docker-compose搭建ES和Kibana环境，并安装IK中文分词插件

为了方便学习elasticsearch，通过docker compose快速搭建环境。没有安装docker和docker compose的小伙伴可以先看关于docker及docker compose的安装
建议：不要使用root用户，最好另外创建用户

目录结构

/---
---home
------docker
---------docker-compose.yml
---------elasticsearch
-------------Dockerfile
-------------config
-----------------elasticsearch.yml
-------------data
-------------logs
-------------plugins
---------kibana
-------------Dockerfile
-------------config
-----------------kibana.yml

配置

Dockerfile for ES
可查看Dockerfile for elasticsearch

FROM docker.elastic.co/elasticsearch/elasticsearch:7.3.0@sha256:8c7075b17918a954e34d71ab1661ea14737429426376d045a23e79c3632346ab

docker-compose.yml

version: "3"
services:
    elasticsearch:
        build: ./elasticsearch
        container_name: "elasticsearch"
        ports:
            - "9200:9200"
            - "9300:9300"
        volumes:
            - "./elasticsearch/data:/usr/share/elasticsearch/data:rw"
            - "./elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml"
            - "./elasticsearch/logs:/user/share/elasticsearch/logs:rw"
            - "./elasticsearch/plugins/ik:/usr/share/elasticsearch/plugins/ik"
    kibana:
        build: ./kibana
        container_name: kibana
        ports:
            - "5601:5601"
        volumes:
            - ./kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml
        depends_on:
            - "elasticsearch"

elasticsearch.yml

discovery.type: "single-node"
bootstrap.memory_lock: true
network.host: 0.0.0.0
http.port: 9200
transport.tcp.port: 9300
path.logs: /usr/share/elasticsearch/logs
http.cors.enabled: true
http.cors.allow-origin: "*"
xpack.security.audit.enabled: true

Dockerfile for kibana
可查看Dockerfile for kibana

FROM docker.elastic.co/kibana/kibana:7.3.0@sha256:f283049e917e678e2cf160e28f0739abf562fe02e9a61b318f840e70c45135de

kibana.yml

# 访问ES的url，根据自己的配置修改
elasticsearch.hosts: "http://elasticsearch:9200"
server.name: kibana
server.host: "0"

指定的配置文件都放到指定位置后，进入docker-compose.yml所在文件夹

cd /home/docker

再执行

docker-compose build
docker-compose up -d

注意

1.启动时有可能会出现java.nio.file.AccessDeniedException
解决办法：是因为对应的文件夹没有相关权限，可以通过

chown linux用户名 elasticsearch安装目录 -R 

需要先切换到root用户才能执行以上命令。
2.max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
解决办法：在 /etc/sysctl.conf文件最后添加一行
vm.max_map_count=262144

安装IK中文分词插件

点击IK分词插件下载，下载zip压缩文件，解压缩到plugins指定的ik文件夹

image.png

注意需要重启es实例

测试

通过访问kibana，在Dev Tools中我们开始测试中文分词插件是否生效：

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

响应结果：

{
  "tokens" : [
    {
      "token" : "你好",
      "start_offset" : 0,
      "end_offset" : 2,
      "type" : "CN_WORD",
      "position" : 0
    },
    {
      "token" : "我",
      "start_offset" : 3,
      "end_offset" : 4,
      "type" : "CN_CHAR",
      "position" : 1
    },
    {
      "token" : "是",
      "start_offset" : 4,
      "end_offset" : 5,
      "type" : "CN_CHAR",
      "position" : 2
    },
    {
      "token" : "中国人",
      "start_offset" : 5,
      "end_offset" : 8,
      "type" : "CN_WORD",
      "position" : 3
    },
    {
      "token" : "中国",
      "start_offset" : 5,
      "end_offset" : 7,
      "type" : "CN_WORD",
      "position" : 4
    },
    {
      "token" : "国人",
      "start_offset" : 6,
      "end_offset" : 8,
      "type" : "CN_WORD",
      "position" : 5
    }
  ]
}

至此，我们就搭建了一个简单的es和kibana环境。