Elasticsearch Analyzer - elasticsearch - elasticsearch tutorial - elastic search



Elasticsearch Analyzer

  • Analysis is the process of converting text, like the body of any email, into tokens or terms which are added to the inverted index for searching.
  • learn elasticsearch tutorials - elasticsearch-compiler-intepretation analyzer

    learn elasticsearch tutorials - elasticsearch-compiler-intepretation analyzer Example

  • Analysis is performed by an analyzer which can be either a built-in analyzer or a custom analyzer defined per index.
 index and query processing

Request Body:

{
   "settings": {
      "analysis": {
         "analyzer": {
            "index_analyzer": {
               "tokenizer": "standard", "filter": [
                  "standard", "my_delimiter", "lowercase", "stop", 
                     "asciifolding", "porter_stem"
               ]
            },
				
            "search_analyzer": {
               "tokenizer": "standard", "filter": [
                  "standard", "lowercase", "stop", "asciifolding", "porter_stem"
               ]
            }
         },
			
         "filter": {
            "my_delimiter": {
               "type": "word_delimiter",
               "generate_word_parts": true,
               "catenate_words": true,
               "catenate_numbers": true,
               "catenate_all": true,
               "split_on_case_change": true,
               "preserve_original": true,
               "split_on_numerics": true,
               "stem_english_possessive": true
            }
         }
      }
   }
}
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Analyzers:

  • An analyzer consists of a tokenizer and optional token filters.
  • These analyzers are registered in analysis module with logical names, which can be referenced either in mapping definitions or in some APIs.
  • There are a number of default analyzers as follows
Sr.No Analyzer & Description
1

Standard analyzer (standard)

stopwords and max_token_length setting can be set for this analyzer. By default, stopwords list is empty and max_token_length is 255.

2

Simple analyzer (simple)

This analyzer is composed of lowercase tokenizer.

3

Whitespace analyzer (whitespace)

This analyzer is composed of whitespace tokenizer.

4

Stop analyzer (stop)

stopwords and stopwords_path can be configured. By default stopwords initialized to English stop words and stopwords_path contains path to a text file with stop words.

5

Keyword analyzer (keyword)

This analyzer tokenizes an entire stream as a single token. It can be used for zip code.

6

Pattern analyzer (pattern)

This analyzer mainly deals with regular expressions. Settings like lowercase, pattern, flags, stopwords can be set in this analyzer.

7

Language analyzer

This analyzer deals with languages like hindi, arabic, ducth etc.

8

Snowball analyzer (snowball)

This analyzer uses the standard tokenizer, with standard filter, lowercase filter, stop filter, and snowball filter.

9

Custom analyzer (custom)

This analyzer is used to create customized analyzer with a tokenizer with optional token filters and char filters. Settings like tokenizer, filter, char_filter and position_increment_gap can be configured in this analyzer.

Tokenizers:

  • Tokenizers are used for generating tokens from a text in Elastic search.
  • Text can be broken down into tokens by taking whitespace or other punctuations into account.
  • learn elasticsearch tutorials - elasticsearch tokenizer analysis

    learn elasticsearch tutorials - elasticsearch tokenizer analysisExample

  • Elastic search has plenty of built-in tokenizers, which can be used in custom analyzer.
Sr.No Tokenizer & Description
1

Standard tokenizer (standard)

This is built on grammar based tokenizer and max_token_length can be configured for this tokenizer.

2

Edge NGram tokenizer (edgeNGram)

Settings like min_gram, max_gram, token_chars can be set for this tokenizer.

3

Keyword tokenizer (keyword)

This generates entire input as an output and buffer_size can be set for this.

4

Letter tokenizer (letter)

This captures the whole word until a non-letter is encountered.

5

Lowercase tokenizer (lowercase)

This works the same as the letter tokenizer, but after creating tokens, it changes them to lower case.

6

NGram Tokenizer (nGram)

Settings like min_gram (default value is 1), max_gram (default value is 2) and token_chars can be set for this tokenizer.

7

Whitespace tokenizer (whitespace)

This divides text on the basis of whitespaces.

8

Pattern tokenizer (pattern)

This uses regular expressions as a token separator. Pattern, flags and group settings can be set for this tokenizer.

9

UAX Email URL Tokenizer (uax_url_email)

This works same lie standard tokenizer but it treats email and URL as single token.

10

Path hierarchy tokenizer (path_hierarchy)

This tokenizer generated all the possible paths present in the input directory path. Settings available for this tokenizer are delimiter (defaults to /), replacement, buffer_size (defaults to 1024), reverse (defaults to false) and skip (defaults to 0).

11

Classic tokenizer (classic)

This works on the basis of grammar based tokens. max_token_length can be set for this tokenizer.

12

Thai tokenizer (thai)

This tokenizer is used for Thai language and uses built-in Thai segmentation algorithm.

Token Filters:

  • Token filters receive input from tokenizers and then these filters can modify, delete or add text in that input.
  • Elasticsearch offers plenty of built-in token filters. Most of them have already been explained in previous sections.

Character Filters:

  • These filters process the text before tokenizers.
  • Character filters look for special characters or html tags or specified pattern and then either delete then or change them to appropriate words like ‘&’ to and, delete html markup tags.
  • Here is an example of analyzer with synonym specified in synonym.txt
{
   "settings":{
      "index":{
         "analysis":{
            "analyzer":{
               "synonym":{
                  "tokenizer":"whitespace", "filter":["synonym"]
               }
            },
				
            "filter":{
               "synonym":{
                  "type":"synonym", "synonyms_path":"synonym.txt", "ignore_case":"true"
               }
            }
         }
      }
   }
}
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