Docker 安装 elk(elasticsearch、logstash、kibana)、ES安装ik分词器

前期准备

创建kibana配置文件路径

bash 复制代码

mkdir -p /data/docker/logstash/config

先启动临时 logstash服务，目的拷贝/usr/share/logstash/pipeline/logstash.conf文件

bash 复制代码

# 启动
docker run --name logstash -d docker.elastic.co/logstash/logstash:7.10.1

# 拷贝
docker container cp logstash:/usr/share/logstash/pipeline/logstash.conf /data/docker/logstash/config

# 编辑
vi /data/docker/logstash/config/logstash.conf 

# 停止删除容器
docker rm -f logstash

# 设置权限	
chmod -R 777 /data/docker/logstash

logstash.conf文件配置-参考：https://cloud.tencent.com/developer/article/2355726

nginx 复制代码

input {
  tcp {
    mode => "server"
    host => "0.0.0.0"
    port => 4560
    codec => json
  }
}
output {
  elasticsearch {
    hosts => "elasticsearch:9200"
    index => "logstash-%{+YYYY.MM.dd}"
  }
}

docker执行

bash 复制代码

# 创建一个名为 elk 的桥接网络
docker network create elk
# 启动 Elasticsearch
docker run -d \
  --name elasticsearch \
  --restart always \
  -e TZ=Asia/Shanghai \
  -e node.name=elasticsearch \
  -e cluster.name=es-docker-cluster \
  -e discovery.type=single-node \
  -e bootstrap.memory_lock=true \
  -e ES_JAVA_OPTS=-Xms512m -Xmx512m \
  --ulimit memlock=-1:-1 \
  -v esdata:/usr/share/elasticsearch/data \
  -p 9200:9200 \
  -p 9300:9300 \
  --network elk \
  docker.elastic.co/elasticsearch/elasticsearch:7.10.1

# 启动 Logstash
docker run -d \
  --name logstash \
  --restart always \
  -v /data/docker/logstash/config/logstash.conf:/usr/share/logstash/pipeline/logstash.conf \
  -p 4560:4560 \
  -p 5044:5044 \
  -p 5000:5000/tcp \
  -p 5000:5000/udp \
  -e TZ=Asia/Shanghai \
  -e LS_JAVA_OPTS="-Xmx256m -Xms256m" \
  --network elk \
  docker.elastic.co/logstash/logstash:7.10.1

# 启动 Kibana
docker run -d \
  --name kibana \
  --restart always \
  -e TZ=Asia/Shanghai \
  -e ELASTICSEARCH_URL=http://elasticsearch:9200 \
  -e ELASTICSEARCH_HOSTS=http://elasticsearch:9200 \
  -p 5601:5601 \
  --network elk \
  docker.elastic.co/kibana/kibana:7.10.1

docker-compose执行

docker-compose 文件

yaml 复制代码

version: '3.1'  
services:  
  elasticsearch:  
    image: docker.elastic.co/elasticsearch/elasticsearch:7.10.1  
    container_name: elasticsearch
    restart: always  
    environment:  
      - TZ=Asia/Shanghai
      - node.name=elasticsearch  
      - cluster.name=es-docker-cluster  
      - discovery.type=single-node  
      - bootstrap.memory_lock=true  
      - ES_JAVA_OPTS=-Xms512m -Xmx512m  
    ulimits:  
      memlock:  
        soft: -1  
        hard: -1  
    volumes:  
      - esdata:/usr/share/elasticsearch/data  
    ports:  
      - "9200:9200"  
      - "9300:9300"  
    networks:  
      - elk  
  logstash:  
    image: docker.elastic.co/logstash/logstash:7.10.1  
    container_name: logstash
    restart: always  
    volumes:  
      - /data/docker/logstash/config/logstash.conf:/usr/share/logstash/pipeline/logstash.conf  
    ports:  
      - "4560:4560"
      - "5044:5044"  
      - "5000:5000/tcp"  
      - "5000:5000/udp"  
    environment:  
        TZ: Asia/Shanghai
        LS_JAVA_OPTS: "-Xmx256m -Xms256m"  
    depends_on:  
      - elasticsearch  
    networks:  
      - elk  
  kibana:  
    image: docker.elastic.co/kibana/kibana:7.10.1  
    container_name: kibana
    restart: always  
    environment:  
      TZ: Asia/Shanghai
      ELASTICSEARCH_URL: http://elasticsearch:9200  
      ELASTICSEARCH_HOSTS: http://elasticsearch:9200  
    ports:  
      - "5601:5601"  
    depends_on:  
      - elasticsearch  
    networks:  
      - elk  
  
volumes:  
  esdata:  
    driver: local  
  
networks:  
  elk:  
    driver: bridge

运行docker-comopse命令

bash 复制代码

docker-compose up -d

安装ik分词器

ik分词器地址：https://github.com/infinilabs/analysis-ik

使用官方安装方式：bin/elasticsearch-plugin install https://get.infini.cloud/elasticsearch/analysis-ik/7.10.1

bash 复制代码

# 进入容器
docker exec -it elasticsearch bash

# 安装ik分词器插件
bin/elasticsearch-plugin install https://get.infini.cloud/elasticsearch/analysis-ik/7.10.1

# 重启es
docker restart elasticsearch

验证ik分词器是否安装成功

进入kibana页面devtools页面

输入查询命令：

javascript 复制代码

POST /_analyze
{
  "analyzer": "ik_smart",
  "text":["中国人最牛"]
}