Языковые анализаторы
Набор анализаторов, предназначенных для анализа текста конкретного языка. Поддерживаются следующие типы: arabic, armenian, basque, bengali, brazilian, bulgarian, catalan, cjk, czech, danish, dutch, english, estonian, finnish, french, galician, german, greek, hindi, hungarian, indonesian, irish, italian, latvian, lithuanian, norwegian, persian, portuguese, romanian, russian, serbian, sorani, spanish, swedish, turkish, thai.
Настройка языковых анализаторов
Стоп-слова
Все анализаторы поддерживают настройку пользовательских stopwords либо внутри конфигурации, либо с помощью внешнего файла стоп-слов, установив stopwords_path. Подробнее см. Анализатор стоп-слов.
Исключение слов из стеминга
Параметр stem_exclusion позволяет указать массив слов в нижнем регистре, которые не должны подвергаться стемингу. Внутренне эта функциональность реализуется добавлением keyword_marker фильтра токенов с keywords, установленным в значение параметра stem_exclusion.
Следующие анализаторы поддерживают настройку пользовательского списка stem_exclusion: arabic, armenian, basque, bengali, bulgarian, catalan, czech, dutch, english, finnish, french, galician, german, hindi, hungarian, indonesian, irish, italian, latvian, lithuanian, norwegian, portuguese, romanian, russian, serbian, sorani, spanish, swedish, turkish.
Реализация анализаторов языка заново
Встроенные анализаторы языка могут быть переписаны как анализаторы custom (как описано ниже), чтобы настроить их поведение.
Если вы не планируете исключать слова из стемминга (эквивалент параметра stem_exclusion выше), то вам следует удалить токен-фильтр keyword_marker из конфигурации пользовательского анализатора.
arabic analyzer
Анализатор arabic может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="arabic_example",
settings={
"analysis": {
"filter": {
"arabic_stop": {
"type": "stop",
"stopwords": "_arabic_"
},
"arabic_keywords": {
"type": "keyword_marker",
"keywords": [
"مثال"
]
},
"arabic_stemmer": {
"type": "stemmer",
"language": "arabic"
}
},
"analyzer": {
"rebuilt_arabic": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"arabic_stop",
"arabic_normalization",
"arabic_keywords",
"arabic_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'arabic_example',
body: {
settings: {
analysis: {
filter: {
arabic_stop: {
type: 'stop',
stopwords: '_arabic_'
},
arabic_keywords: {
type: 'keyword_marker',
keywords: [
'مثال'
]
},
arabic_stemmer: {
type: 'stemmer',
language: 'arabic'
}
},
analyzer: {
rebuilt_arabic: {
tokenizer: 'standard',
filter: [
'lowercase',
'decimal_digit',
'arabic_stop',
'arabic_normalization',
'arabic_keywords',
'arabic_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "arabic_example",
settings: {
analysis: {
filter: {
arabic_stop: {
type: "stop",
stopwords: "_arabic_",
},
arabic_keywords: {
type: "keyword_marker",
keywords: ["مثال"],
},
arabic_stemmer: {
type: "stemmer",
language: "arabic",
},
},
analyzer: {
rebuilt_arabic: {
tokenizer: "standard",
filter: [
"lowercase",
"decimal_digit",
"arabic_stop",
"arabic_normalization",
"arabic_keywords",
"arabic_stemmer",
],
},
},
},
},
});
console.log(response); PUT /arabic_example
{
"settings": {
"analysis": {
"filter": {
"arabic_stop": {
"type": "stop",
"stopwords": "_arabic_"
},
"arabic_keywords": {
"type": "keyword_marker",
"keywords": ["مثال"]
},
"arabic_stemmer": {
"type": "stemmer",
"language": "arabic"
}
},
"analyzer": {
"rebuilt_arabic": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"arabic_stop",
"arabic_normalization",
"arabic_keywords",
"arabic_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
armenian analyzer
Анализатор armenian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="armenian_example",
settings={
"analysis": {
"filter": {
"armenian_stop": {
"type": "stop",
"stopwords": "_armenian_"
},
"armenian_keywords": {
"type": "keyword_marker",
"keywords": [
"օրինակ"
]
},
"armenian_stemmer": {
"type": "stemmer",
"language": "armenian"
}
},
"analyzer": {
"rebuilt_armenian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"armenian_stop",
"armenian_keywords",
"armenian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'armenian_example',
body: {
settings: {
analysis: {
filter: {
armenian_stop: {
type: 'stop',
stopwords: '_armenian_'
},
armenian_keywords: {
type: 'keyword_marker',
keywords: [
'օրինակ'
]
},
armenian_stemmer: {
type: 'stemmer',
language: 'armenian'
}
},
analyzer: {
rebuilt_armenian: {
tokenizer: 'standard',
filter: [
'lowercase',
'armenian_stop',
'armenian_keywords',
'armenian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "armenian_example",
settings: {
analysis: {
filter: {
armenian_stop: {
type: "stop",
stopwords: "_armenian_",
},
armenian_keywords: {
type: "keyword_marker",
keywords: ["օրինակ"],
},
armenian_stemmer: {
type: "stemmer",
language: "armenian",
},
},
analyzer: {
rebuilt_armenian: {
tokenizer: "standard",
filter: [
"lowercase",
"armenian_stop",
"armenian_keywords",
"armenian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /armenian_example
{
"settings": {
"analysis": {
"filter": {
"armenian_stop": {
"type": "stop",
"stopwords": "_armenian_"
},
"armenian_keywords": {
"type": "keyword_marker",
"keywords": ["օրինակ"]
},
"armenian_stemmer": {
"type": "stemmer",
"language": "armenian"
}
},
"analyzer": {
"rebuilt_armenian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"armenian_stop",
"armenian_keywords",
"armenian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
basque analyzer
Анализатор basque может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="basque_example",
settings={
"analysis": {
"filter": {
"basque_stop": {
"type": "stop",
"stopwords": "_basque_"
},
"basque_keywords": {
"type": "keyword_marker",
"keywords": [
"Adibidez"
]
},
"basque_stemmer": {
"type": "stemmer",
"language": "basque"
}
},
"analyzer": {
"rebuilt_basque": {
"tokenizer": "standard",
"filter": [
"lowercase",
"basque_stop",
"basque_keywords",
"basque_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'basque_example',
body: {
settings: {
analysis: {
filter: {
basque_stop: {
type: 'stop',
stopwords: '_basque_'
},
basque_keywords: {
type: 'keyword_marker',
keywords: [
'Adibidez'
]
},
basque_stemmer: {
type: 'stemmer',
language: 'basque'
}
},
analyzer: {
rebuilt_basque: {
tokenizer: 'standard',
filter: [
'lowercase',
'basque_stop',
'basque_keywords',
'basque_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "basque_example",
settings: {
analysis: {
filter: {
basque_stop: {
type: "stop",
stopwords: "_basque_",
},
basque_keywords: {
type: "keyword_marker",
keywords: ["Adibidez"],
},
basque_stemmer: {
type: "stemmer",
language: "basque",
},
},
analyzer: {
rebuilt_basque: {
tokenizer: "standard",
filter: [
"lowercase",
"basque_stop",
"basque_keywords",
"basque_stemmer",
],
},
},
},
},
});
console.log(response); PUT /basque_example
{
"settings": {
"analysis": {
"filter": {
"basque_stop": {
"type": "stop",
"stopwords": "_basque_"
},
"basque_keywords": {
"type": "keyword_marker",
"keywords": ["Adibidez"]
},
"basque_stemmer": {
"type": "stemmer",
"language": "basque"
}
},
"analyzer": {
"rebuilt_basque": {
"tokenizer": "standard",
"filter": [
"lowercase",
"basque_stop",
"basque_keywords",
"basque_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
bengali analyzer
Анализатор bengali может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="bengali_example",
settings={
"analysis": {
"filter": {
"bengali_stop": {
"type": "stop",
"stopwords": "_bengali_"
},
"bengali_keywords": {
"type": "keyword_marker",
"keywords": [
"উদাহরণ"
]
},
"bengali_stemmer": {
"type": "stemmer",
"language": "bengali"
}
},
"analyzer": {
"rebuilt_bengali": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"bengali_keywords",
"indic_normalization",
"bengali_normalization",
"bengali_stop",
"bengali_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'bengali_example',
body: {
settings: {
analysis: {
filter: {
bengali_stop: {
type: 'stop',
stopwords: '_bengali_'
},
bengali_keywords: {
type: 'keyword_marker',
keywords: [
'উদাহরণ'
]
},
bengali_stemmer: {
type: 'stemmer',
language: 'bengali'
}
},
analyzer: {
rebuilt_bengali: {
tokenizer: 'standard',
filter: [
'lowercase',
'decimal_digit',
'bengali_keywords',
'indic_normalization',
'bengali_normalization',
'bengali_stop',
'bengali_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "bengali_example",
settings: {
analysis: {
filter: {
bengali_stop: {
type: "stop",
stopwords: "_bengali_",
},
bengali_keywords: {
type: "keyword_marker",
keywords: ["উদাহরণ"],
},
bengali_stemmer: {
type: "stemmer",
language: "bengali",
},
},
analyzer: {
rebuilt_bengali: {
tokenizer: "standard",
filter: [
"lowercase",
"decimal_digit",
"bengali_keywords",
"indic_normalization",
"bengali_normalization",
"bengali_stop",
"bengali_stemmer",
],
},
},
},
},
});
console.log(response); PUT /bengali_example
{
"settings": {
"analysis": {
"filter": {
"bengali_stop": {
"type": "stop",
"stopwords": "_bengali_"
},
"bengali_keywords": {
"type": "keyword_marker",
"keywords": ["উদাহরণ"]
},
"bengali_stemmer": {
"type": "stemmer",
"language": "bengali"
}
},
"analyzer": {
"rebuilt_bengali": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"bengali_keywords",
"indic_normalization",
"bengali_normalization",
"bengali_stop",
"bengali_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
brazilian analyzer
Анализатор brazilian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="brazilian_example",
settings={
"analysis": {
"filter": {
"brazilian_stop": {
"type": "stop",
"stopwords": "_brazilian_"
},
"brazilian_keywords": {
"type": "keyword_marker",
"keywords": [
"exemplo"
]
},
"brazilian_stemmer": {
"type": "stemmer",
"language": "brazilian"
}
},
"analyzer": {
"rebuilt_brazilian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"brazilian_stop",
"brazilian_keywords",
"brazilian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'brazilian_example',
body: {
settings: {
analysis: {
filter: {
brazilian_stop: {
type: 'stop',
stopwords: '_brazilian_'
},
brazilian_keywords: {
type: 'keyword_marker',
keywords: [
'exemplo'
]
},
brazilian_stemmer: {
type: 'stemmer',
language: 'brazilian'
}
},
analyzer: {
rebuilt_brazilian: {
tokenizer: 'standard',
filter: [
'lowercase',
'brazilian_stop',
'brazilian_keywords',
'brazilian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "brazilian_example",
settings: {
analysis: {
filter: {
brazilian_stop: {
type: "stop",
stopwords: "_brazilian_",
},
brazilian_keywords: {
type: "keyword_marker",
keywords: ["exemplo"],
},
brazilian_stemmer: {
type: "stemmer",
language: "brazilian",
},
},
analyzer: {
rebuilt_brazilian: {
tokenizer: "standard",
filter: [
"lowercase",
"brazilian_stop",
"brazilian_keywords",
"brazilian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /brazilian_example
{
"settings": {
"analysis": {
"filter": {
"brazilian_stop": {
"type": "stop",
"stopwords": "_brazilian_"
},
"brazilian_keywords": {
"type": "keyword_marker",
"keywords": ["exemplo"]
},
"brazilian_stemmer": {
"type": "stemmer",
"language": "brazilian"
}
},
"analyzer": {
"rebuilt_brazilian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"brazilian_stop",
"brazilian_keywords",
"brazilian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
bulgarian analyzer
Анализатор bulgarian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="bulgarian_example",
settings={
"analysis": {
"filter": {
"bulgarian_stop": {
"type": "stop",
"stopwords": "_bulgarian_"
},
"bulgarian_keywords": {
"type": "keyword_marker",
"keywords": [
"пример"
]
},
"bulgarian_stemmer": {
"type": "stemmer",
"language": "bulgarian"
}
},
"analyzer": {
"rebuilt_bulgarian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"bulgarian_stop",
"bulgarian_keywords",
"bulgarian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'bulgarian_example',
body: {
settings: {
analysis: {
filter: {
bulgarian_stop: {
type: 'stop',
stopwords: '_bulgarian_'
},
bulgarian_keywords: {
type: 'keyword_marker',
keywords: [
'пример'
]
},
bulgarian_stemmer: {
type: 'stemmer',
language: 'bulgarian'
}
},
analyzer: {
rebuilt_bulgarian: {
tokenizer: 'standard',
filter: [
'lowercase',
'bulgarian_stop',
'bulgarian_keywords',
'bulgarian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "bulgarian_example",
settings: {
analysis: {
filter: {
bulgarian_stop: {
type: "stop",
stopwords: "_bulgarian_",
},
bulgarian_keywords: {
type: "keyword_marker",
keywords: ["пример"],
},
bulgarian_stemmer: {
type: "stemmer",
language: "bulgarian",
},
},
analyzer: {
rebuilt_bulgarian: {
tokenizer: "standard",
filter: [
"lowercase",
"bulgarian_stop",
"bulgarian_keywords",
"bulgarian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /bulgarian_example
{
"settings": {
"analysis": {
"filter": {
"bulgarian_stop": {
"type": "stop",
"stopwords": "_bulgarian_"
},
"bulgarian_keywords": {
"type": "keyword_marker",
"keywords": ["пример"]
},
"bulgarian_stemmer": {
"type": "stemmer",
"language": "bulgarian"
}
},
"analyzer": {
"rebuilt_bulgarian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"bulgarian_stop",
"bulgarian_keywords",
"bulgarian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
catalan analyzer
Анализатор catalan может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="catalan_example",
settings={
"analysis": {
"filter": {
"catalan_elision": {
"type": "elision",
"articles": [
"d",
"l",
"m",
"n",
"s",
"t"
],
"articles_case": True
},
"catalan_stop": {
"type": "stop",
"stopwords": "_catalan_"
},
"catalan_keywords": {
"type": "keyword_marker",
"keywords": [
"example"
]
},
"catalan_stemmer": {
"type": "stemmer",
"language": "catalan"
}
},
"analyzer": {
"rebuilt_catalan": {
"tokenizer": "standard",
"filter": [
"catalan_elision",
"lowercase",
"catalan_stop",
"catalan_keywords",
"catalan_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'catalan_example',
body: {
settings: {
analysis: {
filter: {
catalan_elision: {
type: 'elision',
articles: [
'd',
'l',
'm',
'n',
's',
't'
],
articles_case: true
},
catalan_stop: {
type: 'stop',
stopwords: '_catalan_'
},
catalan_keywords: {
type: 'keyword_marker',
keywords: [
'example'
]
},
catalan_stemmer: {
type: 'stemmer',
language: 'catalan'
}
},
analyzer: {
rebuilt_catalan: {
tokenizer: 'standard',
filter: [
'catalan_elision',
'lowercase',
'catalan_stop',
'catalan_keywords',
'catalan_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "catalan_example",
settings: {
analysis: {
filter: {
catalan_elision: {
type: "elision",
articles: ["d", "l", "m", "n", "s", "t"],
articles_case: true,
},
catalan_stop: {
type: "stop",
stopwords: "_catalan_",
},
catalan_keywords: {
type: "keyword_marker",
keywords: ["example"],
},
catalan_stemmer: {
type: "stemmer",
language: "catalan",
},
},
analyzer: {
rebuilt_catalan: {
tokenizer: "standard",
filter: [
"catalan_elision",
"lowercase",
"catalan_stop",
"catalan_keywords",
"catalan_stemmer",
],
},
},
},
},
});
console.log(response); PUT /catalan_example
{
"settings": {
"analysis": {
"filter": {
"catalan_elision": {
"type": "elision",
"articles": [ "d", "l", "m", "n", "s", "t"],
"articles_case": true
},
"catalan_stop": {
"type": "stop",
"stopwords": "_catalan_"
},
"catalan_keywords": {
"type": "keyword_marker",
"keywords": ["example"]
},
"catalan_stemmer": {
"type": "stemmer",
"language": "catalan"
}
},
"analyzer": {
"rebuilt_catalan": {
"tokenizer": "standard",
"filter": [
"catalan_elision",
"lowercase",
"catalan_stop",
"catalan_keywords",
"catalan_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
cjk analyzer
Вы можете обнаружить, что icu_analyzer в плагине анализа ICU работает лучше для текста CJK, чем анализатор cjk. Поэкспериментируйте с вашим текстом и запросами.
Анализатор cjk может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="cjk_example",
settings={
"analysis": {
"filter": {
"english_stop": {
"type": "stop",
"stopwords": [
"a",
"and",
"are",
"as",
"at",
"be",
"but",
"by",
"for",
"if",
"in",
"into",
"is",
"it",
"no",
"not",
"of",
"on",
"or",
"s",
"such",
"t",
"that",
"the",
"their",
"then",
"there",
"these",
"they",
"this",
"to",
"was",
"will",
"with",
"www"
]
}
},
"analyzer": {
"rebuilt_cjk": {
"tokenizer": "standard",
"filter": [
"cjk_width",
"lowercase",
"cjk_bigram",
"english_stop"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'cjk_example',
body: {
settings: {
analysis: {
filter: {
english_stop: {
type: 'stop',
stopwords: [
'a',
'and',
'are',
'as',
'at',
'be',
'but',
'by',
'for',
'if',
'in',
'into',
'is',
'it',
'no',
'not',
'of',
'on',
'or',
's',
'such',
't',
'that',
'the',
'their',
'then',
'there',
'these',
'they',
'this',
'to',
'was',
'will',
'with',
'www'
]
}
},
analyzer: {
rebuilt_cjk: {
tokenizer: 'standard',
filter: [
'cjk_width',
'lowercase',
'cjk_bigram',
'english_stop'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "cjk_example",
settings: {
analysis: {
filter: {
english_stop: {
type: "stop",
stopwords: [
"a",
"and",
"are",
"as",
"at",
"be",
"but",
"by",
"for",
"if",
"in",
"into",
"is",
"it",
"no",
"not",
"of",
"on",
"or",
"s",
"such",
"t",
"that",
"the",
"their",
"then",
"there",
"these",
"they",
"this",
"to",
"was",
"will",
"with",
"www",
],
},
},
analyzer: {
rebuilt_cjk: {
tokenizer: "standard",
filter: ["cjk_width", "lowercase", "cjk_bigram", "english_stop"],
},
},
},
},
});
console.log(response); PUT /cjk_example
{
"settings": {
"analysis": {
"filter": {
"english_stop": {
"type": "stop",
"stopwords": [
"a", "and", "are", "as", "at", "be", "but", "by", "for",
"if", "in", "into", "is", "it", "no", "not", "of", "on",
"or", "s", "such", "t", "that", "the", "their", "then",
"there", "these", "they", "this", "to", "was", "will",
"with", "www"
]
}
},
"analyzer": {
"rebuilt_cjk": {
"tokenizer": "standard",
"filter": [
"cjk_width",
"lowercase",
"cjk_bigram",
"english_stop"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров |
czech analyzer
Анализатор czech может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="czech_example",
settings={
"analysis": {
"filter": {
"czech_stop": {
"type": "stop",
"stopwords": "_czech_"
},
"czech_keywords": {
"type": "keyword_marker",
"keywords": [
"příklad"
]
},
"czech_stemmer": {
"type": "stemmer",
"language": "czech"
}
},
"analyzer": {
"rebuilt_czech": {
"tokenizer": "standard",
"filter": [
"lowercase",
"czech_stop",
"czech_keywords",
"czech_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'czech_example',
body: {
settings: {
analysis: {
filter: {
czech_stop: {
type: 'stop',
stopwords: '_czech_'
},
czech_keywords: {
type: 'keyword_marker',
keywords: [
'příklad'
]
},
czech_stemmer: {
type: 'stemmer',
language: 'czech'
}
},
analyzer: {
rebuilt_czech: {
tokenizer: 'standard',
filter: [
'lowercase',
'czech_stop',
'czech_keywords',
'czech_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "czech_example",
settings: {
analysis: {
filter: {
czech_stop: {
type: "stop",
stopwords: "_czech_",
},
czech_keywords: {
type: "keyword_marker",
keywords: ["příklad"],
},
czech_stemmer: {
type: "stemmer",
language: "czech",
},
},
analyzer: {
rebuilt_czech: {
tokenizer: "standard",
filter: [
"lowercase",
"czech_stop",
"czech_keywords",
"czech_stemmer",
],
},
},
},
},
});
console.log(response); PUT /czech_example
{
"settings": {
"analysis": {
"filter": {
"czech_stop": {
"type": "stop",
"stopwords": "_czech_"
},
"czech_keywords": {
"type": "keyword_marker",
"keywords": ["příklad"]
},
"czech_stemmer": {
"type": "stemmer",
"language": "czech"
}
},
"analyzer": {
"rebuilt_czech": {
"tokenizer": "standard",
"filter": [
"lowercase",
"czech_stop",
"czech_keywords",
"czech_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр должен быть удален, если нет слов, которые следует исключить из стемминга. |
danish analyzer
Анализатор danish может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="danish_example",
settings={
"analysis": {
"filter": {
"danish_stop": {
"type": "stop",
"stopwords": "_danish_"
},
"danish_keywords": {
"type": "keyword_marker",
"keywords": [
"eksempel"
]
},
"danish_stemmer": {
"type": "stemmer",
"language": "danish"
}
},
"analyzer": {
"rebuilt_danish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"danish_stop",
"danish_keywords",
"danish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'danish_example',
body: {
settings: {
analysis: {
filter: {
danish_stop: {
type: 'stop',
stopwords: '_danish_'
},
danish_keywords: {
type: 'keyword_marker',
keywords: [
'eksempel'
]
},
danish_stemmer: {
type: 'stemmer',
language: 'danish'
}
},
analyzer: {
rebuilt_danish: {
tokenizer: 'standard',
filter: [
'lowercase',
'danish_stop',
'danish_keywords',
'danish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "danish_example",
settings: {
analysis: {
filter: {
danish_stop: {
type: "stop",
stopwords: "_danish_",
},
danish_keywords: {
type: "keyword_marker",
keywords: ["eksempel"],
},
danish_stemmer: {
type: "stemmer",
language: "danish",
},
},
analyzer: {
rebuilt_danish: {
tokenizer: "standard",
filter: [
"lowercase",
"danish_stop",
"danish_keywords",
"danish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /danish_example
{
"settings": {
"analysis": {
"filter": {
"danish_stop": {
"type": "stop",
"stopwords": "_danish_"
},
"danish_keywords": {
"type": "keyword_marker",
"keywords": ["eksempel"]
},
"danish_stemmer": {
"type": "stemmer",
"language": "danish"
}
},
"analyzer": {
"rebuilt_danish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"danish_stop",
"danish_keywords",
"danish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
dutch analyzer
Анализатор dutch может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="dutch_example",
settings={
"analysis": {
"filter": {
"dutch_stop": {
"type": "stop",
"stopwords": "_dutch_"
},
"dutch_keywords": {
"type": "keyword_marker",
"keywords": [
"voorbeeld"
]
},
"dutch_stemmer": {
"type": "stemmer",
"language": "dutch"
},
"dutch_override": {
"type": "stemmer_override",
"rules": [
"fiets=>fiets",
"bromfiets=>bromfiets",
"ei=>eier",
"kind=>kinder"
]
}
},
"analyzer": {
"rebuilt_dutch": {
"tokenizer": "standard",
"filter": [
"lowercase",
"dutch_stop",
"dutch_keywords",
"dutch_override",
"dutch_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'dutch_example',
body: {
settings: {
analysis: {
filter: {
dutch_stop: {
type: 'stop',
stopwords: '_dutch_'
},
dutch_keywords: {
type: 'keyword_marker',
keywords: [
'voorbeeld'
]
},
dutch_stemmer: {
type: 'stemmer',
language: 'dutch'
},
dutch_override: {
type: 'stemmer_override',
rules: [
'fiets=>fiets',
'bromfiets=>bromfiets',
'ei=>eier',
'kind=>kinder'
]
}
},
analyzer: {
rebuilt_dutch: {
tokenizer: 'standard',
filter: [
'lowercase',
'dutch_stop',
'dutch_keywords',
'dutch_override',
'dutch_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "dutch_example",
settings: {
analysis: {
filter: {
dutch_stop: {
type: "stop",
stopwords: "_dutch_",
},
dutch_keywords: {
type: "keyword_marker",
keywords: ["voorbeeld"],
},
dutch_stemmer: {
type: "stemmer",
language: "dutch",
},
dutch_override: {
type: "stemmer_override",
rules: [
"fiets=>fiets",
"bromfiets=>bromfiets",
"ei=>eier",
"kind=>kinder",
],
},
},
analyzer: {
rebuilt_dutch: {
tokenizer: "standard",
filter: [
"lowercase",
"dutch_stop",
"dutch_keywords",
"dutch_override",
"dutch_stemmer",
],
},
},
},
},
});
console.log(response); PUT /dutch_example
{
"settings": {
"analysis": {
"filter": {
"dutch_stop": {
"type": "stop",
"stopwords": "_dutch_"
},
"dutch_keywords": {
"type": "keyword_marker",
"keywords": ["voorbeeld"]
},
"dutch_stemmer": {
"type": "stemmer",
"language": "dutch"
},
"dutch_override": {
"type": "stemmer_override",
"rules": [
"fiets=>fiets",
"bromfiets=>bromfiets",
"ei=>eier",
"kind=>kinder"
]
}
},
"analyzer": {
"rebuilt_dutch": {
"tokenizer": "standard",
"filter": [
"lowercase",
"dutch_stop",
"dutch_keywords",
"dutch_override",
"dutch_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
english analyzer
Анализатор english может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="english_example",
settings={
"analysis": {
"filter": {
"english_stop": {
"type": "stop",
"stopwords": "_english_"
},
"english_keywords": {
"type": "keyword_marker",
"keywords": [
"example"
]
},
"english_stemmer": {
"type": "stemmer",
"language": "english"
},
"english_possessive_stemmer": {
"type": "stemmer",
"language": "possessive_english"
}
},
"analyzer": {
"rebuilt_english": {
"tokenizer": "standard",
"filter": [
"english_possessive_stemmer",
"lowercase",
"english_stop",
"english_keywords",
"english_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'english_example',
body: {
settings: {
analysis: {
filter: {
english_stop: {
type: 'stop',
stopwords: '_english_'
},
english_keywords: {
type: 'keyword_marker',
keywords: [
'example'
]
},
english_stemmer: {
type: 'stemmer',
language: 'english'
},
english_possessive_stemmer: {
type: 'stemmer',
language: 'possessive_english'
}
},
analyzer: {
rebuilt_english: {
tokenizer: 'standard',
filter: [
'english_possessive_stemmer',
'lowercase',
'english_stop',
'english_keywords',
'english_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "english_example",
settings: {
analysis: {
filter: {
english_stop: {
type: "stop",
stopwords: "_english_",
},
english_keywords: {
type: "keyword_marker",
keywords: ["example"],
},
english_stemmer: {
type: "stemmer",
language: "english",
},
english_possessive_stemmer: {
type: "stemmer",
language: "possessive_english",
},
},
analyzer: {
rebuilt_english: {
tokenizer: "standard",
filter: [
"english_possessive_stemmer",
"lowercase",
"english_stop",
"english_keywords",
"english_stemmer",
],
},
},
},
},
});
console.log(response); PUT /english_example
{
"settings": {
"analysis": {
"filter": {
"english_stop": {
"type": "stop",
"stopwords": "_english_"
},
"english_keywords": {
"type": "keyword_marker",
"keywords": ["example"]
},
"english_stemmer": {
"type": "stemmer",
"language": "english"
},
"english_possessive_stemmer": {
"type": "stemmer",
"language": "possessive_english"
}
},
"analyzer": {
"rebuilt_english": {
"tokenizer": "standard",
"filter": [
"english_possessive_stemmer",
"lowercase",
"english_stop",
"english_keywords",
"english_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
estonian analyzer
Анализатор estonian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="estonian_example",
settings={
"analysis": {
"filter": {
"estonian_stop": {
"type": "stop",
"stopwords": "_estonian_"
},
"estonian_keywords": {
"type": "keyword_marker",
"keywords": [
"näide"
]
},
"estonian_stemmer": {
"type": "stemmer",
"language": "estonian"
}
},
"analyzer": {
"rebuilt_estonian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"estonian_stop",
"estonian_keywords",
"estonian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'estonian_example',
body: {
settings: {
analysis: {
filter: {
estonian_stop: {
type: 'stop',
stopwords: '_estonian_'
},
estonian_keywords: {
type: 'keyword_marker',
keywords: [
'näide'
]
},
estonian_stemmer: {
type: 'stemmer',
language: 'estonian'
}
},
analyzer: {
rebuilt_estonian: {
tokenizer: 'standard',
filter: [
'lowercase',
'estonian_stop',
'estonian_keywords',
'estonian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "estonian_example",
settings: {
analysis: {
filter: {
estonian_stop: {
type: "stop",
stopwords: "_estonian_",
},
estonian_keywords: {
type: "keyword_marker",
keywords: ["näide"],
},
estonian_stemmer: {
type: "stemmer",
language: "estonian",
},
},
analyzer: {
rebuilt_estonian: {
tokenizer: "standard",
filter: [
"lowercase",
"estonian_stop",
"estonian_keywords",
"estonian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /estonian_example
{
"settings": {
"analysis": {
"filter": {
"estonian_stop": {
"type": "stop",
"stopwords": "_estonian_"
},
"estonian_keywords": {
"type": "keyword_marker",
"keywords": ["näide"]
},
"estonian_stemmer": {
"type": "stemmer",
"language": "estonian"
}
},
"analyzer": {
"rebuilt_estonian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"estonian_stop",
"estonian_keywords",
"estonian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
finnish analyzer
Анализатор finnish может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="finnish_example",
settings={
"analysis": {
"filter": {
"finnish_stop": {
"type": "stop",
"stopwords": "_finnish_"
},
"finnish_keywords": {
"type": "keyword_marker",
"keywords": [
"esimerkki"
]
},
"finnish_stemmer": {
"type": "stemmer",
"language": "finnish"
}
},
"analyzer": {
"rebuilt_finnish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"finnish_stop",
"finnish_keywords",
"finnish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'finnish_example',
body: {
settings: {
analysis: {
filter: {
finnish_stop: {
type: 'stop',
stopwords: '_finnish_'
},
finnish_keywords: {
type: 'keyword_marker',
keywords: [
'esimerkki'
]
},
finnish_stemmer: {
type: 'stemmer',
language: 'finnish'
}
},
analyzer: {
rebuilt_finnish: {
tokenizer: 'standard',
filter: [
'lowercase',
'finnish_stop',
'finnish_keywords',
'finnish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "finnish_example",
settings: {
analysis: {
filter: {
finnish_stop: {
type: "stop",
stopwords: "_finnish_",
},
finnish_keywords: {
type: "keyword_marker",
keywords: ["esimerkki"],
},
finnish_stemmer: {
type: "stemmer",
language: "finnish",
},
},
analyzer: {
rebuilt_finnish: {
tokenizer: "standard",
filter: [
"lowercase",
"finnish_stop",
"finnish_keywords",
"finnish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /finnish_example
{
"settings": {
"analysis": {
"filter": {
"finnish_stop": {
"type": "stop",
"stopwords": "_finnish_"
},
"finnish_keywords": {
"type": "keyword_marker",
"keywords": ["esimerkki"]
},
"finnish_stemmer": {
"type": "stemmer",
"language": "finnish"
}
},
"analyzer": {
"rebuilt_finnish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"finnish_stop",
"finnish_keywords",
"finnish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
french analyzer
Анализатор french может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="french_example",
settings={
"analysis": {
"filter": {
"french_elision": {
"type": "elision",
"articles_case": True,
"articles": [
"l",
"m",
"t",
"qu",
"n",
"s",
"j",
"d",
"c",
"jusqu",
"quoiqu",
"lorsqu",
"puisqu"
]
},
"french_stop": {
"type": "stop",
"stopwords": "_french_"
},
"french_keywords": {
"type": "keyword_marker",
"keywords": [
"Example"
]
},
"french_stemmer": {
"type": "stemmer",
"language": "light_french"
}
},
"analyzer": {
"rebuilt_french": {
"tokenizer": "standard",
"filter": [
"french_elision",
"lowercase",
"french_stop",
"french_keywords",
"french_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'french_example',
body: {
settings: {
analysis: {
filter: {
french_elision: {
type: 'elision',
articles_case: true,
articles: [
'l',
'm',
't',
'qu',
'n',
's',
'j',
'd',
'c',
'jusqu',
'quoiqu',
'lorsqu',
'puisqu'
]
},
french_stop: {
type: 'stop',
stopwords: '_french_'
},
french_keywords: {
type: 'keyword_marker',
keywords: [
'Example'
]
},
french_stemmer: {
type: 'stemmer',
language: 'light_french'
}
},
analyzer: {
rebuilt_french: {
tokenizer: 'standard',
filter: [
'french_elision',
'lowercase',
'french_stop',
'french_keywords',
'french_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "french_example",
settings: {
analysis: {
filter: {
french_elision: {
type: "elision",
articles_case: true,
articles: [
"l",
"m",
"t",
"qu",
"n",
"s",
"j",
"d",
"c",
"jusqu",
"quoiqu",
"lorsqu",
"puisqu",
],
},
french_stop: {
type: "stop",
stopwords: "_french_",
},
french_keywords: {
type: "keyword_marker",
keywords: ["Example"],
},
french_stemmer: {
type: "stemmer",
language: "light_french",
},
},
analyzer: {
rebuilt_french: {
tokenizer: "standard",
filter: [
"french_elision",
"lowercase",
"french_stop",
"french_keywords",
"french_stemmer",
],
},
},
},
},
});
console.log(response); PUT /french_example
{
"settings": {
"analysis": {
"filter": {
"french_elision": {
"type": "elision",
"articles_case": true,
"articles": [
"l", "m", "t", "qu", "n", "s",
"j", "d", "c", "jusqu", "quoiqu",
"lorsqu", "puisqu"
]
},
"french_stop": {
"type": "stop",
"stopwords": "_french_"
},
"french_keywords": {
"type": "keyword_marker",
"keywords": ["Example"]
},
"french_stemmer": {
"type": "stemmer",
"language": "light_french"
}
},
"analyzer": {
"rebuilt_french": {
"tokenizer": "standard",
"filter": [
"french_elision",
"lowercase",
"french_stop",
"french_keywords",
"french_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
galician analyzer
Анализатор galician может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="galician_example",
settings={
"analysis": {
"filter": {
"galician_stop": {
"type": "stop",
"stopwords": "_galician_"
},
"galician_keywords": {
"type": "keyword_marker",
"keywords": [
"exemplo"
]
},
"galician_stemmer": {
"type": "stemmer",
"language": "galician"
}
},
"analyzer": {
"rebuilt_galician": {
"tokenizer": "standard",
"filter": [
"lowercase",
"galician_stop",
"galician_keywords",
"galician_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'galician_example',
body: {
settings: {
analysis: {
filter: {
galician_stop: {
type: 'stop',
stopwords: '_galician_'
},
galician_keywords: {
type: 'keyword_marker',
keywords: [
'exemplo'
]
},
galician_stemmer: {
type: 'stemmer',
language: 'galician'
}
},
analyzer: {
rebuilt_galician: {
tokenizer: 'standard',
filter: [
'lowercase',
'galician_stop',
'galician_keywords',
'galician_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "galician_example",
settings: {
analysis: {
filter: {
galician_stop: {
type: "stop",
stopwords: "_galician_",
},
galician_keywords: {
type: "keyword_marker",
keywords: ["exemplo"],
},
galician_stemmer: {
type: "stemmer",
language: "galician",
},
},
analyzer: {
rebuilt_galician: {
tokenizer: "standard",
filter: [
"lowercase",
"galician_stop",
"galician_keywords",
"galician_stemmer",
],
},
},
},
},
});
console.log(response); PUT /galician_example
{
"settings": {
"analysis": {
"filter": {
"galician_stop": {
"type": "stop",
"stopwords": "_galician_"
},
"galician_keywords": {
"type": "keyword_marker",
"keywords": ["exemplo"]
},
"galician_stemmer": {
"type": "stemmer",
"language": "galician"
}
},
"analyzer": {
"rebuilt_galician": {
"tokenizer": "standard",
"filter": [
"lowercase",
"galician_stop",
"galician_keywords",
"galician_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
german analyzer
Анализатор german может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="german_example",
settings={
"analysis": {
"filter": {
"german_stop": {
"type": "stop",
"stopwords": "_german_"
},
"german_keywords": {
"type": "keyword_marker",
"keywords": [
"Beispiel"
]
},
"german_stemmer": {
"type": "stemmer",
"language": "light_german"
}
},
"analyzer": {
"rebuilt_german": {
"tokenizer": "standard",
"filter": [
"lowercase",
"german_stop",
"german_keywords",
"german_normalization",
"german_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'german_example',
body: {
settings: {
analysis: {
filter: {
german_stop: {
type: 'stop',
stopwords: '_german_'
},
german_keywords: {
type: 'keyword_marker',
keywords: [
'Beispiel'
]
},
german_stemmer: {
type: 'stemmer',
language: 'light_german'
}
},
analyzer: {
rebuilt_german: {
tokenizer: 'standard',
filter: [
'lowercase',
'german_stop',
'german_keywords',
'german_normalization',
'german_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "german_example",
settings: {
analysis: {
filter: {
german_stop: {
type: "stop",
stopwords: "_german_",
},
german_keywords: {
type: "keyword_marker",
keywords: ["Beispiel"],
},
german_stemmer: {
type: "stemmer",
language: "light_german",
},
},
analyzer: {
rebuilt_german: {
tokenizer: "standard",
filter: [
"lowercase",
"german_stop",
"german_keywords",
"german_normalization",
"german_stemmer",
],
},
},
},
},
});
console.log(response); PUT /german_example
{
"settings": {
"analysis": {
"filter": {
"german_stop": {
"type": "stop",
"stopwords": "_german_"
},
"german_keywords": {
"type": "keyword_marker",
"keywords": ["Beispiel"]
},
"german_stemmer": {
"type": "stemmer",
"language": "light_german"
}
},
"analyzer": {
"rebuilt_german": {
"tokenizer": "standard",
"filter": [
"lowercase",
"german_stop",
"german_keywords",
"german_normalization",
"german_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
greek analyzer
Анализатор greek может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="greek_example",
settings={
"analysis": {
"filter": {
"greek_stop": {
"type": "stop",
"stopwords": "_greek_"
},
"greek_lowercase": {
"type": "lowercase",
"language": "greek"
},
"greek_keywords": {
"type": "keyword_marker",
"keywords": [
"παράδειγμα"
]
},
"greek_stemmer": {
"type": "stemmer",
"language": "greek"
}
},
"analyzer": {
"rebuilt_greek": {
"tokenizer": "standard",
"filter": [
"greek_lowercase",
"greek_stop",
"greek_keywords",
"greek_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'greek_example',
body: {
settings: {
analysis: {
filter: {
greek_stop: {
type: 'stop',
stopwords: '_greek_'
},
greek_lowercase: {
type: 'lowercase',
language: 'greek'
},
greek_keywords: {
type: 'keyword_marker',
keywords: [
'παράδειγμα'
]
},
greek_stemmer: {
type: 'stemmer',
language: 'greek'
}
},
analyzer: {
rebuilt_greek: {
tokenizer: 'standard',
filter: [
'greek_lowercase',
'greek_stop',
'greek_keywords',
'greek_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "greek_example",
settings: {
analysis: {
filter: {
greek_stop: {
type: "stop",
stopwords: "_greek_",
},
greek_lowercase: {
type: "lowercase",
language: "greek",
},
greek_keywords: {
type: "keyword_marker",
keywords: ["παράδειγμα"],
},
greek_stemmer: {
type: "stemmer",
language: "greek",
},
},
analyzer: {
rebuilt_greek: {
tokenizer: "standard",
filter: [
"greek_lowercase",
"greek_stop",
"greek_keywords",
"greek_stemmer",
],
},
},
},
},
});
console.log(response); PUT /greek_example
{
"settings": {
"analysis": {
"filter": {
"greek_stop": {
"type": "stop",
"stopwords": "_greek_"
},
"greek_lowercase": {
"type": "lowercase",
"language": "greek"
},
"greek_keywords": {
"type": "keyword_marker",
"keywords": ["παράδειγμα"]
},
"greek_stemmer": {
"type": "stemmer",
"language": "greek"
}
},
"analyzer": {
"rebuilt_greek": {
"tokenizer": "standard",
"filter": [
"greek_lowercase",
"greek_stop",
"greek_keywords",
"greek_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если только нет слов, которые должны быть исключены из стемминга. |
hindi analyzer
hindi анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="hindi_example",
settings={
"analysis": {
"filter": {
"hindi_stop": {
"type": "stop",
"stopwords": "_hindi_"
},
"hindi_keywords": {
"type": "keyword_marker",
"keywords": [
"उदाहरण"
]
},
"hindi_stemmer": {
"type": "stemmer",
"language": "hindi"
}
},
"analyzer": {
"rebuilt_hindi": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"hindi_keywords",
"indic_normalization",
"hindi_normalization",
"hindi_stop",
"hindi_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'hindi_example',
body: {
settings: {
analysis: {
filter: {
hindi_stop: {
type: 'stop',
stopwords: '_hindi_'
},
hindi_keywords: {
type: 'keyword_marker',
keywords: [
'उदाहरण'
]
},
hindi_stemmer: {
type: 'stemmer',
language: 'hindi'
}
},
analyzer: {
rebuilt_hindi: {
tokenizer: 'standard',
filter: [
'lowercase',
'decimal_digit',
'hindi_keywords',
'indic_normalization',
'hindi_normalization',
'hindi_stop',
'hindi_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "hindi_example",
settings: {
analysis: {
filter: {
hindi_stop: {
type: "stop",
stopwords: "_hindi_",
},
hindi_keywords: {
type: "keyword_marker",
keywords: ["उदाहरण"],
},
hindi_stemmer: {
type: "stemmer",
language: "hindi",
},
},
analyzer: {
rebuilt_hindi: {
tokenizer: "standard",
filter: [
"lowercase",
"decimal_digit",
"hindi_keywords",
"indic_normalization",
"hindi_normalization",
"hindi_stop",
"hindi_stemmer",
],
},
},
},
},
});
console.log(response); PUT /hindi_example
{
"settings": {
"analysis": {
"filter": {
"hindi_stop": {
"type": "stop",
"stopwords": "_hindi_"
},
"hindi_keywords": {
"type": "keyword_marker",
"keywords": ["उदाहरण"]
},
"hindi_stemmer": {
"type": "stemmer",
"language": "hindi"
}
},
"analyzer": {
"rebuilt_hindi": {
"tokenizer": "standard",
"filter": [
"lowercase",
"decimal_digit",
"hindi_keywords",
"indic_normalization",
"hindi_normalization",
"hindi_stop",
"hindi_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
hungarian analyzer
hungarian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="hungarian_example",
settings={
"analysis": {
"filter": {
"hungarian_stop": {
"type": "stop",
"stopwords": "_hungarian_"
},
"hungarian_keywords": {
"type": "keyword_marker",
"keywords": [
"példa"
]
},
"hungarian_stemmer": {
"type": "stemmer",
"language": "hungarian"
}
},
"analyzer": {
"rebuilt_hungarian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"hungarian_stop",
"hungarian_keywords",
"hungarian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'hungarian_example',
body: {
settings: {
analysis: {
filter: {
hungarian_stop: {
type: 'stop',
stopwords: '_hungarian_'
},
hungarian_keywords: {
type: 'keyword_marker',
keywords: [
'példa'
]
},
hungarian_stemmer: {
type: 'stemmer',
language: 'hungarian'
}
},
analyzer: {
rebuilt_hungarian: {
tokenizer: 'standard',
filter: [
'lowercase',
'hungarian_stop',
'hungarian_keywords',
'hungarian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "hungarian_example",
settings: {
analysis: {
filter: {
hungarian_stop: {
type: "stop",
stopwords: "_hungarian_",
},
hungarian_keywords: {
type: "keyword_marker",
keywords: ["példa"],
},
hungarian_stemmer: {
type: "stemmer",
language: "hungarian",
},
},
analyzer: {
rebuilt_hungarian: {
tokenizer: "standard",
filter: [
"lowercase",
"hungarian_stop",
"hungarian_keywords",
"hungarian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /hungarian_example
{
"settings": {
"analysis": {
"filter": {
"hungarian_stop": {
"type": "stop",
"stopwords": "_hungarian_"
},
"hungarian_keywords": {
"type": "keyword_marker",
"keywords": ["példa"]
},
"hungarian_stemmer": {
"type": "stemmer",
"language": "hungarian"
}
},
"analyzer": {
"rebuilt_hungarian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"hungarian_stop",
"hungarian_keywords",
"hungarian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
indonesian analyzer
indonesian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="indonesian_example",
settings={
"analysis": {
"filter": {
"indonesian_stop": {
"type": "stop",
"stopwords": "_indonesian_"
},
"indonesian_keywords": {
"type": "keyword_marker",
"keywords": [
"contoh"
]
},
"indonesian_stemmer": {
"type": "stemmer",
"language": "indonesian"
}
},
"analyzer": {
"rebuilt_indonesian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"indonesian_stop",
"indonesian_keywords",
"indonesian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'indonesian_example',
body: {
settings: {
analysis: {
filter: {
indonesian_stop: {
type: 'stop',
stopwords: '_indonesian_'
},
indonesian_keywords: {
type: 'keyword_marker',
keywords: [
'contoh'
]
},
indonesian_stemmer: {
type: 'stemmer',
language: 'indonesian'
}
},
analyzer: {
rebuilt_indonesian: {
tokenizer: 'standard',
filter: [
'lowercase',
'indonesian_stop',
'indonesian_keywords',
'indonesian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "indonesian_example",
settings: {
analysis: {
filter: {
indonesian_stop: {
type: "stop",
stopwords: "_indonesian_",
},
indonesian_keywords: {
type: "keyword_marker",
keywords: ["contoh"],
},
indonesian_stemmer: {
type: "stemmer",
language: "indonesian",
},
},
analyzer: {
rebuilt_indonesian: {
tokenizer: "standard",
filter: [
"lowercase",
"indonesian_stop",
"indonesian_keywords",
"indonesian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /indonesian_example
{
"settings": {
"analysis": {
"filter": {
"indonesian_stop": {
"type": "stop",
"stopwords": "_indonesian_"
},
"indonesian_keywords": {
"type": "keyword_marker",
"keywords": ["contoh"]
},
"indonesian_stemmer": {
"type": "stemmer",
"language": "indonesian"
}
},
"analyzer": {
"rebuilt_indonesian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"indonesian_stop",
"indonesian_keywords",
"indonesian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
irish analyzer
irish анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="irish_example",
settings={
"analysis": {
"filter": {
"irish_hyphenation": {
"type": "stop",
"stopwords": [
"h",
"n",
"t"
],
"ignore_case": True
},
"irish_elision": {
"type": "elision",
"articles": [
"d",
"m",
"b"
],
"articles_case": True
},
"irish_stop": {
"type": "stop",
"stopwords": "_irish_"
},
"irish_lowercase": {
"type": "lowercase",
"language": "irish"
},
"irish_keywords": {
"type": "keyword_marker",
"keywords": [
"sampla"
]
},
"irish_stemmer": {
"type": "stemmer",
"language": "irish"
}
},
"analyzer": {
"rebuilt_irish": {
"tokenizer": "standard",
"filter": [
"irish_hyphenation",
"irish_elision",
"irish_lowercase",
"irish_stop",
"irish_keywords",
"irish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'irish_example',
body: {
settings: {
analysis: {
filter: {
irish_hyphenation: {
type: 'stop',
stopwords: [
'h',
'n',
't'
],
ignore_case: true
},
irish_elision: {
type: 'elision',
articles: [
'd',
'm',
'b'
],
articles_case: true
},
irish_stop: {
type: 'stop',
stopwords: '_irish_'
},
irish_lowercase: {
type: 'lowercase',
language: 'irish'
},
irish_keywords: {
type: 'keyword_marker',
keywords: [
'sampla'
]
},
irish_stemmer: {
type: 'stemmer',
language: 'irish'
}
},
analyzer: {
rebuilt_irish: {
tokenizer: 'standard',
filter: [
'irish_hyphenation',
'irish_elision',
'irish_lowercase',
'irish_stop',
'irish_keywords',
'irish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "irish_example",
settings: {
analysis: {
filter: {
irish_hyphenation: {
type: "stop",
stopwords: ["h", "n", "t"],
ignore_case: true,
},
irish_elision: {
type: "elision",
articles: ["d", "m", "b"],
articles_case: true,
},
irish_stop: {
type: "stop",
stopwords: "_irish_",
},
irish_lowercase: {
type: "lowercase",
language: "irish",
},
irish_keywords: {
type: "keyword_marker",
keywords: ["sampla"],
},
irish_stemmer: {
type: "stemmer",
language: "irish",
},
},
analyzer: {
rebuilt_irish: {
tokenizer: "standard",
filter: [
"irish_hyphenation",
"irish_elision",
"irish_lowercase",
"irish_stop",
"irish_keywords",
"irish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /irish_example
{
"settings": {
"analysis": {
"filter": {
"irish_hyphenation": {
"type": "stop",
"stopwords": [ "h", "n", "t" ],
"ignore_case": true
},
"irish_elision": {
"type": "elision",
"articles": [ "d", "m", "b" ],
"articles_case": true
},
"irish_stop": {
"type": "stop",
"stopwords": "_irish_"
},
"irish_lowercase": {
"type": "lowercase",
"language": "irish"
},
"irish_keywords": {
"type": "keyword_marker",
"keywords": ["sampla"]
},
"irish_stemmer": {
"type": "stemmer",
"language": "irish"
}
},
"analyzer": {
"rebuilt_irish": {
"tokenizer": "standard",
"filter": [
"irish_hyphenation",
"irish_elision",
"irish_lowercase",
"irish_stop",
"irish_keywords",
"irish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
italian analyzer
italian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="italian_example",
settings={
"analysis": {
"filter": {
"italian_elision": {
"type": "elision",
"articles": [
"c",
"l",
"all",
"dall",
"dell",
"nell",
"sull",
"coll",
"pell",
"gl",
"agl",
"dagl",
"degl",
"negl",
"sugl",
"un",
"m",
"t",
"s",
"v",
"d"
],
"articles_case": True
},
"italian_stop": {
"type": "stop",
"stopwords": "_italian_"
},
"italian_keywords": {
"type": "keyword_marker",
"keywords": [
"esempio"
]
},
"italian_stemmer": {
"type": "stemmer",
"language": "light_italian"
}
},
"analyzer": {
"rebuilt_italian": {
"tokenizer": "standard",
"filter": [
"italian_elision",
"lowercase",
"italian_stop",
"italian_keywords",
"italian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'italian_example',
body: {
settings: {
analysis: {
filter: {
italian_elision: {
type: 'elision',
articles: [
'c',
'l',
'all',
'dall',
'dell',
'nell',
'sull',
'coll',
'pell',
'gl',
'agl',
'dagl',
'degl',
'negl',
'sugl',
'un',
'm',
't',
's',
'v',
'd'
],
articles_case: true
},
italian_stop: {
type: 'stop',
stopwords: '_italian_'
},
italian_keywords: {
type: 'keyword_marker',
keywords: [
'esempio'
]
},
italian_stemmer: {
type: 'stemmer',
language: 'light_italian'
}
},
analyzer: {
rebuilt_italian: {
tokenizer: 'standard',
filter: [
'italian_elision',
'lowercase',
'italian_stop',
'italian_keywords',
'italian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "italian_example",
settings: {
analysis: {
filter: {
italian_elision: {
type: "elision",
articles: [
"c",
"l",
"all",
"dall",
"dell",
"nell",
"sull",
"coll",
"pell",
"gl",
"agl",
"dagl",
"degl",
"negl",
"sugl",
"un",
"m",
"t",
"s",
"v",
"d",
],
articles_case: true,
},
italian_stop: {
type: "stop",
stopwords: "_italian_",
},
italian_keywords: {
type: "keyword_marker",
keywords: ["esempio"],
},
italian_stemmer: {
type: "stemmer",
language: "light_italian",
},
},
analyzer: {
rebuilt_italian: {
tokenizer: "standard",
filter: [
"italian_elision",
"lowercase",
"italian_stop",
"italian_keywords",
"italian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /italian_example
{
"settings": {
"analysis": {
"filter": {
"italian_elision": {
"type": "elision",
"articles": [
"c", "l", "all", "dall", "dell",
"nell", "sull", "coll", "pell",
"gl", "agl", "dagl", "degl", "negl",
"sugl", "un", "m", "t", "s", "v", "d"
],
"articles_case": true
},
"italian_stop": {
"type": "stop",
"stopwords": "_italian_"
},
"italian_keywords": {
"type": "keyword_marker",
"keywords": ["esempio"]
},
"italian_stemmer": {
"type": "stemmer",
"language": "light_italian"
}
},
"analyzer": {
"rebuilt_italian": {
"tokenizer": "standard",
"filter": [
"italian_elision",
"lowercase",
"italian_stop",
"italian_keywords",
"italian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
latvian analyzer
latvian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="latvian_example",
settings={
"analysis": {
"filter": {
"latvian_stop": {
"type": "stop",
"stopwords": "_latvian_"
},
"latvian_keywords": {
"type": "keyword_marker",
"keywords": [
"piemērs"
]
},
"latvian_stemmer": {
"type": "stemmer",
"language": "latvian"
}
},
"analyzer": {
"rebuilt_latvian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"latvian_stop",
"latvian_keywords",
"latvian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'latvian_example',
body: {
settings: {
analysis: {
filter: {
latvian_stop: {
type: 'stop',
stopwords: '_latvian_'
},
latvian_keywords: {
type: 'keyword_marker',
keywords: [
'piemērs'
]
},
latvian_stemmer: {
type: 'stemmer',
language: 'latvian'
}
},
analyzer: {
rebuilt_latvian: {
tokenizer: 'standard',
filter: [
'lowercase',
'latvian_stop',
'latvian_keywords',
'latvian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "latvian_example",
settings: {
analysis: {
filter: {
latvian_stop: {
type: "stop",
stopwords: "_latvian_",
},
latvian_keywords: {
type: "keyword_marker",
keywords: ["piemērs"],
},
latvian_stemmer: {
type: "stemmer",
language: "latvian",
},
},
analyzer: {
rebuilt_latvian: {
tokenizer: "standard",
filter: [
"lowercase",
"latvian_stop",
"latvian_keywords",
"latvian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /latvian_example
{
"settings": {
"analysis": {
"filter": {
"latvian_stop": {
"type": "stop",
"stopwords": "_latvian_"
},
"latvian_keywords": {
"type": "keyword_marker",
"keywords": ["piemērs"]
},
"latvian_stemmer": {
"type": "stemmer",
"language": "latvian"
}
},
"analyzer": {
"rebuilt_latvian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"latvian_stop",
"latvian_keywords",
"latvian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
lithuanian analyzer
lithuanian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="lithuanian_example",
settings={
"analysis": {
"filter": {
"lithuanian_stop": {
"type": "stop",
"stopwords": "_lithuanian_"
},
"lithuanian_keywords": {
"type": "keyword_marker",
"keywords": [
"pavyzdys"
]
},
"lithuanian_stemmer": {
"type": "stemmer",
"language": "lithuanian"
}
},
"analyzer": {
"rebuilt_lithuanian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"lithuanian_stop",
"lithuanian_keywords",
"lithuanian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'lithuanian_example',
body: {
settings: {
analysis: {
filter: {
lithuanian_stop: {
type: 'stop',
stopwords: '_lithuanian_'
},
lithuanian_keywords: {
type: 'keyword_marker',
keywords: [
'pavyzdys'
]
},
lithuanian_stemmer: {
type: 'stemmer',
language: 'lithuanian'
}
},
analyzer: {
rebuilt_lithuanian: {
tokenizer: 'standard',
filter: [
'lowercase',
'lithuanian_stop',
'lithuanian_keywords',
'lithuanian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "lithuanian_example",
settings: {
analysis: {
filter: {
lithuanian_stop: {
type: "stop",
stopwords: "_lithuanian_",
},
lithuanian_keywords: {
type: "keyword_marker",
keywords: ["pavyzdys"],
},
lithuanian_stemmer: {
type: "stemmer",
language: "lithuanian",
},
},
analyzer: {
rebuilt_lithuanian: {
tokenizer: "standard",
filter: [
"lowercase",
"lithuanian_stop",
"lithuanian_keywords",
"lithuanian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /lithuanian_example
{
"settings": {
"analysis": {
"filter": {
"lithuanian_stop": {
"type": "stop",
"stopwords": "_lithuanian_"
},
"lithuanian_keywords": {
"type": "keyword_marker",
"keywords": ["pavyzdys"]
},
"lithuanian_stemmer": {
"type": "stemmer",
"language": "lithuanian"
}
},
"analyzer": {
"rebuilt_lithuanian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"lithuanian_stop",
"lithuanian_keywords",
"lithuanian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
norwegian analyzer
norwegian анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="norwegian_example",
settings={
"analysis": {
"filter": {
"norwegian_stop": {
"type": "stop",
"stopwords": "_norwegian_"
},
"norwegian_keywords": {
"type": "keyword_marker",
"keywords": [
"eksempel"
]
},
"norwegian_stemmer": {
"type": "stemmer",
"language": "norwegian"
}
},
"analyzer": {
"rebuilt_norwegian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"norwegian_stop",
"norwegian_keywords",
"norwegian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'norwegian_example',
body: {
settings: {
analysis: {
filter: {
norwegian_stop: {
type: 'stop',
stopwords: '_norwegian_'
},
norwegian_keywords: {
type: 'keyword_marker',
keywords: [
'eksempel'
]
},
norwegian_stemmer: {
type: 'stemmer',
language: 'norwegian'
}
},
analyzer: {
rebuilt_norwegian: {
tokenizer: 'standard',
filter: [
'lowercase',
'norwegian_stop',
'norwegian_keywords',
'norwegian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "norwegian_example",
settings: {
analysis: {
filter: {
norwegian_stop: {
type: "stop",
stopwords: "_norwegian_",
},
norwegian_keywords: {
type: "keyword_marker",
keywords: ["eksempel"],
},
norwegian_stemmer: {
type: "stemmer",
language: "norwegian",
},
},
analyzer: {
rebuilt_norwegian: {
tokenizer: "standard",
filter: [
"lowercase",
"norwegian_stop",
"norwegian_keywords",
"norwegian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /norwegian_example
{
"settings": {
"analysis": {
"filter": {
"norwegian_stop": {
"type": "stop",
"stopwords": "_norwegian_"
},
"norwegian_keywords": {
"type": "keyword_marker",
"keywords": ["eksempel"]
},
"norwegian_stemmer": {
"type": "stemmer",
"language": "norwegian"
}
},
"analyzer": {
"rebuilt_norwegian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"norwegian_stop",
"norwegian_keywords",
"norwegian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
persian analyzer
persian анализатор может быть переписан как custom анализатор следующим образом:
response = client.indices.create(
index: 'persian_example',
body: {
settings: {
analysis: {
char_filter: {
zero_width_spaces: {
type: 'mapping',
mappings: [
'\\u200C=>\\u0020'
]
}
},
filter: {
persian_stop: {
type: 'stop',
stopwords: '_persian_'
}
},
analyzer: {
rebuilt_persian: {
tokenizer: 'standard',
char_filter: [
'zero_width_spaces'
],
filter: [
'lowercase',
'decimal_digit',
'arabic_normalization',
'persian_normalization',
'persian_stop'
]
}
}
}
}
}
)
puts response PUT /persian_example
{
"settings": {
"analysis": {
"char_filter": {
"zero_width_spaces": {
"type": "mapping",
"mappings": [ "\\u200C=>\\u0020"]
}
},
"filter": {
"persian_stop": {
"type": "stop",
"stopwords": "_persian_"
}
},
"analyzer": {
"rebuilt_persian": {
"tokenizer": "standard",
"char_filter": [ "zero_width_spaces" ],
"filter": [
"lowercase",
"decimal_digit",
"arabic_normalization",
"persian_normalization",
"persian_stop"
]
}
}
}
}
} | Заменяет неразрывные знаки нулевой ширины на пробел ASCII. | |
| Стоп-слова по умолчанию можно переопределить с помощью параметров |
portuguese analyzer
portuguese анализатор может быть переписан как custom анализатор следующим образом:
resp = client.indices.create(
index="portuguese_example",
settings={
"analysis": {
"filter": {
"portuguese_stop": {
"type": "stop",
"stopwords": "_portuguese_"
},
"portuguese_keywords": {
"type": "keyword_marker",
"keywords": [
"exemplo"
]
},
"portuguese_stemmer": {
"type": "stemmer",
"language": "light_portuguese"
}
},
"analyzer": {
"rebuilt_portuguese": {
"tokenizer": "standard",
"filter": [
"lowercase",
"portuguese_stop",
"portuguese_keywords",
"portuguese_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'portuguese_example',
body: {
settings: {
analysis: {
filter: {
portuguese_stop: {
type: 'stop',
stopwords: '_portuguese_'
},
portuguese_keywords: {
type: 'keyword_marker',
keywords: [
'exemplo'
]
},
portuguese_stemmer: {
type: 'stemmer',
language: 'light_portuguese'
}
},
analyzer: {
rebuilt_portuguese: {
tokenizer: 'standard',
filter: [
'lowercase',
'portuguese_stop',
'portuguese_keywords',
'portuguese_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "portuguese_example",
settings: {
analysis: {
filter: {
portuguese_stop: {
type: "stop",
stopwords: "_portuguese_",
},
portuguese_keywords: {
type: "keyword_marker",
keywords: ["exemplo"],
},
portuguese_stemmer: {
type: "stemmer",
language: "light_portuguese",
},
},
analyzer: {
rebuilt_portuguese: {
tokenizer: "standard",
filter: [
"lowercase",
"portuguese_stop",
"portuguese_keywords",
"portuguese_stemmer",
],
},
},
},
},
});
console.log(response); PUT /portuguese_example
{
"settings": {
"analysis": {
"filter": {
"portuguese_stop": {
"type": "stop",
"stopwords": "_portuguese_"
},
"portuguese_keywords": {
"type": "keyword_marker",
"keywords": ["exemplo"]
},
"portuguese_stemmer": {
"type": "stemmer",
"language": "light_portuguese"
}
},
"analyzer": {
"rebuilt_portuguese": {
"tokenizer": "standard",
"filter": [
"lowercase",
"portuguese_stop",
"portuguese_keywords",
"portuguese_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию можно переопределить с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые следует исключить из стемминга. |
romanian analyzer
Анализатор romanian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="romanian_example",
settings={
"analysis": {
"filter": {
"romanian_stop": {
"type": "stop",
"stopwords": "_romanian_"
},
"romanian_keywords": {
"type": "keyword_marker",
"keywords": [
"exemplu"
]
},
"romanian_stemmer": {
"type": "stemmer",
"language": "romanian"
}
},
"analyzer": {
"rebuilt_romanian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"romanian_stop",
"romanian_keywords",
"romanian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'romanian_example',
body: {
settings: {
analysis: {
filter: {
romanian_stop: {
type: 'stop',
stopwords: '_romanian_'
},
romanian_keywords: {
type: 'keyword_marker',
keywords: [
'exemplu'
]
},
romanian_stemmer: {
type: 'stemmer',
language: 'romanian'
}
},
analyzer: {
rebuilt_romanian: {
tokenizer: 'standard',
filter: [
'lowercase',
'romanian_stop',
'romanian_keywords',
'romanian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "romanian_example",
settings: {
analysis: {
filter: {
romanian_stop: {
type: "stop",
stopwords: "_romanian_",
},
romanian_keywords: {
type: "keyword_marker",
keywords: ["exemplu"],
},
romanian_stemmer: {
type: "stemmer",
language: "romanian",
},
},
analyzer: {
rebuilt_romanian: {
tokenizer: "standard",
filter: [
"lowercase",
"romanian_stop",
"romanian_keywords",
"romanian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /romanian_example
{
"settings": {
"analysis": {
"filter": {
"romanian_stop": {
"type": "stop",
"stopwords": "_romanian_"
},
"romanian_keywords": {
"type": "keyword_marker",
"keywords": ["exemplu"]
},
"romanian_stemmer": {
"type": "stemmer",
"language": "romanian"
}
},
"analyzer": {
"rebuilt_romanian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"romanian_stop",
"romanian_keywords",
"romanian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
russian analyzer
Анализатор russian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="russian_example",
settings={
"analysis": {
"filter": {
"russian_stop": {
"type": "stop",
"stopwords": "_russian_"
},
"russian_keywords": {
"type": "keyword_marker",
"keywords": [
"пример"
]
},
"russian_stemmer": {
"type": "stemmer",
"language": "russian"
}
},
"analyzer": {
"rebuilt_russian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"russian_stop",
"russian_keywords",
"russian_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'russian_example',
body: {
settings: {
analysis: {
filter: {
russian_stop: {
type: 'stop',
stopwords: '_russian_'
},
russian_keywords: {
type: 'keyword_marker',
keywords: [
'пример'
]
},
russian_stemmer: {
type: 'stemmer',
language: 'russian'
}
},
analyzer: {
rebuilt_russian: {
tokenizer: 'standard',
filter: [
'lowercase',
'russian_stop',
'russian_keywords',
'russian_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "russian_example",
settings: {
analysis: {
filter: {
russian_stop: {
type: "stop",
stopwords: "_russian_",
},
russian_keywords: {
type: "keyword_marker",
keywords: ["пример"],
},
russian_stemmer: {
type: "stemmer",
language: "russian",
},
},
analyzer: {
rebuilt_russian: {
tokenizer: "standard",
filter: [
"lowercase",
"russian_stop",
"russian_keywords",
"russian_stemmer",
],
},
},
},
},
});
console.log(response); PUT /russian_example
{
"settings": {
"analysis": {
"filter": {
"russian_stop": {
"type": "stop",
"stopwords": "_russian_"
},
"russian_keywords": {
"type": "keyword_marker",
"keywords": ["пример"]
},
"russian_stemmer": {
"type": "stemmer",
"language": "russian"
}
},
"analyzer": {
"rebuilt_russian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"russian_stop",
"russian_keywords",
"russian_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
serbian analyzer
Анализатор serbian может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="serbian_example",
settings={
"analysis": {
"filter": {
"serbian_stop": {
"type": "stop",
"stopwords": "_serbian_"
},
"serbian_keywords": {
"type": "keyword_marker",
"keywords": [
"пример"
]
},
"serbian_stemmer": {
"type": "stemmer",
"language": "serbian"
}
},
"analyzer": {
"rebuilt_serbian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"serbian_stop",
"serbian_keywords",
"serbian_stemmer",
"serbian_normalization"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'serbian_example',
body: {
settings: {
analysis: {
filter: {
serbian_stop: {
type: 'stop',
stopwords: '_serbian_'
},
serbian_keywords: {
type: 'keyword_marker',
keywords: [
'пример'
]
},
serbian_stemmer: {
type: 'stemmer',
language: 'serbian'
}
},
analyzer: {
rebuilt_serbian: {
tokenizer: 'standard',
filter: [
'lowercase',
'serbian_stop',
'serbian_keywords',
'serbian_stemmer',
'serbian_normalization'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "serbian_example",
settings: {
analysis: {
filter: {
serbian_stop: {
type: "stop",
stopwords: "_serbian_",
},
serbian_keywords: {
type: "keyword_marker",
keywords: ["пример"],
},
serbian_stemmer: {
type: "stemmer",
language: "serbian",
},
},
analyzer: {
rebuilt_serbian: {
tokenizer: "standard",
filter: [
"lowercase",
"serbian_stop",
"serbian_keywords",
"serbian_stemmer",
"serbian_normalization",
],
},
},
},
},
});
console.log(response); PUT /serbian_example
{
"settings": {
"analysis": {
"filter": {
"serbian_stop": {
"type": "stop",
"stopwords": "_serbian_"
},
"serbian_keywords": {
"type": "keyword_marker",
"keywords": ["пример"]
},
"serbian_stemmer": {
"type": "stemmer",
"language": "serbian"
}
},
"analyzer": {
"rebuilt_serbian": {
"tokenizer": "standard",
"filter": [
"lowercase",
"serbian_stop",
"serbian_keywords",
"serbian_stemmer",
"serbian_normalization"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
sorani analyzer
Анализатор sorani может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="sorani_example",
settings={
"analysis": {
"filter": {
"sorani_stop": {
"type": "stop",
"stopwords": "_sorani_"
},
"sorani_keywords": {
"type": "keyword_marker",
"keywords": [
"mînak"
]
},
"sorani_stemmer": {
"type": "stemmer",
"language": "sorani"
}
},
"analyzer": {
"rebuilt_sorani": {
"tokenizer": "standard",
"filter": [
"sorani_normalization",
"lowercase",
"decimal_digit",
"sorani_stop",
"sorani_keywords",
"sorani_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'sorani_example',
body: {
settings: {
analysis: {
filter: {
sorani_stop: {
type: 'stop',
stopwords: '_sorani_'
},
sorani_keywords: {
type: 'keyword_marker',
keywords: [
'mînak'
]
},
sorani_stemmer: {
type: 'stemmer',
language: 'sorani'
}
},
analyzer: {
rebuilt_sorani: {
tokenizer: 'standard',
filter: [
'sorani_normalization',
'lowercase',
'decimal_digit',
'sorani_stop',
'sorani_keywords',
'sorani_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "sorani_example",
settings: {
analysis: {
filter: {
sorani_stop: {
type: "stop",
stopwords: "_sorani_",
},
sorani_keywords: {
type: "keyword_marker",
keywords: ["mînak"],
},
sorani_stemmer: {
type: "stemmer",
language: "sorani",
},
},
analyzer: {
rebuilt_sorani: {
tokenizer: "standard",
filter: [
"sorani_normalization",
"lowercase",
"decimal_digit",
"sorani_stop",
"sorani_keywords",
"sorani_stemmer",
],
},
},
},
},
});
console.log(response); PUT /sorani_example
{
"settings": {
"analysis": {
"filter": {
"sorani_stop": {
"type": "stop",
"stopwords": "_sorani_"
},
"sorani_keywords": {
"type": "keyword_marker",
"keywords": ["mînak"]
},
"sorani_stemmer": {
"type": "stemmer",
"language": "sorani"
}
},
"analyzer": {
"rebuilt_sorani": {
"tokenizer": "standard",
"filter": [
"sorani_normalization",
"lowercase",
"decimal_digit",
"sorani_stop",
"sorani_keywords",
"sorani_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
spanish analyzer
Анализатор spanish может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="spanish_example",
settings={
"analysis": {
"filter": {
"spanish_stop": {
"type": "stop",
"stopwords": "_spanish_"
},
"spanish_keywords": {
"type": "keyword_marker",
"keywords": [
"ejemplo"
]
},
"spanish_stemmer": {
"type": "stemmer",
"language": "light_spanish"
}
},
"analyzer": {
"rebuilt_spanish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"spanish_stop",
"spanish_keywords",
"spanish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'spanish_example',
body: {
settings: {
analysis: {
filter: {
spanish_stop: {
type: 'stop',
stopwords: '_spanish_'
},
spanish_keywords: {
type: 'keyword_marker',
keywords: [
'ejemplo'
]
},
spanish_stemmer: {
type: 'stemmer',
language: 'light_spanish'
}
},
analyzer: {
rebuilt_spanish: {
tokenizer: 'standard',
filter: [
'lowercase',
'spanish_stop',
'spanish_keywords',
'spanish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "spanish_example",
settings: {
analysis: {
filter: {
spanish_stop: {
type: "stop",
stopwords: "_spanish_",
},
spanish_keywords: {
type: "keyword_marker",
keywords: ["ejemplo"],
},
spanish_stemmer: {
type: "stemmer",
language: "light_spanish",
},
},
analyzer: {
rebuilt_spanish: {
tokenizer: "standard",
filter: [
"lowercase",
"spanish_stop",
"spanish_keywords",
"spanish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /spanish_example
{
"settings": {
"analysis": {
"filter": {
"spanish_stop": {
"type": "stop",
"stopwords": "_spanish_"
},
"spanish_keywords": {
"type": "keyword_marker",
"keywords": ["ejemplo"]
},
"spanish_stemmer": {
"type": "stemmer",
"language": "light_spanish"
}
},
"analyzer": {
"rebuilt_spanish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"spanish_stop",
"spanish_keywords",
"spanish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
swedish analyzer
Анализатор swedish может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="swedish_example",
settings={
"analysis": {
"filter": {
"swedish_stop": {
"type": "stop",
"stopwords": "_swedish_"
},
"swedish_keywords": {
"type": "keyword_marker",
"keywords": [
"exempel"
]
},
"swedish_stemmer": {
"type": "stemmer",
"language": "swedish"
}
},
"analyzer": {
"rebuilt_swedish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"swedish_stop",
"swedish_keywords",
"swedish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'swedish_example',
body: {
settings: {
analysis: {
filter: {
swedish_stop: {
type: 'stop',
stopwords: '_swedish_'
},
swedish_keywords: {
type: 'keyword_marker',
keywords: [
'exempel'
]
},
swedish_stemmer: {
type: 'stemmer',
language: 'swedish'
}
},
analyzer: {
rebuilt_swedish: {
tokenizer: 'standard',
filter: [
'lowercase',
'swedish_stop',
'swedish_keywords',
'swedish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "swedish_example",
settings: {
analysis: {
filter: {
swedish_stop: {
type: "stop",
stopwords: "_swedish_",
},
swedish_keywords: {
type: "keyword_marker",
keywords: ["exempel"],
},
swedish_stemmer: {
type: "stemmer",
language: "swedish",
},
},
analyzer: {
rebuilt_swedish: {
tokenizer: "standard",
filter: [
"lowercase",
"swedish_stop",
"swedish_keywords",
"swedish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /swedish_example
{
"settings": {
"analysis": {
"filter": {
"swedish_stop": {
"type": "stop",
"stopwords": "_swedish_"
},
"swedish_keywords": {
"type": "keyword_marker",
"keywords": ["exempel"]
},
"swedish_stemmer": {
"type": "stemmer",
"language": "swedish"
}
},
"analyzer": {
"rebuilt_swedish": {
"tokenizer": "standard",
"filter": [
"lowercase",
"swedish_stop",
"swedish_keywords",
"swedish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
turkish analyzer
Анализатор turkish может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="turkish_example",
settings={
"analysis": {
"filter": {
"turkish_stop": {
"type": "stop",
"stopwords": "_turkish_"
},
"turkish_lowercase": {
"type": "lowercase",
"language": "turkish"
},
"turkish_keywords": {
"type": "keyword_marker",
"keywords": [
"örnek"
]
},
"turkish_stemmer": {
"type": "stemmer",
"language": "turkish"
}
},
"analyzer": {
"rebuilt_turkish": {
"tokenizer": "standard",
"filter": [
"apostrophe",
"turkish_lowercase",
"turkish_stop",
"turkish_keywords",
"turkish_stemmer"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'turkish_example',
body: {
settings: {
analysis: {
filter: {
turkish_stop: {
type: 'stop',
stopwords: '_turkish_'
},
turkish_lowercase: {
type: 'lowercase',
language: 'turkish'
},
turkish_keywords: {
type: 'keyword_marker',
keywords: [
'örnek'
]
},
turkish_stemmer: {
type: 'stemmer',
language: 'turkish'
}
},
analyzer: {
rebuilt_turkish: {
tokenizer: 'standard',
filter: [
'apostrophe',
'turkish_lowercase',
'turkish_stop',
'turkish_keywords',
'turkish_stemmer'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "turkish_example",
settings: {
analysis: {
filter: {
turkish_stop: {
type: "stop",
stopwords: "_turkish_",
},
turkish_lowercase: {
type: "lowercase",
language: "turkish",
},
turkish_keywords: {
type: "keyword_marker",
keywords: ["örnek"],
},
turkish_stemmer: {
type: "stemmer",
language: "turkish",
},
},
analyzer: {
rebuilt_turkish: {
tokenizer: "standard",
filter: [
"apostrophe",
"turkish_lowercase",
"turkish_stop",
"turkish_keywords",
"turkish_stemmer",
],
},
},
},
},
});
console.log(response); PUT /turkish_example
{
"settings": {
"analysis": {
"filter": {
"turkish_stop": {
"type": "stop",
"stopwords": "_turkish_"
},
"turkish_lowercase": {
"type": "lowercase",
"language": "turkish"
},
"turkish_keywords": {
"type": "keyword_marker",
"keywords": ["örnek"]
},
"turkish_stemmer": {
"type": "stemmer",
"language": "turkish"
}
},
"analyzer": {
"rebuilt_turkish": {
"tokenizer": "standard",
"filter": [
"apostrophe",
"turkish_lowercase",
"turkish_stop",
"turkish_keywords",
"turkish_stemmer"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров | |
| Этот фильтр следует удалить, если нет слов, которые должны быть исключены из стемминга. |
thai analyzer
Анализатор thai может быть переписан как анализатор custom следующим образом:
resp = client.indices.create(
index="thai_example",
settings={
"analysis": {
"filter": {
"thai_stop": {
"type": "stop",
"stopwords": "_thai_"
}
},
"analyzer": {
"rebuilt_thai": {
"tokenizer": "thai",
"filter": [
"lowercase",
"decimal_digit",
"thai_stop"
]
}
}
}
},
)
print(resp) response = client.indices.create(
index: 'thai_example',
body: {
settings: {
analysis: {
filter: {
thai_stop: {
type: 'stop',
stopwords: '_thai_'
}
},
analyzer: {
rebuilt_thai: {
tokenizer: 'thai',
filter: [
'lowercase',
'decimal_digit',
'thai_stop'
]
}
}
}
}
}
)
puts response const response = await client.indices.create({
index: "thai_example",
settings: {
analysis: {
filter: {
thai_stop: {
type: "stop",
stopwords: "_thai_",
},
},
analyzer: {
rebuilt_thai: {
tokenizer: "thai",
filter: ["lowercase", "decimal_digit", "thai_stop"],
},
},
},
},
});
console.log(response); PUT /thai_example
{
"settings": {
"analysis": {
"filter": {
"thai_stop": {
"type": "stop",
"stopwords": "_thai_"
}
},
"analyzer": {
"rebuilt_thai": {
"tokenizer": "thai",
"filter": [
"lowercase",
"decimal_digit",
"thai_stop"
]
}
}
}
}
} | Стоп-слова по умолчанию могут быть переопределены с помощью параметров |
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https://www.elastic.co/guide/en/elasticsearch/reference/8.17/analysis-lang-analyzer.html
