ElasticSearch入门elasticsearch玩转大数据

五十九、Elasticsearch索引管理-修改分词器以及定制自

2017-07-12  本文已影响1340人  编程界的小学生

1、默认的分词器

standard

standard tokenizer:以单词为边界进行切分
standard token filter:什么都不做
lowercase token filter:将所有字母转换为小写
stop token filter(默认被禁用):移除停用词,比如a an the it等等

2、修改分词器的设置

需求:上面说了stop token filter默认被禁用。 现在需要启用english的停用词token filter

PUT /my_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "es_std" : {
          "type" : "standard",
          "stopwords" : "_english_"
        }
      }
    }
  }
}

测试分词
(1)先用标准的standard分词查看结果

GET /my_index/_analyze
{
  "analyzer": "standard", 
  "text": "a dog is in the house"
}

返回结果

{
  "tokens": [
    {
      "token": "a",
      "start_offset": 0,
      "end_offset": 1,
      "type": "<ALPHANUM>",
      "position": 0
    },
    {
      "token": "dog",
      "start_offset": 2,
      "end_offset": 5,
      "type": "<ALPHANUM>",
      "position": 1
    },
    {
      "token": "is",
      "start_offset": 6,
      "end_offset": 8,
      "type": "<ALPHANUM>",
      "position": 2
    },
    {
      "token": "in",
      "start_offset": 9,
      "end_offset": 11,
      "type": "<ALPHANUM>",
      "position": 3
    },
    {
      "token": "the",
      "start_offset": 12,
      "end_offset": 15,
      "type": "<ALPHANUM>",
      "position": 4
    },
    {
      "token": "house",
      "start_offset": 16,
      "end_offset": 21,
      "type": "<ALPHANUM>",
      "position": 5
    }
  ]
}

结果表明没有自动去掉a,the,in等词项。

(2)用我们修改过的分词器

GET /my_index/_analyze
{
  "analyzer": "es_std", 
  "text": "a dog is in the house"
}

结果

{
  "tokens": [
    {
      "token": "dog",
      "start_offset": 2,
      "end_offset": 5,
      "type": "<ALPHANUM>",
      "position": 1
    },
    {
      "token": "house",
      "start_offset": 16,
      "end_offset": 21,
      "type": "<ALPHANUM>",
      "position": 5
    }
  ]
}

结果表明已经去掉了a the in这些。

3、定制化自己的分词器

PUT /my_index
{
  "settings": {
    "analysis": {
      "char_filter": {
        "&_to_and": {
          "type": "mapping",
          "mappings": ["&=> and"]
        }
      },
      "filter": {
        "my_stopwords": {
          "type": "stop",
          "stopwords": ["the", "a"]
        }
      },
      "analyzer": {
        "my_analyzer": {
          "type": "custom",
          "char_filter": ["html_strip", "&_to_and"],
          "tokenizer": "standard",
          "filter": ["lowercase", "my_stopwords"]
        }
      }
    }
  }
}

测试

GET /my_index/_analyze
{
  "text": "tom&jerry are a friend in the house, <a>, HAHA!!",
  "analyzer": "my_analyzer"
}

结果

{
  "tokens": [
    {
      "token": "tomandjerry",
      "start_offset": 0,
      "end_offset": 9,
      "type": "<ALPHANUM>",
      "position": 0
    },
    {
      "token": "are",
      "start_offset": 10,
      "end_offset": 13,
      "type": "<ALPHANUM>",
      "position": 1
    },
    {
      "token": "friend",
      "start_offset": 16,
      "end_offset": 22,
      "type": "<ALPHANUM>",
      "position": 3
    },
    {
      "token": "in",
      "start_offset": 23,
      "end_offset": 25,
      "type": "<ALPHANUM>",
      "position": 4
    },
    {
      "token": "house",
      "start_offset": 30,
      "end_offset": 35,
      "type": "<ALPHANUM>",
      "position": 6
    },
    {
      "token": "haha",
      "start_offset": 42,
      "end_offset": 46,
      "type": "<ALPHANUM>",
      "position": 7
    }
  ]
}

可以发现自动将&转换成了and,自动去掉了are a等

可以为我们定制的分词器添加field

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

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