為Elasticsarch添增ik分析器優化中文搜索(二)
前言
雖然說安裝好ik分析器可以對中文能夠比較友善的處理了; 但測試後發現有些詞彙還是沒有成功分詞. 不過幸好也找到了解決辦法; 順便也介紹一下如何熱更新流行詞彙吧!
調整之前
我們看看針對這個句子可以得到什麼結果: 首先呢, 既然要使用那個模塊, 就必須先確保你的 Nginx 有編譯該模塊
root@ghost-elastic01:~# curl 'http://localhost:9200/ikhell/_analyze?pretty=true' -H 'Content-Type: application/json' -d '{ "field": "content", "text":"首先呢, 既然要使用那個模塊, 就必須先確保你的 Nginx 有編譯該模塊"}'
{
"tokens" : [
{
"token" : "首先",
"start_offset" : 0,
"end_offset" : 2,
"type" : "CN_WORD",
"position" : 0
},
{
"token" : "呢",
"start_offset" : 2,
"end_offset" : 3,
"type" : "CN_CHAR",
"position" : 1
},
{
"token" : "既然",
"start_offset" : 5,
"end_offset" : 7,
"type" : "CN_WORD",
"position" : 2
},
{
"token" : "要使",
"start_offset" : 7,
"end_offset" : 9,
"type" : "CN_WORD",
"position" : 3
},
{
"token" : "使用",
"start_offset" : 8,
"end_offset" : 10,
"type" : "CN_WORD",
"position" : 4
},
{
"token" : "那",
"start_offset" : 10,
"end_offset" : 11,
"type" : "CN_CHAR",
"position" : 5
},
{
"token" : "個",
"start_offset" : 11,
"end_offset" : 12,
"type" : "CN_CHAR",
"position" : 6
},
{
"token" : "模",
"start_offset" : 12,
"end_offset" : 13,
"type" : "CN_CHAR",
"position" : 7
},
{
"token" : "塊",
"start_offset" : 13,
"end_offset" : 14,
"type" : "CN_CHAR",
"position" : 8
},
{
"token" : "就",
"start_offset" : 16,
"end_offset" : 17,
"type" : "CN_CHAR",
"position" : 9
},
{
"token" : "必",
"start_offset" : 17,
"end_offset" : 18,
"type" : "CN_CHAR",
"position" : 10
},
{
"token" : "須",
"start_offset" : 18,
"end_offset" : 19,
"type" : "CN_CHAR",
"position" : 11
},
{
"token" : "先",
"start_offset" : 19,
"end_offset" : 20,
"type" : "CN_CHAR",
"position" : 12
},
{
"token" : "確",
"start_offset" : 20,
"end_offset" : 21,
"type" : "CN_CHAR",
"position" : 13
},
{
"token" : "保",
"start_offset" : 21,
"end_offset" : 22,
"type" : "CN_CHAR",
"position" : 14
},
{
"token" : "你",
"start_offset" : 22,
"end_offset" : 23,
"type" : "CN_CHAR",
"position" : 15
},
{
"token" : "的",
"start_offset" : 23,
"end_offset" : 24,
"type" : "CN_CHAR",
"position" : 16
},
{
"token" : "nginx",
"start_offset" : 25,
"end_offset" : 30,
"type" : "ENGLISH",
"position" : 17
},
{
"token" : "有",
"start_offset" : 31,
"end_offset" : 32,
"type" : "CN_CHAR",
"position" : 18
},
{
"token" : "編",
"start_offset" : 32,
"end_offset" : 33,
"type" : "CN_CHAR",
"position" : 19
},
{
"token" : "譯",
"start_offset" : 33,
"end_offset" : 34,
"type" : "CN_CHAR",
"position" : 20
},
{
"token" : "該",
"start_offset" : 34,
"end_offset" : 35,
"type" : "CN_CHAR",
"position" : 21
},
{
"token" : "模",
"start_offset" : 35,
"end_offset" : 36,
"type" : "CN_CHAR",
"position" : 22
},
{
"token" : "塊",
"start_offset" : 36,
"end_offset" : 37,
"type" : "CN_CHAR",
"position" : 23
}
]
}
首先呢, 既然要使用那個模塊, 就必須先確保你的 Nginx 有編譯該模塊
被分解為
首先
, 呢
, 既然
, 要使
, 使用
, 那
, 個
, 模
, 塊
, 就
, 必
, 須
, 先
, 確
, 保
, 你
, 的
, nginx
, 有
, 編
, 譯
, 該
, 模
, 塊
恩..可謂不盡理想呀..
添加自訂義字典
修改配置文件
根據作者文檔說明ik分析器, 我們可以在/etc/elasticsearch/analysis-ik/IKAnalyzer.cfg.xml
這個設定檔添增自定義的字典檔.
在 ext_dict
的地方填入我們的字典路徑.
<?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>
<!--用户可以在这里配置自己的扩展字典 -->
<entry key="ext_dict">custom/custom.dic</entry>
<!--用户可以在这里配置自己的扩展停止词字典-->
<entry key="ext_stopwords"></entry>
<!--用户可以在这里配置远程扩展字典 -->
<entry key="remote_ext_dict"></entry>
<!--用户可以在这里配置远程扩展停止词字典-->
<!-- <entry key="remote_ext_stopwords">words_location</entry> -->
</properties>
添加字典檔
cd /etc/elasticsearch/analysis-ik
mkdir custom
wget https://raw.githubusercontent.com/samejack/sc-dictionary/master/main.txt -O custom/custom.dic
這邊使用網友製作的超齊百萬字典檔
重啟elasticsearch
systemctl restart elasticsearch
驗證結果
經過自定義的字典檔, 我們來看看分詞如何不同吧.
root@ghost-elastic01:/etc/elasticsearch/analysis-ik# curl 'http://localhost:9200/ikhell/_analyze?pretty=true' -H 'Content-Type: application/json' -d '{ "field": "content", "text":"首先呢, 既然要使用那個模塊, 就必須先確保你的 Nginx 有編譯該模塊"}'
{
"tokens" : [
{
"token" : "首先",
"start_offset" : 0,
"end_offset" : 2,
"type" : "CN_WORD",
"position" : 0
},
{
"token" : "呢",
"start_offset" : 2,
"end_offset" : 3,
"type" : "CN_CHAR",
"position" : 1
},
{
"token" : "既然",
"start_offset" : 5,
"end_offset" : 7,
"type" : "CN_WORD",
"position" : 2
},
{
"token" : "要使",
"start_offset" : 7,
"end_offset" : 9,
"type" : "CN_WORD",
"position" : 3
},
{
"token" : "使用",
"start_offset" : 8,
"end_offset" : 10,
"type" : "CN_WORD",
"position" : 4
},
{
"token" : "那個",
"start_offset" : 10,
"end_offset" : 12,
"type" : "CN_WORD",
"position" : 5
},
{
"token" : "模塊",
"start_offset" : 12,
"end_offset" : 14,
"type" : "CN_WORD",
"position" : 6
},
{
"token" : "就必須",
"start_offset" : 16,
"end_offset" : 19,
"type" : "CN_WORD",
"position" : 7
},
{
"token" : "必須先",
"start_offset" : 17,
"end_offset" : 20,
"type" : "CN_WORD",
"position" : 8
},
{
"token" : "必須",
"start_offset" : 17,
"end_offset" : 19,
"type" : "CN_WORD",
"position" : 9
},
{
"token" : "先",
"start_offset" : 19,
"end_offset" : 20,
"type" : "CN_CHAR",
"position" : 10
},
{
"token" : "確保",
"start_offset" : 20,
"end_offset" : 22,
"type" : "CN_WORD",
"position" : 11
},
{
"token" : "你的",
"start_offset" : 22,
"end_offset" : 24,
"type" : "CN_WORD",
"position" : 12
},
{
"token" : "nginx",
"start_offset" : 25,
"end_offset" : 30,
"type" : "ENGLISH",
"position" : 13
},
{
"token" : "有",
"start_offset" : 31,
"end_offset" : 32,
"type" : "CN_CHAR",
"position" : 14
},
{
"token" : "編譯",
"start_offset" : 32,
"end_offset" : 34,
"type" : "CN_WORD",
"position" : 15
},
{
"token" : "該",
"start_offset" : 34,
"end_offset" : 35,
"type" : "CN_CHAR",
"position" : 16
},
{
"token" : "模塊",
"start_offset" : 35,
"end_offset" : 37,
"type" : "CN_WORD",
"position" : 17
}
]
}
首先呢, 既然要使用那個模塊, 就必須先確保你的 Nginx 有編譯該模塊
被分解為
首先
, 呢
, 既然
, 要使
, 使用
, 那個
, 模塊
, 就必須
, 必須先
, 必須
, 先
, 確保
, 你的
, nginx
, 有
, 編譯
, 該
, 模塊
是不是好了很多呢?
熱更新
網路上的詞彙日新月異, 因此我們的必須要能夠熱更新我們的字典檔; 這邊就依照文檔做一次示範.
依照文檔說明, 可以在配置文件填入外部獲取字典的接口, 然後依照Last-Modified
和ETag
兩個header來決定是否重新獲取字典檔案.
若文件被編輯過, 則Last-Modified和ETag會變動; 代表文件被改動過, 此時就會重新獲取字典檔.
編輯配置文件
首先也是編輯IKAnalyzer.cfg.xml
這個配置文件; 找到remote_ext_dict
這個入口.
<?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>
<!--用户可以在这里配置自己的扩展字典 -->
<entry key="ext_dict">custom/custom.dic</entry>
<!--用户可以在这里配置自己的扩展停止词字典-->
<entry key="ext_stopwords"></entry>
<!--用户可以在这里配置远程扩展字典 -->
<entry key="remote_ext_dict">http://127.0.0.1/es/dic</entry>
<!--用户可以在这里配置远程扩展停止词字典-->
<!-- <entry key="remote_ext_stopwords">words_location</entry> -->
</properties>
這邊因為外掛內容被改動過, 所以還是重啟elasticsearch一次: systemctl restart elasticsearch
配置nginx
在server
區塊當中加入以下的路徑接口
location /es {
alias /etc/nginx/elasticsearch;
}
重新載入配置文件nginx -s reload
配置字典檔案
mkdir /etc/nginx/elasticsearch
touch /etc/nginx/elasticsearch/dic
到這邊為止; 我們先測試能不能獲取到字典
root@ubuntu-87:~# curl http://127.0.0.1/es/dic
因為目前字典是空的; 這樣就是成功囉.
驗證熱更新
在更新之前先測試一次分詞: 傻眼貓咪氣pupu
root@ubuntu-87:~# curl 'http://localhost:9200/ikhell/_analyze?pretty=true' -H 'Content-Type: application/json' -d '{ "field": "content", "text":"傻眼貓咪氣pupu"}'
{
"tokens" : [
{
"token" : "傻眼",
"start_offset" : 0,
"end_offset" : 2,
"type" : "CN_WORD",
"position" : 0
},
{
"token" : "貓咪",
"start_offset" : 2,
"end_offset" : 4,
"type" : "CN_WORD",
"position" : 1
},
{
"token" : "氣",
"start_offset" : 4,
"end_offset" : 5,
"type" : "CN_CHAR",
"position" : 2
},
{
"token" : "pupu",
"start_offset" : 5,
"end_offset" : 9,
"type" : "ENGLISH",
"position" : 3
}
]
}
可以看到被分詞為: 傻眼
,貓咪
, 氣
, pupu
.
然後我們寫入新的詞彙
echo -e "傻眼貓咪\n氣pupu" > /etc/nginx/elasticsearch/dic
接著再測試一次
root@ubuntu-87:~# curl 'http://localhost:9200/ikhell/_analyze?pretty=true' -H 'Content-Type: application/json' -d '{ "field": "content", "text":"傻眼貓咪氣pupu"}'
{
"tokens" : [
{
"token" : "傻眼貓咪",
"start_offset" : 0,
"end_offset" : 4,
"type" : "CN_WORD",
"position" : 0
},
{
"token" : "傻眼",
"start_offset" : 0,
"end_offset" : 2,
"type" : "CN_WORD",
"position" : 1
},
{
"token" : "貓咪",
"start_offset" : 2,
"end_offset" : 4,
"type" : "CN_WORD",
"position" : 2
},
{
"token" : "氣pupu",
"start_offset" : 4,
"end_offset" : 9,
"type" : "CN_WORD",
"position" : 3
},
{
"token" : "pupu",
"start_offset" : 5,
"end_offset" : 9,
"type" : "ENGLISH",
"position" : 4
}
]
}
可以看到我們的流行詞彙都進來了唷! 分詞結果為: 傻眼貓咪
, 傻眼
, 貓咪
, 氣pupu
, pupu
經測試發現這並不是立即生效的, 可能要等數分鐘; 請大家給他一點時間XD
尾聲
中文搜尋的基本優化也就到這邊告個段落了, 之後會沿著這個脈絡繼續做Ghost博客和Elasticsearch搭配的相關文章唷! 下次見~