
           "aggs": {
             "balanceAgg": {
               "avg": {
                 "field": "balance"
               }
             }
           }
         },
         "ageBalanceAgg": {
           "avg": {
             "field": "balance"
           }
         }
       }
     }
    },
    "size": 0
    }
    

    image.png

3.3.3 Mapping

1. 字段类型

image.pngimage.pngimage.png
image.png
image.png

2. 映射

Mapping(映射)
Mapping 是用来定义一个文档(document),以及它所包含的属性(field)是如何存储和索引的。

比如,使用 mapping 来定义:

  • 哪些字符串属性应该被看做全文本属性(full text fields)。
  • 哪些属性包含数字,日期或者地理位置。
  • 文档中的所有属性是否都能被索引(_all 配置)。
  • 日期的格式。
  • 自定义映射规则来执行动态添加属性。
  1. 查看映射信息

    GET bank/_mapping
    

    image.png

  2. 修改 mapping 信息

https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html
自动猜测的映射类型:
image.png

3. 新版本改变

Es7 及以上移除了 type 的概念。

关系型数据库中两个数据表示是独立的,即使他们里面有相同名称的列也不影响使用,
但 ES 中不是这样的。elasticsearch 是基于 Lucene 开发的搜索引擎,而 ES 中不同 type
下名称相同的 filed 最终在 Lucene 中的处理方式是一样的。

  • 两个不同 type 下的两个 user_name,在 ES 同一个索引下其实被认为是同一个 filed,

你必须在两个不同的 type 中定义相同的 filed 映射。否则,不同 type 中的相同字段
名称就会在处理中出现冲突的情况,导致 Lucene 处理效率下降。

  • 去掉 type 就是为了提高 ES 处理数据的效率。

Elasticsearch 7.x

  • URL 中的 type 参数为可选。比如,索引一个文档不再要求提供文档类型。

Elasticsearch 8.x

  • 不再支持 URL 中的 type 参数。

解决:

  • 将索引从多类型迁移到单类型,每种类型文档一个独立索引
  • 将已存在的索引下的类型数据,全部迁移到指定位置即可。详见数据迁移

4. 创建映射
PUT /my_index
{
  "mappings": {
    "properties": {
      "age": {
        "type": "integer"
      },
      "name": {
        "type": "text"
      },
      "email": {
        "type": "keyword"
      }
    }
  }
}

image.png

5. 添加新的字段映射
PUT /my_index/_mapping
{
  "properties": {
    "employee-id": {
      "type": "long",
      "index": false
    }
  }
}

image.png

6. 更细映射

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。

7. 数据迁移

先创建出 新索引 的正确映射。然后使用如下方式进行数据迁移:

POST _reindex [固定写法] 
{ 
  "source": { 
    "index": "twitter" 
  },
  "dest": { 
    "index": "new_twitter" 
  } 
}
若是旧索引,包含type,则需要用下面的方式来做迁移:
POST _reindex 
{ 
  "source": {
    "index": "twitter", 
    "type": "tweet" 
  },
  "dest": { 
    "index": "tweets" 
  } 
}

示例:
创建了新索引:

PUT newbank
{
  "mappings": {
    "properties": {
      "account_number" : {
          "type" : "long"
        },
        "address" : {
          "type" : "text"
        },
        "age" : {
          "type" : "integer"
        },
        "balance" : {
          "type" : "long"
        },
        "city" : {
          "type" : "keyword"
        },
        "email" : {
          "type" : "keyword"
        },
        "employer" : {
          "type" : "keyword"
        },
        "firstname" : {
          "type" : "text"
        },
        "gender" : {
          "type" : "keyword"
        },
        "lastname" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        },
        "state" : {
          "type" : "text"
        }
    }
  }
}

image.png

查看老索引:<br />![image.png](https://cdn.nlark.com/yuque/0/2022/png/22365594/1648285009197-7875c1fa-4b57-4331-bd7d-d2c3a0505358.png#clientId=uf939de05-9574-4&crop=0&crop=0&crop=1&crop=1&from=paste&height=734&id=ucdc2f26f&margin=%5Bobject%20Object%5D&name=image.png&originHeight=734&originWidth=556&originalType=binary&ratio=1&rotation=0&showTitle=false&size=51774&status=done&style=none&taskId=u67ac7d58-817c-4b1e-91a6-9b014df442d&title=&width=556)

数据迁移:

POST _reindex
{
  "source": {
    "index": "bank",
    "type": "account"
  },
  "dest": {
    "index": "newbank"
  }
}

image.png

查询迁移后的索引:

GET newbank/_search
{
  "query": {
    "match_all": {}
  }
}

image.png

3.4 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)。

3.4.1 安装ik分词器

注意:不能用默认 elasticsearch-plugin install xxx.zip 进行自动安装。

访问 https://github.com/medcl/elasticsearch-analysis-ik/releases?after=v6.4.2 ,找到对应 es 版本的ik分词器,下载并解压到挂载目录plugins

可以进入容器内部,查看系统的插件列表,获取所安装的分词器:

docker exec -it elasticsearch742 /bin/bash

cd ../bin

elasticsearch-plugin list

image.png

3.4.2 测试分词器

默认使用系统自带的标准分词器,对中文分词不友好:

GET _analyze
{
  "text": "我是中国人"
}

image.png

我们可以指定使用ik分词器来进行分词:

GET _analyze
{
  "analyzer": "ik_smart",
  "text": "我是中国人"
}

image.png

GET _analyze
{
  "analyzer": "ik_max_word",
  "text": "我是中国人"
}

image.png

3.4.3 自定义词库

  1. 在Nginx的静态资源挂载目录/html下,创建fenci.txt文件作为自定义词库。

在词库中配置乔碧萝关键词:

乔碧萝
殿下
  1. 访问静态文件路径,查看部署情况

乱码,后续解决,但是可访问到:
image.png

  1. 修改ik分词器所在目录下的config/目录中,找到 IKAnalyzer.cfg.xml文件。 ```bash <?xml version=”1.0” encoding=”UTF-8”?> <!DOCTYPE properties SYSTEM “http://java.sun.com/dtd/properties.dtd"> IK Analyzer 扩展配置
```bash
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">
<properties>
    <comment>IK Analyzer 扩展配置</comment>
    <!--用户可以在这里配置自己的扩展字典 -->
    <entry key="ext_dict"></entry>
     <!--用户可以在这里配置自己的扩展停止词字典-->
    <entry key="ext_stopwords"></entry>
    <!--用户可以在这里配置远程扩展字典 -->
    <entry key="remote_ext_dict">http://ip/es/fenci.txt</entry>
    <!--用户可以在这里配置远程扩展停止词字典-->
    <!-- <entry key="remote_ext_stopwords">words_location</entry> -->
</properties>
  1. 重启es,重新使用分词功能
    docker restart elasticsearch742
    
    成功识别到自定义的词库内容:
    GET _analyze
    {
    "analyzer": "ik_smart",
    "text": "乔碧萝殿下"
    }
    
    image.png