Docker 搭建 ES 和 Kibana 8.2.0版本

向右看齐 2023-09-28 10:56 9阅读 0赞

#### Docker 搭建 ES 和 Kibana 8.2.0版本 ####

*  一 镜像拉取和部署
 *   *  1.拉取和启动
     *  2.配置ES密码
     *  3.为Kibana生成签名
     *  4.配置IK分词器
 *  二 ES测试
 *   *  1.基本命令
     *  2.数据添加和查寻
     *  3.分词器演示

## 一 镜像拉取和部署 ##

### 1.拉取和启动 ###

## 1.拉取 Elasticsearch
    docker pull elasticsearch:8.2.0
    ## 2.拉取 Kibana
    docker pull kibana:8.2.0
    ## 3.启动 Elasticsearch
    docker run -it --name elasticsearch --restart=always -d -p 9200:9200 -p 9300:9300 -p 5601:5601 -e "discovery.type=single-node" -e ES_JAVA_OPTS="-Xms1024m -Xmx1024m" -d elasticsearch:8.2.0 
    ## 4.启动 Kibana
    ## --network 指定容器共享elasticsearch容器的网络栈
    docker run -it --name kibana --restart=always -d -e ELASTICSEARCH_URL=http://127.0.0.1:9200  --network=container:elasticsearch kibana:8.2.0

### 2.配置ES密码 ###

## 1.进入容器
    docker exec -it elasticsearch /bin/bash
    ## 2.设置密码命令
    /usr/share/elasticsearch/bin/elasticsearch-setup-passwords interactive

控制台信息

elasticsearch@12d673513b9b:~$ /usr/share/elasticsearch/bin/elasticsearch-setup-passwords interactive
    ******************************************************************************
    Note: The 'elasticsearch-setup-passwords' tool has been deprecated. This       command will be removed in a future release.
    ******************************************************************************
    
    Initiating the setup of passwords for reserved users elastic,apm_system,kibana,kibana_system,logstash_system,beats_system,remote_monitoring_user.
    You will be prompted to enter passwords as the process progresses.
    Please confirm that you would like to continue [y/N]y
    
    
    Enter password for [elastic]:
    Reenter password for [elastic]:
    Enter password for [apm_system]:
    Reenter password for [apm_system]:
    Enter password for [kibana_system]:
    Reenter password for [kibana_system]:
    Enter password for [logstash_system]:
    Reenter password for [logstash_system]:
    Enter password for [beats_system]:
    Reenter password for [beats_system]:
    Enter password for [remote_monitoring_user]:
    Reenter password for [remote_monitoring_user]:
    Changed password for user [apm_system]
    Changed password for user [kibana_system]
    Changed password for user [kibana]
    Changed password for user [logstash_system]
    Changed password for user [beats_system]
    Changed password for user [remote_monitoring_user]
    Changed password for user [elastic]
    elasticsearch@12d673513b9b:~$

![在这里插入图片描述][1e8ace4fe8ef44c48c68dcadb6103799.png]

### 3.为Kibana生成签名 ###

## 1.连接容器
    docker exec -it elasticsearch /bin/bash
    ## 2.生成签名
    /usr/share/elasticsearch/bin/elasticsearch-create-enrollment-token --scope kibana

![在这里插入图片描述][2c4990b9265d46a8b5d2c0fb752f99c2.png]

将签名信息添加到Kibana  
![在这里插入图片描述][51c41152815d4c8885ad4467015461a1.png]

## 1.连接容器
    docker exec -it kibana /bin/bash
    ## 2.生成Code
    bin/kibana-verification-code
    ## 3.汉化：修改容器内：/usr/share/kibana/config/kibana.yml
    ##        增加：i18n.locale: "zh-CN"

![在这里插入图片描述][80474f8163a44793b93dfb85adfe382f.png]  
输入Kibana  
![在这里插入图片描述][507df2ebd91d40988e894f39d8bf8dbf.png]  
开始初始化  
![在这里插入图片描述][80c5bdb9cae84f3a80088835f0e2f317.png]  
登录  
![在这里插入图片描述][dce133666cb148ccb4ade406e6e284c7.png]

### 4.配置IK分词器 ###

## 1.将IK分词器插件拷贝到Elasticsearch容器内
    docker cp elasticsearch-analysis-ik-8.2.0.tar.gz elasticsearch:/usr/share/elasticsearch/plugins/
    ## 2.连接容器
    docker exec -it elasticsearch /bin/bash
    ## 3.解压
    cd plugins/ && tar zxvf elasticsearch-analysis-ik-8.2.0.tar.gz
    ## 4.修改文件夹名称并删除压缩包
    mv elasticsearch-analysis-ik-8.2.0 ik && rm -rf elasticsearch-analysis-ik-8.2.0.tar.gz
    ## 5.重启ES容器
    docker restart elasticsearch
    ## 6.查看已安装分词器
    bin/elasticsearch-plugin list

## 二 ES测试 ##

### 1.基本命令 ###

## 1.查看节点信息
    GET /_cat/nodes?v
    ## 2.查看节点健康状态
    GET _cluster/health
    ## 3.创建索引库
    PUT /moon_db
    ## 4.查寻索引库
    GET /moon_db
    ## 5.删除索引库
    DELETE /moon_db
    ## 6.判断索引库是否存在
    HEAD /moon_db

1.查看节点  
![在这里插入图片描述][315f7c0912c94c6a88f438abb5a5b1f0.png]

2.查看节点健康状态  
![在这里插入图片描述][aa0955f3ff1d41b49790ce6a18d78789.png]

3.创建索引库  
![在这里插入图片描述][3da68d1b4e5a4ad4aebfc1c98572d07a.png]  
4.查寻索引库  
![在这里插入图片描述][52d4aaaffef440e1b7dc91658cf88119.png]

5.删除索引库  
![在这里插入图片描述][f1056990a07048dfbc6162da5efdb829.png]  
6.判断索引库是否存在  
![在这里插入图片描述][d59ae9a256a6407c9508fb7f63481ca0.png]

### 2.数据添加和查寻 ###

## 1.创建索引库时设置分词器、分片数和副本数
    PUT /moon_db
    {
        
      "settings":{
        
        "number_of_shards": 2,
        "number_of_replicas": 2,
        "index":{
        
          "analysis.analyzer.default.type":"ik_max_word"
        }
      }
    }
    ## 2.创建文档
    ##  如果id不存在，创建新的文档，否则先删除现有文档，再创建新的文档，版本会增加
    ##  如果是_create命令，id存在则会报错
    ##  如果用POST命令，带着ID则使用指定ID，否在由ES生成一个ID
    PUT /moon_db/_doc/1
    {
        
      "name":"张三",
      "sex":1,
      "age":18,
      "poem":"连雨不知春去，一晴方觉夏深"
    }
    
    POST /moon_db/_doc/
    {
        
      "name":"孙八",
      "sex":1,
      "age":30,
      "poem":"清江一曲抱村流，长夏江村事事幽"
    }
    ## 3.查寻数据
    GET /moon_db/_doc/1
    ## 4.更新：PUT|POST ID一致相当于全量更新
    ##   部分更新：_update
    POST /moon_db/_update/1
    {
        
      "doc": {
        
        "name":"张三峰"
      }
    }
    ## 5.条件更新： _update_by_query
    ##   如果原文档，无ages属性，则会创建ages，并赋值
    POST /moon_db/_update_by_query
    {
        
      "query": {
        
        "match": {
        
          "_id": "1"
        }
      },
      "script": {
        
        "source": "ctx._source.ages = 30"
      }
    }
    ## 6.并发时读后写版本控制：
    ##   _seq_no:数据序列号，同_version，数据变更时严格递增
    ##   _primary_term:分区版本，主分区重新分配（重启、Primary选举等），版本递增
    PUT /moon_db/_doc/1?if_seq_no=11&if_primary_term=1
    {
        
      "name":"张三峰",
      "age":18,
      "poem":"连雨不知春去，一晴方觉夏深"
    }
    ## 7.条件查询
    GET /moon_db/_search?from=0&size=10
    {
        
      "query": {
        
        "term": {
        
          "age": 30
        }
      }
    }

1.创建库、添加数据、查寻数据  
![在这里插入图片描述][ecb6948983d84a6cb3c0a663c61414ea.png]  
2.用PUT /moon\_db/\_create/id创建文档  
![在这里插入图片描述][15f7b483913844c68e90eee503bf9d22.png]  
3.使用POST创建文档：重复执行则会生成ID不同，数据一致的文档  
![在这里插入图片描述][9ceaaa25dbd24627a7b7a9c604b90915.png]  
4.条件查询  
![在这里插入图片描述][83626cb079ab48f8805ae2ce28adf760.png]

### 3.分词器演示 ###

## 1.创建索引
    PUT /moon_user_n
    {
        
      "mappings": {
        
        "properties": {
        
          "name":{
        
            "type":"text",
            "analyzer":"ik_max_word"
          },
          "age":{
        
            "type":"long"
          }
        }
      }
    }
    ## 2.添加数据
    POST /moon_user_n/_doc/1
    {
        
      "name":"国家",
      "age":12
    }
    
    POST /moon_user_n/_doc/2
    {
        
      "name":"公园",
      "age":12
    }
    
    POST /moon_user_n/_doc/3
    {
        
      "name":"有一家公开教学机构",
      "age":12
    }
    ## 3.条件查寻
    GET /moon_user_n/_search
    {
        
      "query": {
        
        "match": {
        
          "name": "国家公园"
        }
      }
    }
    ## 4.分词分析
    POST _analyze
    {
        
      "analyzer": "ik_max_word",
      "text": "国家公园"
    }

1.查寻结果  
![在这里插入图片描述][c830b3ff61ab4f6cb2265d5908ba0426.png]  
2.分词效果分析  
![在这里插入图片描述][55da5f8d1407499ea33bd8405c545c62.png]

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