mysql数据同步elasticsearch(es)全文检索容器(Markdown版本)

一、安装ElasticSearch(下面统称es,版本6.0.0,环境windows10)

直接上下载地址:https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.0.0.zip

解压后目录如下:
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启动es,./bin/elasticsearch.bat;启动成功如图

mysql数据同步elasticsearch(es)全文检索容器(Markdown版本)_第2张图片
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默认cluster_name是elasticsearch和端口9200可以修改,需要修改在config/elasticsearch.yml;上图

mysql数据同步elasticsearch(es)全文检索容器(Markdown版本)_第3张图片
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二、安装logstash

下载地址:https://artifacts.elastic.co/downloads/logstash/logstash-6.0.0.zip

解压目录
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先安装logstash-input-jdbc插件
./bin/logstash-plugin.bat install logstash-input-jdbc

5

在logstash目录下创建config-mysql,见图4

mysql数据同步elasticsearch(es)全文检索容器(Markdown版本)_第5张图片
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创建配置文件load_data.conf,配置文件随便取名,可以创建sql文件,也可以在conf配置文件中定义,具体下面有说明

先上配置文件内容
input {
    stdin {
    }
    jdbc {
      jdbc_connection_string => "jdbc:mysql://127.0.0.1:3306/jfinal_club?characterEncoding=utf8&useSSL=false"
      jdbc_user => "root"
      jdbc_password => "root"
      jdbc_driver_library => "D:/ELK/6.0.0/logstash-6.0.0/config-mysql/mysql-connector-java-5.1.43.jar"
      jdbc_driver_class => "com.mysql.jdbc.Driver"
      jdbc_paging_enabled => "true"
      jdbc_page_size => "50000"
      statement_filepath => "D:/ELK/6.0.0/logstash-6.0.0/config-mysql/store_list.sql"
      schedule => "* * * * *"
      use_column_value => false
      record_last_run => true
      last_run_metadata_path => "D:/ELK/6.0.0/logstash-6.0.0/config-mysql/run/store_list"
      type => "sl"
    }

jdbc {
      jdbc_connection_string => "jdbc:mysql://127.0.0.1:3306/jfinal_club?characterEncoding=utf8&useSSL=false"
      jdbc_user => "root"
      jdbc_password => "root"
      jdbc_driver_library => "D:/ELK/6.0.0/logstash-6.0.0/config-mysql/mysql-connector-java-5.1.43.jar"
      jdbc_driver_class => "com.mysql.jdbc.Driver"
      jdbc_paging_enabled => "true"
      jdbc_page_size => "50000"
      statement => "select * from store where updated > date_add(:sql_last_value, interval 8 hour)"
      schedule => "* * * * *"
      use_column_value => false
      record_last_run => true
      last_run_metadata_path => "D:/ELK/6.0.0/logstash-6.0.0/config-mysql/run/store_s"
      type => "st"
    }
}

filter {
    json {
        source => "message"
        remove_field => ["message"]
    }
}

output {

    if[type] == "sl"{
        elasticsearch {
              hosts => ["127.0.0.1:9200"]
              index => "store_list"
              document_type => "jdbc"
              document_id => "%{store_id}}"
        }
    }

    if[type] == "st"{
        elasticsearch {
              hosts => ["127.0.0.1:9200"]
              index => "store_st"
              document_type => "jdbc"
              document_id => "%{id}}"
        }
    }

    stdout {
        codec => json_lines
    }
}

字段解释;具体的见:https://www.elastic.co/guide/en/logstash/current/plugins-inputs-jdbc.html

图6中有个run目录,在这里是用来存放:sql_last_value的时间值的
store_list.sql
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先在es中生成index
PUT /store_list
{
    "settings": {
    "number_of_shards": 3,
    "number_of_replicas": 1
  },
  "mappings": {
    "jdbc": {
      "properties": {
        "@timestamp": {
          "type": "date"
        },
        "@version": {
          "type": "keyword"
        },
        "store_id": {
          "type": "long"
        },
        "store_name": {
          "type": "keyword"
        },
        "uid": {
          "type": "text"
        },
        "telephone": {
          "type": "text"
        },
        "street_id": {
          "type": "text"
        },
        "detail": {
          "type": "keyword"
        },
        "address": {
          "type": "keyword"
        },
        "store_created": {
          "type": "date"
        },
        "store_updated": {
          "type": "date"
        },
        "detail_id": {
          "type": "long"
        },
        "type_name": {
          "type": "text"
        },
        "tag": {
          "type": "keyword"
        },
        "overall_rating": {
          "type": "text"
        },
        "navi_location_lng": {
          "type": "double"
        },
        "navi_location_lat": {
          "type": "double"
        },
        "detail_url": {
          "type": "text"
        },
        "comment_num": {
          "type": "integer"
        },
        "detail_created": {
          "type": "date"
        },
        "detail_updated": {
          "type": "date"
        },
        "location_id": {
          "type": "long"
        },
        "lng": {
          "type": "double"
        },
        "lat": {
          "type": "double"
        }
      }
    }
  }
}

上面这种方式可以通过es管理工具执行,比如kibana->dev tools;或者使用curl的方式也可以

curl -XPUT "http://localhost:9200/store_list" -H 'Content-Type: application/json' -d'
{
  "settings": {
    "number_of_shards": 3,
    "number_of_replicas": 1
  },
  "mappings": {
    "jdbc": {
      "properties": {
        "@timestamp": {
          "type": "date"
        },
        "@version": {
          "type": "keyword"
        },
        "store_id": {
          "type": "long"
        },
        "store_name": {
          "type": "keyword"
        },
        "uid": {
          "type": "text"
        },
        "telephone": {
          "type": "text"
        },
        "street_id": {
          "type": "text"
        },
        "detail": {
          "type": "keyword"
        },
        "address": {
          "type": "keyword"
        },
        "store_created": {
          "type": "date"
        },
        "store_updated": {
          "type": "date"
        },
        "detail_id": {
          "type": "long"
        },
        "type_name": {
          "type": "text"
        },
        "tag": {
          "type": "keyword"
        },
        "overall_rating": {
          "type": "text"
        },
        "navi_location_lng": {
          "type": "double"
        },
        "navi_location_lat": {
          "type": "double"
        },
        "detail_url": {
          "type": "text"
        },
        "comment_num": {
          "type": "integer"
        },
        "detail_created": {
          "type": "date"
        },
        "detail_updated": {
          "type": "date"
        },
        "location_id": {
          "type": "long"
        },
        "lng": {
          "type": "double"
        },
        "lat": {
          "type": "double"
        }
      }
    }
  }
}'

然后通过http://localhost:9200/store_list/查看字段生成情况

store_list就是index,相当于数据库的database

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然后回到logstash目录下

执行 nohup.exe ./bin/logstash.bat -f config-mysql/load_data.conf &

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最好加上& 结尾,后台运行

然后看数据库同步情况

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可能有些细节没能写全,如果在集成中遇到什么情况,可以评论指出

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