Elasticsearch 2.2.0 分词篇：中文分词
Elasticsearch 2.2.0 分词篇：中文分词
在Elasticsearch中，内置了很多分词器（analyzers），但默认的分词器对中文的支持都不是太好。所以需要单独安装插件来支持，比较常用的是中科院 ICTCLAS的smartcn和IKAnanlyzer效果还是不错的，但是目前IKAnanlyzer还不支持最新的Elasticsearch2.2.0版本，但是smartcn中文分词器默认官方支持，它提供了一个中文或混合中文英文文本的分析器。支持最新的2.2.0版本版本。但是smartcn不支持自定义词库，作为测试可先用一下。后面的部分介绍如何支持最新的版本。
smartcn
安装分词：plugin install analysis-smartcn
卸载：plugin remove analysis-smartcn
测试：
请求：POST http://127.0.0.1:9200/_analyze/
{
"analyzer": "smartcn",
"text": "联想是全球最大的笔记本厂商"
}
返回结果：
{
"tokens": [
{
"token": "联想",
"start_offset": 0,
"end_offset": 2,
"type": "word",
"position": 0
},
{
"token": "是",
"start_offset": 2,
"end_offset": 3,
"type": "word",
"position": 1
},
{
"token": "全球",
"start_offset": 3,
"end_offset": 5,
"type": "word",
"position": 2
},
{
"token": "最",
"start_offset": 5,
"end_offset": 6,
"type": "word",
"position": 3
},
{
"token": "大",
"start_offset": 6,
"end_offset": 7,
"type": "word",
"position": 4
},
{
"token": "的",
"start_offset": 7,
"end_offset": 8,
"type": "word",
"position": 5
},
{
"token": "笔记本",
"start_offset": 8,
"end_offset": 11,
"type": "word",
"position": 6
},
{
"token": "厂商",
"start_offset": 11,
"end_offset": 13,
"type": "word",
"position": 7
}
]
}
作为对比，我们看一下标准的分词的结果，在请求中巴smartcn，换成standard
然后看返回结果：
{
"tokens": [
{
"token": "联",
"start_offset": 0,
"end_offset": 1,
"type": "<IDEOGRAPHIC>",
"position": 0
},
{
"token": "想",
"start_offset": 1,
"end_offset": 2,
"type": "<IDEOGRAPHIC>",
"position": 1
},
{
"token": "是",
"start_offset": 2,
"end_offset": 3,
"type": "<IDEOGRAPHIC>",
"position": 2
},
{
"token": "全",
"start_offset": 3,
"end_offset": 4,
"type": "<IDEOGRAPHIC>",
"position": 3
},
{
"token": "球",
"start_offset": 4,
"end_offset": 5,
"type": "<IDEOGRAPHIC>",
"position": 4
},
{
"token": "最",
"start_offset": 5,
"end_offset": 6,
"type": "<IDEOGRAPHIC>",
"position": 5
},
{
"token": "大",
"start_offset": 6,
"end_offset": 7,
"type": "<IDEOGRAPHIC>",
"position": 6
},
{
"token": "的",
"start_offset": 7,
"end_offset": 8,
"type": "<IDEOGRAPHIC>",
"position": 7
},
{
"token": "笔",
"start_offset": 8,
"end_offset": 9,
"type": "<IDEOGRAPHIC>",
"position": 8
},
{
"token": "记",
"start_offset": 9,
"end_offset": 10,
"type": "<IDEOGRAPHIC>",
"position": 9
},
{
"token": "本",
"start_offset": 10,
"end_offset": 11,
"type": "<IDEOGRAPHIC>",
"position": 10
},
{
"token": "厂",
"start_offset": 11,
"end_offset": 12,
"type": "<IDEOGRAPHIC>",
"position": 11
},
{
"token": "商",
"start_offset": 12,
"end_offset": 13,
"type": "<IDEOGRAPHIC>",
"position": 12
}
]
}
从中可以看出，基本上不能使用，就是一个汉字变成了一个词了。
本文由赛克 蓝德(secisland)原创，转载请标明作者和出处。
IKAnanlyzer支持2.2.0版本
目前github上最新的版本只支持Elasticsearch2.1.1,路径为https://github.com/medcl/elasticsearch-analysis-ik。但现在最新的Elasticsearch已经到2.2.0了所以要经过处理一下才能支持。
1、下载源码，下载完后解压到任意目录，然后修改elasticsearch-analysis-ik-master目录下的pom.xml文件。找到<elasticsearch.version>行，然后把后面的版本号修改成2.2.0。
2、编译代码mvn package。
3、编译完成后会在target\releases生成elasticsearch-analysis-ik-1.7.0.zip文件。
4、解压文件到Elasticsearch/plugins目录下。
5、修改配置文件增加一行：index.analysis.analyzer.ik.type : "ik"
6、重启Elasticsearch。
测试：和上面的请求一样，只是把分词替换成ik
返回的结果：
{
"tokens": [
{
"token": "联想",
"start_offset": 0,
"end_offset": 2,
"type": "CN_WORD",
"position": 0
},
{
"token": "全球",
"start_offset": 3,
"end_offset": 5,
"type": "CN_WORD",
"position": 1
},
{
"token": "最大",
"start_offset": 5,
"end_offset": 7,
"type": "CN_WORD",
"position": 2
},
{
"token": "笔记本",
"start_offset": 8,
"end_offset": 11,
"type": "CN_WORD",
"position": 3
},
{
"token": "笔记",
"start_offset": 8,
"end_offset": 10,
"type": "CN_WORD",
"position": 4
},
{
"token": "笔",
"start_offset": 8,
"end_offset": 9,
"type": "CN_WORD",
"position": 5
},
{
"token": "记",
"start_offset": 9,
"end_offset": 10,
"type": "CN_CHAR",
"position": 6
},
{
"token": "本厂",
"start_offset": 10,
"end_offset": 12,
"type": "CN_WORD",
"position": 7
},
{
"token": "厂商",
"start_offset": 11,
"end_offset": 13,
"type": "CN_WORD",
"position": 8
}
]
}
从中可以看出，两个分词器分词的结果还是有区别的。
扩展词库，在config\ik\custom下在mydict.dic中增加需要的词组，然后重启Elasticsearch，需要注意的是文件编码是UTF-8 无BOM格式编码。
比如增加了赛克蓝德单词。然后再次查询：
请求：POST http://127.0.0.1:9200/_analyze/
参数：
{
"analyzer": "ik",
"text": "赛克蓝德是一家数据安全公司"
}
返回结果：
{
"tokens": [
{
"token": "赛克蓝德",
"start_offset": 0,
"end_offset": 4,
"type": "CN_WORD",
"position": 0
},
{
"token": "克",
"start_offset": 1,
"end_offset": 2,
"type": "CN_WORD",
"position": 1
},
{
"token": "蓝",
"start_offset": 2,
"end_offset": 3,
"type": "CN_WORD",
"position": 2
},
{
"token": "德",
"start_offset": 3,
"end_offset": 4,
"type": "CN_CHAR",
"position": 3
},
{
"token": "一家",
"start_offset": 5,
"end_offset": 7,
"type": "CN_WORD",
"position": 4
},
{
"token": "一",
"start_offset": 5,
"end_offset": 6,
"type": "TYPE_CNUM",
"position": 5
},
{
"token": "家",
"start_offset": 6,
"end_offset": 7,
"type": "COUNT",
"position": 6
},
{
"token": "数据",
"start_offset": 7,
"end_offset": 9,
"type": "CN_WORD",
"position": 7
},
{
"token": "安全",
"start_offset": 9,
"end_offset": 11,
"type": "CN_WORD",
"position": 8
},
{
"token": "公司",
"start_offset": 11,
"end_offset": 13,
"type": "CN_WORD",
"position": 9
}
]
}
从上面的结果可以看出已经支持赛克蓝德单词了。
ElasticSearch 最新版本 2.20 发布下载了
Linux上安装部署ElasticSearch全程记录
Elasticsearch安装使用教程
ElasticSearch 配置文件译文解析
ElasticSearch集群搭建实例
分布式搜索ElasticSearch单机与服务器环境搭建
ElasticSearch的工作机制
使用Elasticsearch + Logstash + Kibana搭建日志集中分析平台实践
ElasticSearch 的详细介绍：请点这里
ElasticSearch 的下载地址：请点这里
本文永久更新链接地址：
评论暂时关闭