1. kibana配置ES集群

1.1.新建宿主主机的挂载配置文件:

cd /usr/local
mkdir -p kibana/config
cd kibana
cd config
vi kibana.yml

配置内容如下：

server.port: 5601
server.host: "0.0.0.0"
elasticsearch.hosts: ["http://192.168.10.128:9201","http://192.168.10.128:9200"]

字段解析以及填坑方法：
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1.2.以挂载配置文件的方式启动kibana

docker pull kibana:7.6.1

docker run \
-d -p 5601:5601 \
-v /usr/local/kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml \
--name kibana-cluster kibana:7.6.1

1.3.浏览器访问

访问http://192.168.10.128:5601/app/kibana#/dev_tools/console，可以看到启动成功：
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2. logstash配置ES集群

2.1.新建宿主主机的挂载配置文件:

cd /usr/local
mkdir -p logstash/config
cd logstash
mkdir lib
cd config
vi mysql.conf
vi mysql1.conf
vi pipelines.yml

上传jar包到/user/local/logstash/lib目录下：

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配置：mysql.conf、mysql1.conf、pipelines.yml

mysql.conf内容（注意es集群配置）

input {
  jdbc {
    jdbc_driver_library => "/usr/share/logstash/lib/mysql-connector-java-5.1.17-bin.jar"
    jdbc_driver_class => "com.mysql.jdbc.Driver"
    jdbc_connection_string => "jdbc:mysql://172.81.235.217:3306/guoranxinxian-goods"
    jdbc_user => "root"
    jdbc_password => "bruce_1234"
    schedule => "* * * * *"
    statement => "SELECT * FROM product WHERE UPDATED_TIME > :sql_last_value"
    use_column_value => true
    tracking_column_type => "timestamp"
    tracking_column => "updated_time"
    last_run_metadata_path => "syncpoint_product_table"
  }
}


output {
    elasticsearch {
        hosts => ["192.168.10.128:9200","192.168.10.128:9201"]
        index => "product"
        document_id => "%{id}"
        document_type => "product"
    }
    stdout {
        codec => json_lines
    }
}

mysql1.conf内容（注意es集群配置）

input {
  jdbc {
    jdbc_driver_library => "/usr/share/logstash/lib/mysql-connector-java-5.1.17-bin.jar"
    jdbc_driver_class => "com.mysql.jdbc.Driver"
    jdbc_connection_string => "jdbc:mysql://172.81.235.217:3306/guoranxinxian-goods"
    jdbc_user => "root"
    jdbc_password => "bruce_1234"
    schedule => "* * * * *"
    statement => "SELECT * FROM category WHERE UPDATED_TIME > :sql_last_value"
    use_column_value => true
    tracking_column_type => "timestamp"
    tracking_column => "updated_time"
    last_run_metadata_path => "syncpoint_category_table"
  }
}


output {
    elasticsearch {
        hosts => ["192.168.10.128:9200","192.168.10.128:9201"]
        index => "category"
        document_id => "%{id}"
        document_type => "category"
    }
    stdout {
        codec => json_lines
    }
}

pipelines.yml内容：

- pipeline.id: product_table
  path.config: "/usr/share/logstash/config/mysql.conf"
- pipeline.id: category_table
  path.config: "/usr/share/logstash/config/mysql1.conf"

2.2 以挂载配置文件的方式启动logstash

mysql.conf、mysql1.conf、pipelines.yml

docker run \
-v /usr/local/logstash/lib/mysql-connector-java-5.1.17-bin.jar:/usr/share/logstash/lib/mysql-connector-java-5.1.17-bin.jar \
-v /usr/local/logstash/config/mysql.conf:/usr/share/logstash/config/mysql.conf \
-v /usr/local/logstash/config/mysql1.conf:/usr/share/logstash/config/mysql1.conf \
-v /usr/local/logstash/config/pipelines.yml:/usr/share/logstash/config/pipelines.yml \
-d --name logstash-cluster logstash:7.6.1