Elasticsearch之中文分词器插件es-ik的自定义词库

向右看齐 2024-02-18 18:43 9阅读 0赞

前提，

## [Elasticsearch之中文分词器插件es-ik][Elasticsearch_es-ik] ##

针对一些特殊的词语在分词的时候也需要能够识别

有人会问，那么，例如：

如果我想根据自己的本家姓氏来查询，如zhouls，姓氏“周”。

如果我想根据自己的公司名称来查询，如“好记性不如烂笔头感叹号博客园”

如果我想根据自己公司里的产品名称来查询，如“”

如果我想根据某个网络上流行的词名称来查询，如“扫福”

那么，若直接使用es-ik则分不出来的，所以，这就是为什么需要es-ik的自定义词库的缘由啦！

![855959-20170225090836398-2128895492.png][]

\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ curl 'http://192.168.80.10:9200/zhouls/\_analyze?analyzer=ik\_max\_word&pretty=true' -d '\{"text":"好记性不如烂笔头感叹号博客园"\}'  
\{  
"tokens" : \[ \{  
"token" : "好记",  
"start\_offset" : 0,  
"end\_offset" : 2,  
"type" : "CN\_WORD",  
"position" : 0  
\}, \{  
"token" : "记性",  
"start\_offset" : 1,  
"end\_offset" : 3,  
"type" : "CN\_WORD",  
"position" : 1  
\}, \{  
"token" : "不如",  
"start\_offset" : 3,  
"end\_offset" : 5,  
"type" : "CN\_WORD",  
"position" : 2  
\}, \{  
"token" : "烂",  
"start\_offset" : 5,  
"end\_offset" : 6,  
"type" : "CN\_CHAR",  
"position" : 3  
\}, \{  
"token" : "笔头",  
"start\_offset" : 6,  
"end\_offset" : 8,  
"type" : "CN\_WORD",  
"position" : 4  
\}, \{

"token" : "笔",  
"start\_offset" : 6,  
"end\_offset" : 7,  
"type" : "CN\_WORD",  
"position" : 5  
\}, \{  
"token" : "头",  
"start\_offset" : 7,  
"end\_offset" : 8,  
"type" : "CN\_CHAR",  
"position" : 6  
\}, \{  
"token" : "感叹号",  
"start\_offset" : 8,  
"end\_offset" : 11,  
"type" : "CN\_WORD",  
"position" : 7  
\}, \{  
"token" : "感叹",  
"start\_offset" : 8,  
"end\_offset" : 10,  
"type" : "CN\_WORD",  
"position" : 8  
\}, \{  
"token" : "叹号",  
"start\_offset" : 9,  
"end\_offset" : 11,  
"type" : "CN\_WORD",  
"position" : 9  
\}, \{

"token" : "叹",  
"start\_offset" : 9,  
"end\_offset" : 10,  
"type" : "CN\_WORD",  
"position" : 10  
\}, \{  
"token" : "号",  
"start\_offset" : 10,  
"end\_offset" : 11,  
"type" : "CN\_CHAR",  
"position" : 11  
\}, \{  
"token" : "博客园",  
"start\_offset" : 11,  
"end\_offset" : 14,  
"type" : "CN\_WORD",  
"position" : 12  
\}, \{  
"token" : "博客",  
"start\_offset" : 11,  
"end\_offset" : 13,  
"type" : "CN\_WORD",  
"position" : 13  
\}, \{  
"token" : "园",  
"start\_offset" : 13,  
"end\_offset" : 14,  
"type" : "CN\_CHAR",  
"position" : 14  
\} \]  
\}  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$

Elasticsearch之中文分词器插件es-ik的自定义词库

【 ik 自定义词库步骤】  
1： 首先在 ik 插件的 config/custom 目录下创建一个文件 zhouls.dic （当然这个你可以自己命名，如my.dic都行）  
在文件中添加词语即可， 每一个词语一行。  
\-------------------------------------------------------------------------------------------------------------  
注意： 这个文件可以在 linux 中直接 vi 生成， 或者在 windows 中创建之后上传到这里。  
如果是在 linux 中直接 vi 生成的， 可以直接使用。  
如果是在 windows中创建的，需要注意文件的编码必须是 UTF-8 without BOM 格式 【 UTF-8 无  
BOM 格式】  
\-------------------------------------------------------------------------------------------------------------

2： 修改 ik 的配置文件  
默认情况下 ik 的配置文件就在 ik 插件的 config 目录下面。【 IKAnalyzer.cfg.xml】  
把刚才创建的文件的位置添加到 ik 的配置文件中即可。  
vi config/IKAnalyzer.cfg.xml  
<properties>  
<comment>IK Analyzer 扩展配置</comment>  
  
<entry  
key="ext\_dict">custom/mydict.dic;custom/single\_word\_low\_freq.dic;custom/zhouls.dic</entry>  
  
<entry key="ext\_stopwords">custom/ext\_stopword.dic</entry>  
  
  
  
  
</properties>  
\------------------------------------------------------------------------------------------------------------------------------  
注意： 需要把 my.dic 文件的位置添加到 key=ext\_dict 这个 entry 中， 切记不要随意新增 entry，  
随意新增的 entry 是不被识别的。  
并且 entry 的名称也不能乱改， 否则也不会识别。  
<entry  
key="ext\_dict">custom/mydict.dic;custom/single\_word\_low\_freq.dic;custom/my.dic</entry>  
\------------------------------------------------------------------------------------------------------------------------------

3： 重启 es 验证分词效果  
重启的时候查看日志会看到下面信息

第一步：进入$ES\_HOME/plugins/ik/config/custom/下，新建自定义词库。我这里，取名为zhouls.dic

![855959-20170225091019288-1894785107.png][]

![855959-20170225091217523-37416886.png][]

\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ ll  
total 56  
drwxrwxr-x. 2 hadoop hadoop 4096 Feb 22 01:37 bin  
drwxrwxr-x. 3 hadoop hadoop 4096 Feb 22 18:46 config  
drwxrwxr-x. 3 hadoop hadoop 4096 Feb 22 06:05 data  
drwxrwxr-x. 2 hadoop hadoop 4096 Feb 22 01:37 lib  
\-rw-rw-r--. 1 hadoop hadoop 11358 Aug 24 2016 LICENSE.txt  
drwxrwxr-x. 2 hadoop hadoop 4096 Feb 25 05:15 logs  
drwxrwxr-x. 5 hadoop hadoop 4096 Dec 8 00:41 modules  
\-rw-rw-r--. 1 hadoop hadoop 150 Aug 24 2016 NOTICE.txt  
drwxrwxr-x. 5 hadoop hadoop 4096 Feb 25 06:31 plugins  
\-rw-rw-r--. 1 hadoop hadoop 8700 Aug 24 2016 README.textile  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ cd plugins/  
\[hadoop@HadoopMaster plugins\]$ ll  
total 12  
drwxrwxr-x. 5 hadoop hadoop 4096 Feb 22 05:28 head  
drwxrwxr-x. 3 hadoop hadoop 4096 Feb 25 06:32 ik  
drwxrwxr-x. 8 hadoop hadoop 4096 Feb 22 05:34 kopf  
\[hadoop@HadoopMaster plugins\]$ cd ik/  
\[hadoop@HadoopMaster ik\]$ ll  
total 5828  
\-rw-r--r--. 1 hadoop hadoop 263965 Dec 1 2015 commons-codec-1.9.jar  
\-rw-r--r--. 1 hadoop hadoop 61829 Dec 1 2015 commons-logging-1.2.jar  
drwxr-xr-x. 3 hadoop hadoop 4096 Jan 1 12:46 config  
\-rw-r--r--. 1 hadoop hadoop 55998 Jan 1 13:27 elasticsearch-analysis-ik-1.10.3.jar  
\-rw-r--r--. 1 hadoop hadoop 4505518 Jan 15 08:59 elasticsearch-analysis-ik-1.10.3.zip  
\-rw-r--r--. 1 hadoop hadoop 736658 Jan 1 13:26 httpclient-4.5.2.jar  
\-rw-r--r--. 1 hadoop hadoop 326724 Jan 1 13:07 httpcore-4.4.4.jar  
\-rw-r--r--. 1 hadoop hadoop 2667 Jan 1 13:27 plugin-descriptor.properties  
\[hadoop@HadoopMaster ik\]$ cd config/

\[hadoop@HadoopMaster config\]$ ll  
total 3016  
drwxr-xr-x. 2 hadoop hadoop 4096 Jan 1 12:46 custom  
\-rw-r--r--. 1 hadoop hadoop 697 Dec 14 10:34 IKAnalyzer.cfg.xml  
\-rw-r--r--. 1 hadoop hadoop 3058510 Dec 14 10:34 main.dic  
\-rw-r--r--. 1 hadoop hadoop 123 Dec 14 10:34 preposition.dic  
\-rw-r--r--. 1 hadoop hadoop 1824 Dec 14 10:34 quantifier.dic  
\-rw-r--r--. 1 hadoop hadoop 164 Dec 14 10:34 stopword.dic  
\-rw-r--r--. 1 hadoop hadoop 192 Dec 14 10:34 suffix.dic  
\-rw-r--r--. 1 hadoop hadoop 752 Dec 14 10:34 surname.dic  
\[hadoop@HadoopMaster config\]$ cd custom/  
\[hadoop@HadoopMaster custom\]$ ll  
total 5252  
\-rw-r--r--. 1 hadoop hadoop 156 Dec 14 10:34 ext\_stopword.dic  
\-rw-r--r--. 1 hadoop hadoop 130 Dec 14 10:34 mydict.dic  
\-rw-r--r--. 1 hadoop hadoop 63188 Dec 14 10:34 single\_word.dic  
\-rw-r--r--. 1 hadoop hadoop 63188 Dec 14 10:34 single\_word\_full.dic  
\-rw-r--r--. 1 hadoop hadoop 10855 Dec 14 10:34 single\_word\_low\_freq.dic  
\-rw-r--r--. 1 hadoop hadoop 5225922 Dec 14 10:34 sougou.dic  
\[hadoop@HadoopMaster custom\]$ vim zhouls.dic

第二步：输入，自定义词，如我这里，是好记性不如烂笔头感叹号博客园

![855959-20170225091545710-970384771.png][]

![855959-20170225091623788-402488199.png][]

\[hadoop@HadoopMaster custom\]$ pwd  
/home/hadoop/app/elasticsearch-2.4.3/plugins/ik/config/custom  
\[hadoop@HadoopMaster custom\]$ vim zhouls.dic  
\[hadoop@HadoopMaster custom\]$ cat zhouls.dic  
好记性不如烂笔头感叹号博客园  
\[hadoop@HadoopMaster custom\]$

第三步：修改ik的配置文件

自然而然，我刚加入的自定义词库zhouls.dic是需要配置，才可以生效的。

![855959-20170225092200413-658073595.png][]

\[hadoop@HadoopMaster custom\]$ ll  
total 5256  
\-rw-r--r--. 1 hadoop hadoop 156 Dec 14 10:34 ext\_stopword.dic  
\-rw-r--r--. 1 hadoop hadoop 130 Dec 14 10:34 mydict.dic  
\-rw-r--r--. 1 hadoop hadoop 63188 Dec 14 10:34 single\_word.dic  
\-rw-r--r--. 1 hadoop hadoop 63188 Dec 14 10:34 single\_word\_full.dic  
\-rw-r--r--. 1 hadoop hadoop 10855 Dec 14 10:34 single\_word\_low\_freq.dic  
\-rw-r--r--. 1 hadoop hadoop 5225922 Dec 14 10:34 sougou.dic  
\-rw-rw-r--. 1 hadoop hadoop 43 Feb 25 17:16 zhouls.dic  
\[hadoop@HadoopMaster custom\]$ cd ..  
\[hadoop@HadoopMaster config\]$ ll  
total 3016  
drwxr-xr-x. 2 hadoop hadoop 4096 Feb 25 17:16 custom  
\-rw-r--r--. 1 hadoop hadoop 697 Dec 14 10:34 IKAnalyzer.cfg.xml  
\-rw-r--r--. 1 hadoop hadoop 3058510 Dec 14 10:34 main.dic  
\-rw-r--r--. 1 hadoop hadoop 123 Dec 14 10:34 preposition.dic  
\-rw-r--r--. 1 hadoop hadoop 1824 Dec 14 10:34 quantifier.dic  
\-rw-r--r--. 1 hadoop hadoop 164 Dec 14 10:34 stopword.dic  
\-rw-r--r--. 1 hadoop hadoop 192 Dec 14 10:34 suffix.dic  
\-rw-r--r--. 1 hadoop hadoop 752 Dec 14 10:34 surname.dic  
\[hadoop@HadoopMaster config\]$ vim IKAnalyzer.cfg.xml

![855959-20170225092247913-1585334845.png][]

<?xml version="1.0" encoding="UTF-8"?>  
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">  
<properties>  
<comment>IK Analyzer 扩展配置</comment>  
  
<entry key="ext\_dict">custom/mydict.dic;custom/single\_word\_low\_freq.dic</entry>  
  
<entry key="ext\_stopwords">custom/ext\_stopword.dic</entry>  
  
  
  
  
</properties>

修改为

![855959-20170225092613898-334034402.png][]

![855959-20170225092638116-2000619480.png][]

\[hadoop@HadoopMaster config\]$ vim IKAnalyzer.cfg.xml  
\[hadoop@HadoopMaster config\]$ cat IKAnalyzer.cfg.xml  
?<?xml version="1.0" encoding="UTF-8"?>  
<!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd">  
<properties>  
<comment>IK Analyzer 扩展配置</comment>  
  
<entry key="ext\_dict">custom/mydict.dic;custom/single\_word\_low\_freq.dic;custom/zhouls.dic</entry>  
  
<entry key="ext\_stopwords">custom/ext\_stopword.dic</entry>  
  
  
  
  
</properties>  
\[hadoop@HadoopMaster config\]$

第四步：重启es服务进程

为了更好地看出效果，启动es服务进程，我用bin/elasticsearch。一般建议用bin/elasticsearch -d。当然，生产环境下，可以将其设置为服务进程，作为service下的一种服务进程，这样更为方便。

![855959-20170225092848445-471547190.png][]

\[hadoop@HadoopMaster plugins\]$ cd ..  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ jps  
1974 Elasticsearch  
2137 Jps  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ kill -9 1974  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ jps  
2148 Jps  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ bin/elasticsearch  
\[2017-02-25 17:27:56,301\]\[WARN \]\[bootstrap \] unable to install syscall filter: seccomp unavailable: requires kernel 3.5+ with CONFIG\_SECCOMP and CONFIG\_SECCOMP\_FILTER compiled in  
\[2017-02-25 17:27:57,741\]\[INFO \]\[node \] \[Tethlam\] version\[2.4.3\], pid\[2158\], build\[d38a34e/2016-12-07T16:28:56Z\]  
\[2017-02-25 17:27:57,741\]\[INFO \]\[node \] \[Tethlam\] initializing ...  
\[2017-02-25 17:27:59,504\]\[INFO \]\[plugins \] \[Tethlam\] modules \[lang-groovy, reindex, lang-expression\], plugins \[analysis-ik, kopf, head\], sites \[kopf, head\]  
\[2017-02-25 17:27:59,553\]\[INFO \]\[env \] \[Tethlam\] using \[1\] data paths, mounts \[\[/home (/dev/sda5)\]\], net usable\_space \[23.4gb\], net total\_space \[26.1gb\], spins? \[possibly\], types \[ext4\]  
\[2017-02-25 17:27:59,553\]\[INFO \]\[env \] \[Tethlam\] heap size \[1015.6mb\], compressed ordinary object pointers \[true\]  
\[2017-02-25 17:27:59,553\]\[WARN \]\[env \] \[Tethlam\] max file descriptors \[4096\] for elasticsearch process likely too low, consider increasing to at least \[65536\]  
\[2017-02-25 17:28:02,922\]\[INFO \]\[ik-analyzer \] try load config from /home/hadoop/app/elasticsearch-2.4.3/config/analysis-ik/IKAnalyzer.cfg.xml  
\[2017-02-25 17:28:02,923\]\[INFO \]\[ik-analyzer \] try load config from /home/hadoop/app/elasticsearch-2.4.3/plugins/ik/config/IKAnalyzer.cfg.xml  
\[2017-02-25 17:28:03,748\]\[INFO \]\[ik-analyzer \] \[Dict Loading\] custom/mydict.dic  
\[2017-02-25 17:28:03,749\]\[INFO \]\[ik-analyzer \] \[Dict Loading\] custom/single\_word\_low\_freq.dic  
\[2017-02-25 17:28:03,755\]\[INFO \]\[ik-analyzer \] \[Dict Loading\] custom/zhouls.dic  
\[2017-02-25 17:28:03,760\]\[INFO \]\[ik-analyzer \] \[Dict Loading\] custom/ext\_stopword.dic  
\[2017-02-25 17:28:06,914\]\[INFO \]\[node \] \[Tethlam\] initialized  
\[2017-02-25 17:28:06,915\]\[INFO \]\[node \] \[Tethlam\] starting ...  
\[2017-02-25 17:28:07,168\]\[INFO \]\[transport \] \[Tethlam\] publish\_address \{192.168.80.10:9300\}, bound\_addresses \{\[::\]:9300\}  
\[2017-02-25 17:28:07,203\]\[INFO \]\[discovery \] \[Tethlam\] elasticsearch/dXjRTwNJRdyzQWPbHIzGiQ  
\[2017-02-25 17:28:10,589\]\[INFO \]\[cluster.service \] \[Tethlam\] detected\_master \{Peter Parker\}\{3TwJeRfnRH-EttHntj0OdQ\}\{192.168.80.11\}\{192.168.80.11:9300\}, added \{ \{Peter Parker\}\{3TwJeRfnRH-EttHntj0OdQ\}\{192.168.80.11\}\{192.168.80.11:9300\},\{Living Laser\}\{bqV\_F5bLRdq9AGtv3WLx4A\}\{192.168.80.12\}\{192.168.80.12:9300\},\}, reason: zen-disco-receive(from master \[\{Peter Parker\}\{3TwJeRfnRH-EttHntj0OdQ\}\{192.168.80.11\}\{192.168.80.11:9300\}\])  
\[2017-02-25 17:28:10,920\]\[INFO \]\[http \] \[Tethlam\] publish\_address \{192.168.80.10:9200\}, bound\_addresses \{\[::\]:9200\}  
\[2017-02-25 17:28:10,923\]\[INFO \]\[node \] \[Tethlam\] started

第五步：测试效果，验证下

![855959-20170225093150835-999790441.png][]

\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ jps  
2280 Jps  
2231 Elasticsearch  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$ curl 'http://192.168.80.10:9200/zhouls/\_analyze?analyzer=ik\_max\_word&pretty=true' -d '\{"text":"好记性不如烂笔头感叹号博客园"\}'  
\{  
"tokens" : \[ \{  
"token" : "好记性不如烂笔头感叹号博客园",  
"start\_offset" : 0,  
"end\_offset" : 14,  
"type" : "CN\_WORD",  
"position" : 0  
\}, \{  
"token" : "好记",  
"start\_offset" : 0,  
"end\_offset" : 2,  
"type" : "CN\_WORD",  
"position" : 1  
\}, \{  
"token" : "记性",  
"start\_offset" : 1,  
"end\_offset" : 3,  
"type" : "CN\_WORD",  
"position" : 2  
\}, \{  
"token" : "不如",  
"start\_offset" : 3,  
"end\_offset" : 5,  
"type" : "CN\_WORD",  
"position" : 3  
\}, \{  
"token" : "烂",  
"start\_offset" : 5,  
"end\_offset" : 6,

"type" : "CN\_CHAR",  
"position" : 4  
\}, \{  
"token" : "笔头",  
"start\_offset" : 6,  
"end\_offset" : 8,  
"type" : "CN\_WORD",  
"position" : 5  
\}, \{  
"token" : "笔",  
"start\_offset" : 6,  
"end\_offset" : 7,  
"type" : "CN\_WORD",  
"position" : 6  
\}, \{  
"token" : "头",  
"start\_offset" : 7,  
"end\_offset" : 8,  
"type" : "CN\_CHAR",  
"position" : 7  
\}, \{  
"token" : "感叹号",  
"start\_offset" : 8,  
"end\_offset" : 11,  
"type" : "CN\_WORD",  
"position" : 8  
\}, \{  
"token" : "感叹",  
"start\_offset" : 8,  
"end\_offset" : 10,

"type" : "CN\_WORD",  
"position" : 9  
\}, \{  
"token" : "叹号",  
"start\_offset" : 9,  
"end\_offset" : 11,  
"type" : "CN\_WORD",  
"position" : 10  
\}, \{  
"token" : "叹",  
"start\_offset" : 9,  
"end\_offset" : 10,  
"type" : "CN\_WORD",  
"position" : 11  
\}, \{  
"token" : "号",  
"start\_offset" : 10,  
"end\_offset" : 11,  
"type" : "CN\_CHAR",  
"position" : 12  
\}, \{  
"token" : "博客园",  
"start\_offset" : 11,  
"end\_offset" : 14,  
"type" : "CN\_WORD",  
"position" : 13  
\}, \{  
"token" : "博客",  
"start\_offset" : 11,  
"end\_offset" : 13,

"type" : "CN\_WORD",  
"position" : 14  
\}, \{  
"token" : "园",  
"start\_offset" : 13,  
"end\_offset" : 14,  
"type" : "CN\_CHAR",  
"position" : 15  
\} \]  
\}  
\[hadoop@HadoopMaster elasticsearch-2.4.3\]$

可以看出，我们自定义词库zhouls.dic里的自定义词，我这里是，好记性不如烂笔头感叹号博客园。看作是一个词。成功被整体切分出来！

说明成功！

[Elasticsearch_es-ik]: http://www.cnblogs.com/zlslch/p/6440373.html
[855959-20170225090836398-2128895492.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/49b73ce775ce427c856d458913da86fb.png
[855959-20170225091019288-1894785107.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/16da2dc2f9a94e39a1390e5a79b0981e.png
[855959-20170225091217523-37416886.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/90f8c61d0c62431fb35febcc6dee3a10.png
[855959-20170225091545710-970384771.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/6934b3e4de6440758a9ea0e5fa0fb6d2.png
[855959-20170225091623788-402488199.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/3e5e027a1f484772a62ff8b7c86c7401.png
[855959-20170225092200413-658073595.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/6f8902cb18074c2298e41d1d99087ecb.png
[855959-20170225092247913-1585334845.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/f72bc48a41b9452b9e8638ee416a3ded.png
[855959-20170225092613898-334034402.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/01c3dda855cb4d1d865635bcb32e3688.png
[855959-20170225092638116-2000619480.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/2370becb1407470ebbaac12a1692d746.png
[855959-20170225092848445-471547190.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/c42e17e16d5c48c98506ffb9a264a7ac.png
[855959-20170225093150835-999790441.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/dacec6810d4e462d977139436095ba42.png