码迷,mamicode.com
首页 > 其他好文 > 详细

[大数据]-Logstash-5.3.1的安装导入数据到Elasticsearch5.3.1并配置同义词过滤

时间:2017-05-23 18:47:20      阅读:2358      评论:0      收藏:0      [点我收藏+]

标签:last   启动   start   索引   img   point   output   keyword   token   

阅读此文请先阅读上文:[大数据]-Elasticsearch5.3.1 IK分词,同义词/联想搜索设置,前面介绍了ES,Kibana5.3.1的安装配置,以及IK分词的安装和同义词设置,这里主要记录Logstash导入mysql数据到Elasticsearch5.3.1并设置IK分词和同义词。由于logstash配置好JDBC,ES连接之后运行脚本一站式创建index,mapping,导入数据。但是如果我们要配置IK分词器就需要修改创建index,mapping的配置,下面详细介绍。

一、Logstash-5.3.1下载安装:

  • 下载:https://www.elastic.co/cn/downloads/logstash
  • 解压:tar -zxf logstash-5.3.1.tar.gz 
  • 启动:bin/logstash -e ‘input { stdin { } } output { stdout {} }‘  (参数表示终端输入输出)如下则成功。
  • Sending Logstash‘s logs to /home/rzxes/logstash-5.3.1/logs which is now configured via log4j2.properties
    [2017-05-16T10:27:36,957][INFO ][logstash.setting.writabledirectory] Creating directory {:setting=>"path.queue", :path=>"/home/rzxes/logstash-5.3.1/data/queue"}
    [2017-05-16T10:27:37,041][INFO ][logstash.agent           ] No persistent UUID file found. Generating new UUID {:uuid=>"c987803c-9b18-4395-bbee-a83a90e6ea60", :path=>"/home/rzxes/logstash-5.3.1/data/uuid"}
    [2017-05-16T10:27:37,581][INFO ][logstash.pipeline        ] Starting pipeline {"id"=>"main", "pipeline.workers"=>1, "pipeline.batch.size"=>125, "pipeline.batch.delay"=>5, "pipeline.max_inflight"=>125}
    [2017-05-16T10:27:37,682][INFO ][logstash.pipeline        ] Pipeline main started
    The stdin plugin is now waiting for input:
    [2017-05-16T10:27:37,886][INFO ][logstash.agent           ] Successfully started Logstash API endpoint {:port=>9600}

二、Logstash-5.3.1连接mysql作为数据源,ES作为数据输出端:

  • 由于此版本的logstash已经集成了jdbc插件,我们只需要添加一个配置文件xxx.conf。内容如下test.conf:
  • input {
        stdin {
        }
        jdbc {
          # 数据库地址  端口  数据库名
          jdbc_connection_string => "jdbc:mysql://IP:3306/dbname"
          # 数据库用户名
          jdbc_user => "user"
          # 数据库密码
          jdbc_password => "pass"
          # mysql java驱动地址
          jdbc_driver_library => "/home/rzxes/logstash-5.3.1/mysql-connector-java-5.1.17.jar"
          jdbc_driver_class => "com.mysql.jdbc.Driver"
          jdbc_paging_enabled => "true"
          jdbc_page_size => "100000"
          # sql 语句文件,也可以直接写SQL,如statement => "select * from table1"
          statement_filepath => "/home/rzxes/logstash-5.3.1/test.sql"
          schedule => "* * * * *"
          type => "jdbc"
        }
    }
    output {
        stdout {
            codec => json_lines
        }
        elasticsearch {
            hosts  => "192.168.230.150:9200"
            index => "test-1" #索引名称
            document_type => "form" #type名称
            document_id => "%{id}" #id必须是待查询的数据表的序列字段
    } }
  • 创建一个SQL文件:如上配置test.sql内容: select * from table1
  • test.conf,test.sql文件都在logstash的根目录下。
  • 运行logstash脚本导入数据: bin/logstash -f test.conf 启动如下;
  • 技术分享
  • 等待数据导入完成。开启Es-head,访问9100端口如下:技术分享
  • 可以看到已经导入了11597条数据。

  • 更多详细的配置参考官方文档:plugins-inputs-jdbc-jdbc_driver_library

三、logstash是如何创建index,mapping,并导入数据?

ES导入数据必须先创建index,mapping,但是在logstash中并没有直接创建,我们只传入了index,type等参数,logstash是通过es的mapping template来创建的,这个模板文件不需要指定字段,就可以根据输入自动生成。在logstash启动的时候这个模板已经输出了如下log:

[2017-05-23T15:58:45,801][WARN ][logstash.outputs.elasticsearch] Restored connection to ES instance {:url=>#<URI::HTTP:0x68f0d43b URL:http://192.168.230.150:9200/>}
[2017-05-23T15:58:45,805][INFO ][logstash.outputs.elasticsearch] Using mapping template from {:path=>nil}
[2017-05-23T15:58:45,979][INFO ][logstash.outputs.elasticsearch] Attempting to install template {:manage_template=>{"template"=>"logstash-*", "version"=>50001, "settings"=>{"index.refresh_interval"=>"5s"}, "mappings"=>{"_default_"=>{"_all"=>{"enabled"=>true, "norms"=>false}, "dynamic_templates"=>[{"message_field"=>{"path_match"=>"message", "match_mapping_type"=>"string", "mapping"=>{"type"=>"text", "norms"=>false}}}, {"string_fields"=>{"match"=>"*", "match_mapping_type"=>"string", "mapping"=>{"type"=>"text", "norms"=>false, "fields"=>{"keyword"=>{"type"=>"keyword"}}}}}], "properties"=>{"@timestamp"=>{"type"=>"date", "include_in_all"=>false}, "@version"=>{"type"=>"keyword", "include_in_all"=>false}, "geoip"=>{"dynamic"=>true, "properties"=>{"ip"=>{"type"=>"ip"}, "location"=>{"type"=>"geo_point"}, "latitude"=>{"type"=>"half_float"}, "longitude"=>{"type"=>"half_float"}}}}}}}}
  • 添加IK分词,只需要创建一个json文件: vim /home/rzxes/logstash-5.3.1/template/logstash.json  添加如下内容:
  • {
        "template": "*",
        "version": 50001,
        "settings": {
            "index.refresh_interval": "5s"
        },
        "mappings": {
            "_default_": {
                "_all": {
                    "enabled": true,
                    "norms": false
                },
                "dynamic_templates": [
                    {
                        "message_field": {
                            "path_match": "message",
                            "match_mapping_type": "string",
                            "mapping": {
                                "type": "text",
                                "norms": false
                            }
                        }
                    },
                    {
                        "string_fields": {
                            "match": "*",
                            "match_mapping_type": "string",
                            "mapping": {
                                "type": "text",
                                "norms": false,
                                "analyzer": "ik_max_word",#只需要添加这一行即可设置分词器为ik_max_word
                                "fields": {
                                    "keyword": {
                                        "type": "keyword"
                                    }
                                }
                            }
                        }
                    }
                ],
                "properties": {
                    "@timestamp": {
                        "type": "date",
                        "include_in_all": false
                    },
                    "@version": {
                        "type": "keyword",
                        "include_in_all": false
                    }
                }
            }
        }
    }
  • 如需配置同义词,需自定义分词器,配置同义词过滤<IK分词同义词详见上一篇文章>。修改模板logstash.json如下:

  • {
        "template" : "*",
        "version" : 50001,
        "settings" : {
            "index.refresh_interval" : "5s",
            #分词,同义词配置:自定义分词器,过滤器,如不配同义词则没有index这一部分
            "index": {
              "analysis": {
                "analyzer": {
                  "by_smart": {
                    "type": "custom",
                    "tokenizer": "ik_smart",
                    "filter": ["by_tfr","by_sfr"],
                    "char_filter": ["by_cfr"]
                  },
                  "by_max_word": {
                    "type": "custom",
                    "tokenizer": "ik_max_word",
                    "filter": ["by_tfr","by_sfr"],
                    "char_filter": ["by_cfr"]
                  }
                },
                "filter": {
                  "by_tfr": {
                    "type": "stop",
                    "stopwords": [" "]
                  },
                  "by_sfr": {
                    "type": "synonym",
                    "synonyms_path": "analysis/synonyms.txt" #同义词路径
                  }
                },
                "char_filter": {
                  "by_cfr": {
                    "type": "mapping",
                    "mappings": ["| => |"]
                  }
                }
              }
            } # index --end--
          },
        "mappings" : {
            "_default_" : {
                "_all" : {
                    "enabled" : true,
                    "norms" : false
                },
                "dynamic_templates" : [
                    {
                        "message_field" : {
                            "path_match" : "message",
                            "match_mapping_type" : "string",
                            "mapping" : {
                                "type" : "text",
                                "norms" : false
                            }}
                        },
                    {
                        "string_fields" : {
                            "match" : "*",
                            "match_mapping_type" : "string",
                            "mapping" : {
                                "type" : "text",
                                "norms" : false,
                                #选择分词器:自定义分词器,或者ik_mmax_word
                                "analyzer" : "by_max_word",
                                "fields" : {
                                    "keyword" : {
                                        "type" : "keyword"
                                    }
                                }
                            }
                        }
                     }
                ],
                "properties" : {
                    "@timestamp" : {
                        "type" : "date",
                        "include_in_all" : false
                    },
                    "@version" : {
                        "type" : "keyword",
                        "include_in_all" : false
                    }
                }
            }
        }
    }
  • 有了自定义模板文件,test.conf中配置模板覆盖使模板生效。test.conf最终配置如下:
  • input {
                stdin {
                }
                jdbc {
                  # 数据库地址  端口  数据库名
                  jdbc_connection_string => "jdbc:mysql://IP:3306/dbname"
                  # 数据库用户名
                  jdbc_user => "user"
                  # 数据库密码
                  jdbc_password => "pass"
                  # mysql java驱动地址
                  jdbc_driver_library => "/home/rzxes/logstash-5.3.1/mysql-connector-java-5.1.17.jar"
                  jdbc_driver_class => "com.mysql.jdbc.Driver"
                  jdbc_paging_enabled => "true"
                  jdbc_page_size => "100000"
                  # sql 语句文件
                  statement_filepath => "/home/rzxes/logstash-5.3.1/mytest.sql"
                  schedule => "* * * * *"
                  type => "jdbc"
                }
            }
            output {
                stdout {
                    codec => json_lines
                }
                elasticsearch {
                    hosts  => "192.168.230.150:9200"
                    index => "test-1"
                    document_type => "form"
                    document_id => "%{id}" #id必须是待查询的数据表的序列字段
                    template_overwrite => true
                    template => "/home/rzxes/logstash-5.3.1/template/logstash.json"
                    }
            }
  • 删除上次创建的index(由于数据导入时会根据原有数据的index,mapping进行索引创建),重新启动logstash。
  • 最终在Kibana中检索关键词 番茄,就会发现西红柿也会被检索到。如下图:
  • 技术分享
  • 致此logstash数据导入的template重写就完成了。
  • 另一种方式配置IK分词:全局配置,不需要自定义模板。
  • curl -XPUT "http://192.168.230.150:9200/_template/rtf" -H ‘Content-Type: application/json‘ -d‘
    {
                "template" : "*",
                "version" : 50001,
                "settings" : {
                    "index.refresh_interval" : "5s",
                    "index": {
                      "analysis": {
                        "analyzer": {
                          "by_smart": {
                            "type": "custom",
                            "tokenizer": "ik_smart",
                            "filter": ["by_tfr","by_sfr"],
                            "char_filter": ["by_cfr"]
                          },
                          "by_max_word": {
                            "type": "custom",
                            "tokenizer": "ik_max_word",
                            "filter": ["by_tfr","by_sfr"],
                            "char_filter": ["by_cfr"]
                          }
                        },
                        "filter": {
                          "by_tfr": {
                            "type": "stop",
                            "stopwords": [" "]
                          },
                          "by_sfr": {
                            "type": "synonym",
                            "synonyms_path": "analysis/synonyms.txt"
                          }
                        },
                        "char_filter": {
                          "by_cfr": {
                            "type": "mapping",
                            "mappings": ["| => |"]
                          }
                        }
                      }
                    }
                  },
                "mappings" : {
                    "_default_" : {
                        "_all" : {
                            "enabled" : true,
                            "norms" : false
                        },
                        "dynamic_templates" : [
                            {
                                "message_field" : {
                                    "path_match" : "message",
                                    "match_mapping_type" : "string",
                                    "mapping" : {
                                        "type" : "text",
                                        "norms" : false
                                    }}
                                },
                            {
                                "string_fields" : { 
                                    "match" : "*",   
                                    "match_mapping_type" : "string", 
                                    "mapping" : {
                                        "type" : "text",
                                        "norms" : false,
                                        "analyzer" : "by_max_word", 
                                        "fields" : {  
                                            "keyword" : {
                                                "type" : "keyword"
                                            }
                                        }
                                    }
                                }
                             }
                        ],
                        "properties" : {
                            "@timestamp" : {
                                "type" : "date",
                                "include_in_all" : false
                            },
                            "@version" : {
                                "type" : "keyword",
                                "include_in_all" : false
                            }
                        }
                    }
                }
            }‘
  • 可以使用curl查看模板: curl -XGET "http://192.168.230.150:9200/_template" 

[大数据]-Logstash-5.3.1的安装导入数据到Elasticsearch5.3.1并配置同义词过滤

标签:last   启动   start   索引   img   point   output   keyword   token   

原文地址:http://www.cnblogs.com/NextNight/p/6860283.html

(0)
(0)
   
举报
评论 一句话评论(0
登录后才能评论!
© 2014 mamicode.com 版权所有  联系我们:gaon5@hotmail.com
迷上了代码!