search
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.

The above is the detailed content of How can I achieve efficient fuzzy matching for email addresses and phone numbers within Elasticsearch?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How does MySQL handle data replication?How does MySQL handle data replication?Apr 28, 2025 am 12:25 AM

MySQL processes data replication through three modes: asynchronous, semi-synchronous and group replication. 1) Asynchronous replication performance is high but data may be lost. 2) Semi-synchronous replication improves data security but increases latency. 3) Group replication supports multi-master replication and failover, suitable for high availability requirements.

How can you use the EXPLAIN statement to analyze query performance?How can you use the EXPLAIN statement to analyze query performance?Apr 28, 2025 am 12:24 AM

The EXPLAIN statement can be used to analyze and improve SQL query performance. 1. Execute the EXPLAIN statement to view the query plan. 2. Analyze the output results, pay attention to access type, index usage and JOIN order. 3. Create or adjust indexes based on the analysis results, optimize JOIN operations, and avoid full table scanning to improve query efficiency.

How do you back up and restore a MySQL database?How do you back up and restore a MySQL database?Apr 28, 2025 am 12:23 AM

Using mysqldump for logical backup and MySQLEnterpriseBackup for hot backup are effective ways to back up MySQL databases. 1. Use mysqldump to back up the database: mysqldump-uroot-pmydatabase>mydatabase_backup.sql. 2. Use MySQLEnterpriseBackup for hot backup: mysqlbackup--user=root-password=password--backup-dir=/path/to/backupbackup. When recovering, use the corresponding life

What are some common causes of slow queries in MySQL?What are some common causes of slow queries in MySQL?Apr 28, 2025 am 12:18 AM

The main reasons for slow MySQL query include missing or improper use of indexes, query complexity, excessive data volume and insufficient hardware resources. Optimization suggestions include: 1. Create appropriate indexes; 2. Optimize query statements; 3. Use table partitioning technology; 4. Appropriately upgrade hardware.

What are views in MySQL?What are views in MySQL?Apr 28, 2025 am 12:04 AM

MySQL view is a virtual table based on SQL query results and does not store data. 1) Views simplify complex queries, 2) Enhance data security, and 3) Maintain data consistency. Views are stored queries in databases that can be used like tables, but data is generated dynamically.

What are the differences in syntax between MySQL and other SQL dialects?What are the differences in syntax between MySQL and other SQL dialects?Apr 27, 2025 am 12:26 AM

MySQLdiffersfromotherSQLdialectsinsyntaxforLIMIT,auto-increment,stringcomparison,subqueries,andperformanceanalysis.1)MySQLusesLIMIT,whileSQLServerusesTOPandOracleusesROWNUM.2)MySQL'sAUTO_INCREMENTcontrastswithPostgreSQL'sSERIALandOracle'ssequenceandt

What is MySQL partitioning?What is MySQL partitioning?Apr 27, 2025 am 12:23 AM

MySQL partitioning improves performance and simplifies maintenance. 1) Divide large tables into small pieces by specific criteria (such as date ranges), 2) physically divide data into independent files, 3) MySQL can focus on related partitions when querying, 4) Query optimizer can skip unrelated partitions, 5) Choosing the right partition strategy and maintaining it regularly is key.

How do you grant and revoke privileges in MySQL?How do you grant and revoke privileges in MySQL?Apr 27, 2025 am 12:21 AM

How to grant and revoke permissions in MySQL? 1. Use the GRANT statement to grant permissions, such as GRANTALLPRIVILEGESONdatabase_name.TO'username'@'host'; 2. Use the REVOKE statement to revoke permissions, such as REVOKEALLPRIVILEGESONdatabase_name.FROM'username'@'host' to ensure timely communication of permission changes.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

mPDF

mPDF

mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Atom editor mac version download

Atom editor mac version download

The most popular open source editor