Hindi analyzer

The built-in hindi analyzer can be applied to a text field using the following command:

  1. PUT /hindi-index
  2. {
  3.   "mappings": {
  4.     "properties": {
  5.       "content": {
  6.         "type": "text",
  7.         "analyzer": "hindi"
  8.       }
  9.     }
  10.   }
  11. }

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Stem exclusion

You can use stem_exclusion with this language analyzer using the following command:

  1. PUT index_with_stem_exclusion_hindi_analyzer
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "analyzer": {
  6.         "stem_exclusion_hindi_analyzer": {
  7.           "type": "hindi",
  8.           "stem_exclusion": ["अधिकार", "अनुमोदन"]
  9.         }
  10.       }
  11.     }
  12.   }
  13. }

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Hindi analyzer internals

The hindi analyzer is built using the following components:

  • Tokenizer: standard

  • Token filters:

    • lowercase
    • decimal_digit
    • keyword
    • normalization (indic)
    • normalization (Hindi)
    • stop (Hindi)
    • stemmer (Hindi)

Custom Hindi analyzer

You can create a custom Hindi analyzer using the following command:

  1. PUT /hindi-index
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "filter": {
  6.         "hindi_stop": {
  7.           "type": "stop",
  8.           "stopwords": "_hindi_"
  9.         },
  10.         "hindi_stemmer": {
  11.           "type": "stemmer",
  12.           "language": "hindi"
  13.         },
  14.         "hindi_keywords": {
  15.           "type": "keyword_marker",
  16.           "keywords": []
  17.         }
  18.       },
  19.       "analyzer": {
  20.         "hindi_analyzer": {
  21.           "type": "custom",
  22.           "tokenizer": "standard",
  23.           "filter": [
  24.             "lowercase",
  25.             "decimal_digit",
  26.             "hindi_keywords",
  27.             "indic_normalization",
  28.             "hindi_normalization",
  29.             "hindi_stop",
  30.             "hindi_stemmer"
  31.           ]
  32.         }
  33.       }
  34.     }
  35.   },
  36.   "mappings": {
  37.     "properties": {
  38.       "content": {
  39.         "type": "text",
  40.         "analyzer": "hindi_analyzer"
  41.       }
  42.     }
  43.   }
  44. }

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Generated tokens

Use the following request to examine the tokens generated using the analyzer:

  1. POST /hindi-index/_analyze
  2. {
  3.   "field": "content",
  4.   "text": "छात्र भारतीय विश्वविद्यालयों में पढ़ते हैं। उनके नंबर १२३४५६ हैं।"
  5. }

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The response contains the generated tokens:

  1. {
  2.   "tokens": [
  3.     {
  4.       "token": "छातर",
  5.       "start_offset": 0,
  6.       "end_offset": 5,
  7.       "type": "<ALPHANUM>",
  8.       "position": 0
  9.     },
  10.     {
  11.       "token": "भारतिय",
  12.       "start_offset": 6,
  13.       "end_offset": 12,
  14.       "type": "<ALPHANUM>",
  15.       "position": 1
  16.     },
  17.     {
  18.       "token": "विशवविदयालय",
  19.       "start_offset": 13,
  20.       "end_offset": 28,
  21.       "type": "<ALPHANUM>",
  22.       "position": 2
  23.     },
  24.     {
  25.       "token": "पढ",
  26.       "start_offset": 33,
  27.       "end_offset": 38,
  28.       "type": "<ALPHANUM>",
  29.       "position": 4
  30.     },
  31.     {
  32.       "token": "नंबर",
  33.       "start_offset": 49,
  34.       "end_offset": 53,
  35.       "type": "<ALPHANUM>",
  36.       "position": 7
  37.     },
  38.     {
  39.       "token": "123456",
  40.       "start_offset": 54,
  41.       "end_offset": 60,
  42.       "type": "<NUM>",
  43.       "position": 8
  44.     }
  45.   ]
  46. }