es-通过Analyzer进行分词-03

Elasticsearch 通过Analyzer进行分词

Analysis 与 Analyzer

  • Analysis - 文本分析是把全文本转换一系列单词（term/token）的过程，也叫分词
  • Analysis 是通过Aanlyzer来实现的
    • 可使用Elasticsearch内置的分析器/或者按需定制化分析器
  • 除了在数据写入时转换词条，匹配Query语句时候也需要用相同的分析器对查询语句进行分析

es/es-03-01

Analyzer的组成

  • 分词器是专门处理分词的组件，Analyzer由三部分组成
    • Character Filter（针对原始文本处理，例如去除html）
    • Tokenizer （按照规则切分为单词）
    • Token Filter（将切分的单词进行加工，小写，删除stopwrods，增加同义词）

es/es-03-02

Elasticsearch 的内置分词器

  • Standard Analyzer - 默认分词器，按词切分，小写处理
  • Simple Analyzer - 按照非字母切分（符号被过滤），小写处理
  • Stop Analyzer - 小写处理，停用词过滤（the，a，is）
  • Whitespace Analyzer - 按照空格切分，不转小写
  • Keyword Analyzer - 不分词，直接将输入当作输出
  • Pattern Analyzer - 正则表达式，默认\W+（非字符分割）
  • Language - 提供了30多种常见语言的分词器
  • Customer Analyzer 自定义分词器

使用_analyzer API

  • 直接指定Analyzer进行测试 

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    GET _/_analyze  
    {
      "analyzer": "standard",
      "text": "Mastering Elasticsearch, elasticsearch in Action"
    }

  • 指定索引的字段进行测试 

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    POST books/_analyze  
    {
      "field": "title",
      "text": "Mastering Elasticsearch"
    }

  • 自定义分词进行测试

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    POST /_analyze  
    {
      "tokenizer": "standard",
      "filter": ["lowercase"],
      "text": "Mastering Elasticsearch"
    }

Standard Analyzer

es/es-03-03

  • 默认分词器
  • 按词切分
  • 小写处理
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GET _analyze  
{
  "analyzer": "standard",
  "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
}
}
符号‘-’被去除，并且单词都转为小写，
Response:
{
  "tokens" : [
    {
      "token" : "2",
      "start_offset" : 0,
      "end_offset" : 1,
      "type" : "<NUM>",
      "position" : 0
    },
    {
      "token" : "running",
      "start_offset" : 2,
      "end_offset" : 9,
      "type" : "<ALPHANUM>",
      "position" : 1
    },
    {
      "token" : "quick",
      "start_offset" : 10,
      "end_offset" : 15,
      "type" : "<ALPHANUM>",
      "position" : 2
    },
    {
      "token" : "brown",
      "start_offset" : 16,
      "end_offset" : 21,
      "type" : "<ALPHANUM>",
      "position" : 3
    },
    {
      "token" : "foxes",
      "start_offset" : 22,
      "end_offset" : 27,
      "type" : "<ALPHANUM>",
      "position" : 4
    },
    {
      "token" : "leap",
      "start_offset" : 28,
      "end_offset" : 32,
      "type" : "<ALPHANUM>",
      "position" : 5
    },
    {
      "token" : "over",
      "start_offset" : 33,
      "end_offset" : 37,
      "type" : "<ALPHANUM>",
      "position" : 6
    },
    {
      "token" : "lazy",
      "start_offset" : 38,
      "end_offset" : 42,
      "type" : "<ALPHANUM>",
      "position" : 7
    },
    {
      "token" : "dags",
      "start_offset" : 43,
      "end_offset" : 47,
      "type" : "<ALPHANUM>",
      "position" : 8
    },
    {
      "token" : "in",
      "start_offset" : 48,
      "end_offset" : 50,
      "type" : "<ALPHANUM>",
      "position" : 9
    },
    {
      "token" : "the",
      "start_offset" : 51,
      "end_offset" : 54,
      "type" : "<ALPHANUM>",
      "position" : 10
    },
    {
      "token" : "summer",
      "start_offset" : 55,
      "end_offset" : 61,
      "type" : "<ALPHANUM>",
      "position" : 11
    },
    {
      "token" : "evening",
      "start_offset" : 62,
      "end_offset" : 69,
      "type" : "<ALPHANUM>",
      "position" : 12
    }
  ]
}

Simple Analyzer

es/es-03-04

  • 按照非字母切分，非字母的都被去除
  • 小写处理
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    GET _analyze
    {
      "analyzer": "simple",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }
    这里2 被去除了，还有符号‘-’，并且单词都转为小写，
    Response:
    {
      "tokens" : [
        {
          "token" : "running",
          "start_offset" : 2,
          "end_offset" : 9,
          "type" : "word",
          "position" : 0
        },
        {
          "token" : "quick",
          "start_offset" : 10,
          "end_offset" : 15,
          "type" : "word",
          "position" : 1
        },
        {
          "token" : "brown",
          "start_offset" : 16,
          "end_offset" : 21,
          "type" : "word",
          "position" : 2
        },
        {
          "token" : "foxes",
          "start_offset" : 22,
          "end_offset" : 27,
          "type" : "word",
          "position" : 3
        },
        {
          "token" : "leap",
          "start_offset" : 28,
          "end_offset" : 32,
          "type" : "word",
          "position" : 4
        },
        {
          "token" : "over",
          "start_offset" : 33,
          "end_offset" : 37,
          "type" : "word",
          "position" : 5
        },
        {
          "token" : "lazy",
          "start_offset" : 38,
          "end_offset" : 42,
          "type" : "word",
          "position" : 6
        },
        {
          "token" : "dags",
          "start_offset" : 43,
          "end_offset" : 47,
          "type" : "word",
          "position" : 7
        },
        {
          "token" : "in",
          "start_offset" : 48,
          "end_offset" : 50,
          "type" : "word",
          "position" : 8
        },
        {
          "token" : "the",
          "start_offset" : 51,
          "end_offset" : 54,
          "type" : "word",
          "position" : 9
        },
        {
          "token" : "summer",
          "start_offset" : 55,
          "end_offset" : 61,
          "type" : "word",
          "position" : 10
        },
        {
          "token" : "evening",
          "start_offset" : 62,
          "end_offset" : 69,
          "type" : "word",
          "position" : 11
        }
      ]
    }

Whitespace Analyzer

es/es-03-06

  • 按照空格切分
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    GET _analyze
    {
      "analyzer": "whitespace",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }

    Response:
    {
      "tokens" : [
        {
          "token" : "2",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "word",
          "position" : 0
        },
        {
          "token" : "running",
          "start_offset" : 2,
          "end_offset" : 9,
          "type" : "word",
          "position" : 1
        },
        {
          "token" : "Quick",
          "start_offset" : 10,
          "end_offset" : 15,
          "type" : "word",
          "position" : 2
        },
        {
          "token" : "brown-foxes",
          "start_offset" : 16,
          "end_offset" : 27,
          "type" : "word",
          "position" : 3
        },
        {
          "token" : "leap",
          "start_offset" : 28,
          "end_offset" : 32,
          "type" : "word",
          "position" : 4
        },
        {
          "token" : "over",
          "start_offset" : 33,
          "end_offset" : 37,
          "type" : "word",
          "position" : 5
        },
        {
          "token" : "lazy",
          "start_offset" : 38,
          "end_offset" : 42,
          "type" : "word",
          "position" : 6
        },
        {
          "token" : "dags",
          "start_offset" : 43,
          "end_offset" : 47,
          "type" : "word",
          "position" : 7
        },
        {
          "token" : "in",
          "start_offset" : 48,
          "end_offset" : 50,
          "type" : "word",
          "position" : 8
        },
        {
          "token" : "the",
          "start_offset" : 51,
          "end_offset" : 54,
          "type" : "word",
          "position" : 9
        },
        {
          "token" : "summer",
          "start_offset" : 55,
          "end_offset" : 61,
          "type" : "word",
          "position" : 10
        },
        {
          "token" : "evening",
          "start_offset" : 62,
          "end_offset" : 69,
          "type" : "word",
          "position" : 11
        }
      ]
    }

Stop Analyzer

es/es-03-05

  • 相比Simpler Analyzer 多了stop Filter
  • 会把 the，a，is等修饰性词语去除
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    GET _analyze
    {
      "analyzer": "stop",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }
    这里把 2,'-',in,the都去除了
    Response:
    {
      "tokens" : [
        {
          "token" : "running",
          "start_offset" : 2,
          "end_offset" : 9,
          "type" : "word",
          "position" : 0
        },
        {
          "token" : "quick",
          "start_offset" : 10,
          "end_offset" : 15,
          "type" : "word",
          "position" : 1
        },
        {
          "token" : "brown",
          "start_offset" : 16,
          "end_offset" : 21,
          "type" : "word",
          "position" : 2
        },
        {
          "token" : "foxes",
          "start_offset" : 22,
          "end_offset" : 27,
          "type" : "word",
          "position" : 3
        },
        {
          "token" : "leap",
          "start_offset" : 28,
          "end_offset" : 32,
          "type" : "word",
          "position" : 4
        },
        {
          "token" : "over",
          "start_offset" : 33,
          "end_offset" : 37,
          "type" : "word",
          "position" : 5
        },
        {
          "token" : "lazy",
          "start_offset" : 38,
          "end_offset" : 42,
          "type" : "word",
          "position" : 6
        },
        {
          "token" : "dags",
          "start_offset" : 43,
          "end_offset" : 47,
          "type" : "word",
          "position" : 7
        },
        {
          "token" : "summer",
          "start_offset" : 55,
          "end_offset" : 61,
          "type" : "word",
          "position" : 10
        },
        {
          "token" : "evening",
          "start_offset" : 62,
          "end_offset" : 69,
          "type" : "word",
          "position" : 11
        }
      ]
    }

Keyword Analyzer

es/es-03-07

  • 不分词，直接将输入当一个term输出
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    GET _analyze
    {
      "analyzer": "keyword",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }
    Response:
    {
      "tokens" : [
        {
          "token" : "2 running Quick brown-foxes leap over lazy dags in the summer evening",
          "start_offset" : 0,
          "end_offset" : 69,
          "type" : "word",
          "position" : 0
        }
      ]
    }

Pattern Analyzer

es/es-03-08

  • 通过正则表达式进行分词
  • 默认是\W+，非字符的符号进行分隔
  • 转小写
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    GET _analyze
    {
      "analyzer": "pattern",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }
    Response:
    {
      "tokens" : [
        {
          "token" : "2",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "word",
          "position" : 0
        },
        {
          "token" : "running",
          "start_offset" : 2,
          "end_offset" : 9,
          "type" : "word",
          "position" : 1
        },
        {
          "token" : "quick",
          "start_offset" : 10,
          "end_offset" : 15,
          "type" : "word",
          "position" : 2
        },
        {
          "token" : "brown",
          "start_offset" : 16,
          "end_offset" : 21,
          "type" : "word",
          "position" : 3
        },
        {
          "token" : "foxes",
          "start_offset" : 22,
          "end_offset" : 27,
          "type" : "word",
          "position" : 4
        },
        {
          "token" : "leap",
          "start_offset" : 28,
          "end_offset" : 32,
          "type" : "word",
          "position" : 5
        },
        {
          "token" : "over",
          "start_offset" : 33,
          "end_offset" : 37,
          "type" : "word",
          "position" : 6
        },
        {
          "token" : "lazy",
          "start_offset" : 38,
          "end_offset" : 42,
          "type" : "word",
          "position" : 7
        },
        {
          "token" : "dags",
          "start_offset" : 43,
          "end_offset" : 47,
          "type" : "word",
          "position" : 8
        },
        {
          "token" : "in",
          "start_offset" : 48,
          "end_offset" : 50,
          "type" : "word",
          "position" : 9
        },
        {
          "token" : "the",
          "start_offset" : 51,
          "end_offset" : 54,
          "type" : "word",
          "position" : 10
        },
        {
          "token" : "summer",
          "start_offset" : 55,
          "end_offset" : 61,
          "type" : "word",
          "position" : 11
        },
        {
          "token" : "evening",
          "start_offset" : 62,
          "end_offset" : 69,
          "type" : "word",
          "position" : 12
        }
      ]
    }

Language Analyzer

es/es-03-09

  • es 提供了30多种常见语言的分词器
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    GET _analyze
    {
      "analyzer": "english",
      "text": "2 running Quick brown-foxes leap over lazy dags in the summer evening"
    }
    Response:
    {
      "tokens" : [
        {
          "token" : "2",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "<NUM>",
          "position" : 0
        },
        {
          "token" : "run",
          "start_offset" : 2,
          "end_offset" : 9,
          "type" : "<ALPHANUM>",
          "position" : 1
        },
        {
          "token" : "quick",
          "start_offset" : 10,
          "end_offset" : 15,
          "type" : "<ALPHANUM>",
          "position" : 2
        },
        {
          "token" : "brown",
          "start_offset" : 16,
          "end_offset" : 21,
          "type" : "<ALPHANUM>",
          "position" : 3
        },
        {
          "token" : "fox",
          "start_offset" : 22,
          "end_offset" : 27,
          "type" : "<ALPHANUM>",
          "position" : 4
        },
        {
          "token" : "leap",
          "start_offset" : 28,
          "end_offset" : 32,
          "type" : "<ALPHANUM>",
          "position" : 5
        },
        {
          "token" : "over",
          "start_offset" : 33,
          "end_offset" : 37,
          "type" : "<ALPHANUM>",
          "position" : 6
        },
        {
          "token" : "lazi",
          "start_offset" : 38,
          "end_offset" : 42,
          "type" : "<ALPHANUM>",
          "position" : 7
        },
        {
          "token" : "dag",
          "start_offset" : 43,
          "end_offset" : 47,
          "type" : "<ALPHANUM>",
          "position" : 8
        },
        {
          "token" : "summer",
          "start_offset" : 55,
          "end_offset" : 61,
          "type" : "<ALPHANUM>",
          "position" : 11
        },
        {
          "token" : "even",
          "start_offset" : 62,
          "end_offset" : 69,
          "type" : "<ALPHANUM>",
          "position" : 12
        }
      ]
    }

ICU Analyzer

  • 需要安装plugin
    • Elasticsearch-plugin install analysis-icu
  • 提供了Unicode的支持，更好的支持亚洲语言

中文分词

中文分词的难点

  • 中文句子切分成一个一个词（不是一个个字）
  • 英文中，单词有自然的空格做为分隔
  • 一句中文，在不同的上下文，有不同的理解
    • 这个苹果，不大好吃/这个苹果，不大，好吃！
  • 一些例子
    • 他说的确实在理/这事的确定下来

中文分词器，这里安装了IK

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docker-compose exec es01 elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.5.2/elasticsearch-analysis-ik-7.5.2.zip
docker-compose restart
  • 拿standard Analyzer 和 IK Analyzer 做个对比吧
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    GET _analyze
    {
      "analyzer": "standard",
      "text": "他说的确实在理"
    }
    被拆分成一个个的字
    Response:
    {
      "tokens" : [
        {
          "token" : "他",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "<IDEOGRAPHIC>",
          "position" : 0
        },
        {
          "token" : "说",
          "start_offset" : 1,
          "end_offset" : 2,
          "type" : "<IDEOGRAPHIC>",
          "position" : 1
        },
        {
          "token" : "的",
          "start_offset" : 2,
          "end_offset" : 3,
          "type" : "<IDEOGRAPHIC>",
          "position" : 2
        },
        {
          "token" : "确",
          "start_offset" : 3,
          "end_offset" : 4,
          "type" : "<IDEOGRAPHIC>",
          "position" : 3
        },
        {
          "token" : "实",
          "start_offset" : 4,
          "end_offset" : 5,
          "type" : "<IDEOGRAPHIC>",
          "position" : 4
        },
        {
          "token" : "在",
          "start_offset" : 5,
          "end_offset" : 6,
          "type" : "<IDEOGRAPHIC>",
          "position" : 5
        },
        {
          "token" : "理",
          "start_offset" : 6,
          "end_offset" : 7,
          "type" : "<IDEOGRAPHIC>",
          "position" : 6
        }
      ]
    }


    GET _analyze
    {
      "analyzer": "ik_smart",
      "text": "他说的确实在理"
    }
    拆分出单个字和一些中文词语的组合,相比standard analyzer 来说，效果还是比较不错的
    Response:
    {
      "tokens" : [
        {
          "token" : "他",
          "start_offset" : 0,
          "end_offset" : 1,
          "type" : "CN_CHAR",
          "position" : 0
        },
        {
          "token" : "说",
          "start_offset" : 1,
          "end_offset" : 2,
          "type" : "CN_CHAR",
          "position" : 1
        },
        {
          "token" : "的确",
          "start_offset" : 2,
          "end_offset" : 4,
          "type" : "CN_WORD",
          "position" : 2
        },
        {
          "token" : "实",
          "start_offset" : 4,
          "end_offset" : 5,
          "type" : "CN_CHAR",
          "position" : 3
        },
        {
          "token" : "在理",
          "start_offset" : 5,
          "end_offset" : 7,
          "type" : "CN_WORD",
          "position" : 4
        }
      ]
    }

拼音分词器

拼音分词器体验了这个插件，https://github.com/medcl/elasticsearch-analysis-pinyin，

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插件在docker 中的安装方式
docker-compose exec es01 elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-pinyin，
docker-compose restart

推荐用下面这种方式，支持中文和拼音混合搜索,搜索的结果比较贴合需求

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PUT /medcl3/
{
   "settings" : {
       "analysis" : {
           "analyzer" : {
               "pinyin_analyzer" : {
                   "tokenizer" : "my_pinyin"
                   }
           },
           "tokenizer" : {
               "my_pinyin" : {
                   "type" : "pinyin",
                   "keep_first_letter":true,
                   "keep_separate_first_letter" : true,
                   "keep_full_pinyin" : true,
                   "keep_original" : false,
                   "limit_first_letter_length" : 16,
                   "lowercase" : true
               }
           }
       }
   }
}
   
POST /medcl3/_mapping 
{
  "properties": {
      "name": {
          "type": "keyword",
          "fields": {
              "pinyin": {
                  "type": "text",
                  "store": false,
                  "term_vector": "with_offsets",
                  "analyzer": "pinyin_analyzer",
                  "boost": 10
              }
          }
      }
  }
}
  
   
GET /medcl3/_analyze
{
   "text": ["刘德华"],
   "analyzer": "pinyin_analyzer"
}
 
POST /medcl3/_create/andy
{"name":"刘德华"}

GET /medcl3/_search
{
 "query": {"match_phrase": {
   "name.pinyin": "刘德h"
 }}
}

GET /medcl3/_search
{
 "query": {"match_phrase": {
   "name.pinyin": "刘dh"
 }}
}

GET /medcl3/_search
{
 "query": {"match_phrase": {
   "name.pinyin": "liudh"
 }}
}

GET /medcl3/_search
{
 "query": {"match_phrase": {
   "name.pinyin": "liudeh"
 }}
}

GET /medcl3/_search
{
 "query": {"match_phrase": {
   "name.pinyin": "liude华"
 }}
Elasticsearch
es-通过Analyzer进行分词-03
http://example.com/2022/11/06/es/es-通过Analyzer进行分词-03/
作者
weijun Wu
发布于
2022年11月6日
许可协议