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Pinyin Analysis for Elasticsearch

This Pinyin Analysis plugin is used to do conversion between Chinese characters and Pinyin, integrates NLP tools (https://github.com/NLPchina/nlp-lang).

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| Pinyin   Analysis Plugin      | Elasticsearch  |
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| master                        | 6.x -> master  |
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| 6.3.0                         | 6.3.0          |
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| 6.2.4                         | 6.2.4          |
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| 6.1.4                         | 6.1.4          |
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| 5.6.9                         | 5.6.9          |
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| 5.5.3                         | 5.5.3          |
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| 5.4.3                         | 5.4.3          |
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| 5.3.3                         | 5.3.3          |
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| 5.2.2                         | 5.2.2          |
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| 5.1.2                         | 5.1.2          |
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| 1.8.1                         | 2.4.1          |
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| 1.7.5                         | 2.3.5          |
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| 1.6.1                         | 2.2.1          |
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| 1.5.0                         | 2.1.0          |
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| 1.4.0                         | 2.0.x          |
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| 1.3.0                         | 1.6.x          |
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| 1.2.2                         | 1.0.x          |
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The plugin includes analyzer: pinyin , tokenizer: pinyin and token-filter: pinyin.

** Optional Parameters **

  • keep_first_letter when this option enabled, eg: 刘德华>ldh, default: true
  • keep_separate_first_letter when this option enabled, will keep first letters separately, eg: 刘德华>l,d,h, default: false, NOTE: query result maybe too fuzziness due to term too frequency
  • limit_first_letter_length set max length of the first_letter result, default: 16
  • keep_full_pinyin when this option enabled, eg: 刘德华> [liu,de,hua], default: true
  • keep_joined_full_pinyin when this option enabled, eg: 刘德华> [liudehua], default: false
  • keep_none_chinese keep non chinese letter or number in result, default: true
  • keep_none_chinese_together keep non chinese letter together, default: true, eg: DJ音乐家 -> DJ,yin,yue,jia, when set to false, eg: DJ音乐家 -> D,J,yin,yue,jia, NOTE: keep_none_chinese should be enabled first
  • keep_none_chinese_in_first_letter keep non Chinese letters in first letter, eg: 刘德华AT2016->ldhat2016, default: true
  • keep_none_chinese_in_joined_full_pinyin keep non Chinese letters in joined full pinyin, eg: 刘德华2016->liudehua2016, default: false
  • none_chinese_pinyin_tokenize break non chinese letters into separate pinyin term if they are pinyin, default: true, eg: liudehuaalibaba13zhuanghan -> liu,de,hua,a,li,ba,ba,13,zhuang,han, NOTE: keep_none_chinese and keep_none_chinese_together should be enabled first
  • keep_original when this option enabled, will keep original input as well, default: false
  • lowercase lowercase non Chinese letters, default: true
  • trim_whitespace default: true
  • remove_duplicated_term when this option enabled, duplicated term will be removed to save index, eg: de的>de, default: false, NOTE: position related query maybe influenced
  • ignore_pinyin_offset after 6.0, offset is strictly constrained, overlapped tokens are not allowed, with this parameter, overlapped token will allowed by ignore offset, please note, all position related query or highlight will become incorrect, you should use multi fields and specify different settings for different query purpose. if you need offset, please set it to false. default: true.

1.Create a index with custom pinyin analyzer

PUT /medcl/ 
{
    "index" : {
        "analysis" : {
            "analyzer" : {
                "pinyin_analyzer" : {
                    "tokenizer" : "my_pinyin"
                    }
            },
            "tokenizer" : {
                "my_pinyin" : {
                    "type" : "pinyin",
                    "keep_separate_first_letter" : false,
                    "keep_full_pinyin" : true,
                    "keep_original" : true,
                    "limit_first_letter_length" : 16,
                    "lowercase" : true,
                    "remove_duplicated_term" : true
                }
            }
        }
    }
}

2.Test Analyzer, analyzing a chinese name, such as 刘德华

GET /medcl/_analyze
{
  "text": ["刘德华"],
  "analyzer": "pinyin_analyzer"
}
{
  "tokens" : [
    {
      "token" : "liu",
      "start_offset" : 0,
      "end_offset" : 1,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "de",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "hua",
      "start_offset" : 2,
      "end_offset" : 3,
      "type" : "word",
      "position" : 2
    },
    {
      "token" : "刘德华",
      "start_offset" : 0,
      "end_offset" : 3,
      "type" : "word",
      "position" : 3
    },
    {
      "token" : "ldh",
      "start_offset" : 0,
      "end_offset" : 3,
      "type" : "word",
      "position" : 4
    }
  ]
}

3.Create mapping

POST /medcl/folks/_mapping 
{
    "folks": {
        "properties": {
            "name": {
                "type": "keyword",
                "fields": {
                    "pinyin": {
                        "type": "text",
                        "store": false,
                        "term_vector": "with_offsets",
                        "analyzer": "pinyin_analyzer",
                        "boost": 10
                    }
                }
            }
        }
    }
}

4.Indexing

POST /medcl/folks/andy 
{"name":"刘德华"}

5.Let's search

http://localhost:9200/medcl/folks/_search?q=name:%E5%88%98%E5%BE%B7%E5%8D%8E
curl http://localhost:9200/medcl/folks/_search?q=name.pinyin:%e5%88%98%e5%be%b7
curl http://localhost:9200/medcl/folks/_search?q=name.pinyin:liu
curl http://localhost:9200/medcl/folks/_search?q=name.pinyin:ldh
curl http://localhost:9200/medcl/folks/_search?q=name.pinyin:de+hua

6.Using Pinyin-TokenFilter

PUT /medcl1/ 
{
    "index" : {
        "analysis" : {
            "analyzer" : {
                "user_name_analyzer" : {
                    "tokenizer" : "whitespace",
                    "filter" : "pinyin_first_letter_and_full_pinyin_filter"
                }
            },
            "filter" : {
                "pinyin_first_letter_and_full_pinyin_filter" : {
                    "type" : "pinyin",
                    "keep_first_letter" : true,
                    "keep_full_pinyin" : false,
                    "keep_none_chinese" : true,
                    "keep_original" : false,
                    "limit_first_letter_length" : 16,
                    "lowercase" : true,
                    "trim_whitespace" : true,
                    "keep_none_chinese_in_first_letter" : true
                }
            }
        }
    }
}

Token Test:刘德华 张学友 郭富城 黎明 四大天王

GET /medcl/_analyze
{
  "text": ["刘德华 张学友 郭富城 黎明 四大天王"],
  "analyzer": "user_name_analyzer"
}

{
  "tokens" : [
    {
      "token" : "ldh",
      "start_offset" : 0,
      "end_offset" : 3,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "zxy",
      "start_offset" : 4,
      "end_offset" : 7,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "gfc",
      "start_offset" : 8,
      "end_offset" : 11,
      "type" : "word",
      "position" : 2
    },
    {
      "token" : "lm",
      "start_offset" : 12,
      "end_offset" : 14,
      "type" : "word",
      "position" : 3
    },
    {
      "token" : "sdtw",
      "start_offset" : 15,
      "end_offset" : 19,
      "type" : "word",
      "position" : 4
    }
  ]
}

7.Used in phrase query

  • option 1

      PUT /medcl/
  {
      "index" : {
          "analysis" : {
              "analyzer" : {
                  "pinyin_analyzer" : {
                      "tokenizer" : "my_pinyin"
                      }
              },
              "tokenizer" : {
                  "my_pinyin" : {
                      "type" : "pinyin",
                      "keep_first_letter":false,
                      "keep_separate_first_letter" : false,
                      "keep_full_pinyin" : true,
                      "keep_original" : false,
                      "limit_first_letter_length" : 16,
                      "lowercase" : true
                  }
              }
          }
      }
  }
  GET /medcl/folks/_search
  {
    "query": {"match_phrase": {
      "name.pinyin": "刘德华"
    }}
  }

  • option 2

    • 



DELETE medcl


PUT /medcl/
{
"index" : {
"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 /medcl/folks/_mapping
{
"folks": {
"properties": {
"name": {
"type": "keyword",
"fields": {
"pinyin": {
"type": "text",
"store": false,
"term_vector": "with_offsets",
"analyzer": "pinyin_analyzer",
"boost": 10
}
}
}
}
}
}


GET /medcl/_analyze
{
"text": ["刘德华"],
"analyzer": "pinyin_analyzer"
}


POST /medcl/folks/andy
{"name":"刘德华"}


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


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


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


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


GET /medcl/folks/_search
{
"query": {"match_phrase": {
"name.pinyin": "liude华"
}}
}


</pre>



8.That's all, have fun.