ES分词器详解

一、分词器

1、作用：①切词

　　　　  ②normalizaton（提升recall召回率：能搜索到的结果的比率）

2、分析器

①character filter：分词之前预处理（过滤无用字符、标签等，转换一些&=>and 《Elasticsearch》=> Elasticsearch

　　A、HTML Strip Character Filter：html_strip

　　　　escaped_tags   需要保留的html标签

PUT my_index
{
  "settings": {
    "analysis": {
      "char_filter": {
        "my_char_filter":{
          "type":"html_strip",
　　　　　　"escaped_tags":["a"]
        }
      },
      "analyzer": {
        "my_analyzer":{
          "tokenizer":"keyword",
          "char_filter":"my_char_filter"
        }
      }
    }
  }
}
测试分词

　　GET my_index/_analyze
　　{
　　　　"analyzer": "my_analyzer",
　　　　"text": "liuyucheng <a><b>edu</b></a>"
　　}

　　B、Mapping Character Filter：type mapping

PUT my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "keyword",
          "char_filter": [
            "my_char_filter"
          ]
        }
      },
      "char_filter": {
        "my_char_filter": {
          "type": "mapping",
          "mappings": [
            "٠ => 0",
            "١ => 1",
            "٢ => 2",
            "٣ => 3",
            "٤ => 4",
            "٥ => 5",
            "٦ => 6",
            "٧ => 7",
            "٨ => 8",
            "٩ => 9"
          ]
        }
      }
    }
  }
}
测试分词
POST my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "My license plate is ٢٥٠١٥"
}

　　C、Pattern Replace Character Filter：正则替换type pattern_replace

PUT my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "standard",
          "char_filter": ["my_char_filter"]
        }
      },
      "char_filter": {
        "my_char_filter": {
          "type": "pattern_replace",
          "pattern": "(\d+)-(?=\d)",
          "replacement": "$1_"
        }
      }
    }
  }
}
测试分词
POST my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "My credit card is 123-456-789"
}

②tokenizer：分词器

③token filter：时态转换、大小写转换、同义词转换、语气词处理等

　　　　　　  比如：has=>have  him=>he  apples=>apple  the/oh/a=>干掉

　　A、大小写 lowercase token filter

GET _analyze
{
  "tokenizer" : "standard",
  "filter" : ["lowercase"],
  "text" : "THE Quick FoX JUMPs"
}

GET /_analyze
{
  "tokenizer": "standard",
  "filter": [
    {
      "type": "condition",
      "filter": [ "lowercase" ],
      "script": {
        "source": "token.getTerm().length() < 5"
      }
    }
  ],
  "text": "THE QUICK BROWN FOX"
}

　　B、停用词 stopwords token filter

PUT /my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer":{
          "type":"standard",
          "stopwords":"_english_"
        }
      }
    }
  }
}
GET my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "Teacher Ma is in the restroom"
}

　　C、分词器  tokenizer ：standard

GET /my_index/_analyze
{
  "text": "江山如此多娇,小姐姐哪里可以撩",
  "analyzer": "standard"
}

　　D、自定义 analysis，设置type为custom告诉Elasticsearch我们正在定义一个定制分析器。将此与配置内置分析器的方式进行比较： type将设置为内置分析器的名称，如 standard或simple

PUT /test_analysis
{
  "settings": {
    "analysis": {
      "char_filter": {
        "test_char_filter": {
          "type": "mapping",
          "mappings": [
            "& => and",
            "| => or"
          ]
        }
      },
      "filter": {
        "test_stopwords": {
          "type": "stop",
          "stopwords": ["is","in","at","the","a","for"]
        }
      },
      "tokenizer": {
        "punctuation": { 
          "type": "pattern",
          "pattern": "[ .,!?]"
        }
      },
      "analyzer": {
        "my_analyzer": {
          "type": "custom",
          "char_filter": [
            "html_strip",
            "test_char_filter"
          ],
          "tokenizer": "standard",
          "filter": ["lowercase","test_stopwords"]
        }
      }
    }
  }
}

GET /test_analysis/_analyze
{
  "text": "Teacher ma & zhang also thinks [mother's friends] is good | nice!!!",
  "analyzer": "my_analyzer"
}

　　E、创建mapping时候指定分词器

PUT /test_analysis/_mapping/my_type
{
  "properties": {
    "content": {
      "type": "text",
      "analyzer": "test_analysis"
    }
  }
}

 二、中文分词器

(1) 中文分词器：

　　① IK分词：ES的安装目录  不要有中文  空格

　　1) 下载：https://github.com/medcl/elasticsearch-analysis-ik

　　2) 创建插件文件夹 cd your-es-root/plugins/ && mkdir ik

　　3) 将插件解压缩到文件夹 your-es-root/plugins/ik

　　4) 重新启动es

　　② 两种analyzer

　　1) ik_max_word：细粒度

　　2) ik_smart：粗粒度

　　③ IK文件描述

　　1) IKAnalyzer.cfg.xml：IK分词配置文件

　　2) 主词库：main.dic

　　3) 英文停用词：stopword.dic，不会建立在倒排索引中

　　4) 特殊词库：

1. quantifier.dic：特殊词库：计量单位等
2. suffix.dic：特殊词库：后缀名
3. surname.dic：特殊词库：百家姓
4. preposition：特殊词库：语气词

　　5) 自定义词库：比如当下流行词：857、emmm...、渣女、舔屏、996

　　6) 热更新：

1. 修改ik分词器源码
2. 基于ik分词器原生支持的热更新方案，部署一个web服务器，提供一个http接口，通过modified和tag两个http响应头，来提供词语的热更新