[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

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。

• 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}

• 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;
• 
• 等待数据导入完成。开启Es-head,访问9100端口如下：

• 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

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。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：
• 
• 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"