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HomeDatabaseMysql TutorialHow can I achieve efficient fuzzy matching for email addresses and phone numbers within Elasticsearch?

How can I achieve efficient fuzzy matching for email addresses and phone numbers within Elasticsearch?

Elasticsearch Fuzzy Email or Telephone Matching

Question:

How can fuzzy matching be implemented for email addresses or telephone numbers using Elasticsearch? Specifically, how can one match all emails ending with "@gmail.com" or all telephone numbers starting with "136"?

Answer:

Utilizing custom analyzers for indexing and searching can facilitate fuzzy matching for email and telephone data.

Email Fuzzy Matching:

Configure an analyzer with the following settings:

  • Index analyzer: index_email_analyzer

    • Standard tokenizer
    • Lowercase and name-ngram filters
    • Max gram: 20
  • Search analyzer: search_email_analyzer

    • Standard tokenizer
    • Lowercase filter

Telephone Number Fuzzy Matching:

Configure an analyzer with the following settings:

  • Index analyzer: index_phone_analyzer

    • Digit-only filter
    • Edge-ngram tokenizer (3-15 grams)
    • Min gram: 1
    • Max gram: 15
  • Search analyzer: search_phone_analyzer

    • Digit-only filter
    • Keyword tokenizer

Index Example:

PUT myindex
{
  "settings": {
    "analysis": {
      "analyzer": {
        "email_url_analyzer": {
          "type": "custom",
          "tokenizer": "uax_url_email",
          "filter": [ "trim" ]
        },
        "index_phone_analyzer": {
          "type": "custom",
          "char_filter": [ "digit_only" ],
          "tokenizer": "digit_edge_ngram_tokenizer",
          "filter": [ "trim" ]
        },
        "search_phone_analyzer": {
          "type": "custom",
          "char_filter": [ "digit_only" ],
          "tokenizer": "keyword",
          "filter": [ "trim" ]
        },
        "index_email_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [ "lowercase", "name_ngram_filter", "trim" ]
        },
        "search_email_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [ "lowercase", "trim" ]
        }
      },
      "char_filter": {
        "digit_only": {
          "type": "pattern_replace",
          "pattern": "\D+",
          "replacement": ""
        }
      },
      "tokenizer": {
        "digit_edge_ngram_tokenizer": {
          "type": "edgeNGram",
          "min_gram": "1",
          "max_gram": "15",
          "token_chars": [ "digit" ]
        }
      },
      "filter": {
        "name_ngram_filter": {
          "type": "ngram",
          "min_gram": "1",
          "max_gram": "20"
        }
      }
    }
  },
  "mappings": {
    "your_type": {
      "properties": {
        "email": {
          "type": "string",
          "analyzer": "index_email_analyzer",
          "search_analyzer": "search_email_analyzer"
        },
        "phone": {
          "type": "string",
          "analyzer": "index_phone_analyzer",
          "search_analyzer": "search_phone_analyzer"
        }
      }
    }
  }
}

Search Queries:

  • Match all emails ending with "@gmail.com":
POST myindex
{ 
    "query": {
        "term": 
            { "email": "@gmail.com" }
    }
}
  • Match all telephone numbers starting with "136":
POST myindex
{ 
    "query": {
        "term": 
            { "phone": "136" }
    }
}

By utilizing these custom analyzers, Elasticsearch can perform fuzzy matching for email addresses and telephone numbers efficiently.

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