每日一博 | ElasticSearch 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。

赛克蓝德(secisland)后续会逐步对Elasticsearch的最新版本的各项功能进行分析，近请期待。 也欢迎加入secisland公众号进行关注 。