logstash5.0版本之后导入es数据指定ik分词器详解

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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 startedThe 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;
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

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：
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"

原文网址：http://www.cnblogs.com/NextNight/p/6860283.html

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