- MariaDB - Useful Functions
- MariaDB - Backup Loading Methods
- MariaDB - Backup Methods
- MariaDB - SQL Injection Protection
- MariaDB - Managing Duplicates
- MariaDB - Sequences
- MariaDB - Table Cloning
- MariaDB - Temporary Tables
- Indexes & Statistics Tables
- MariaDB - Alter Command
- MariaDB - Transactions
- MariaDB - Regular Expression
- MariaDB - Null Values
- MariaDB - Join
- MariaDB - Order By Clause
- MariaDB - Like Clause
- MariaDB - Delete Query
- MariaDB - Update Query
- MariaDB - Where Clause
- MariaDB - Select Query
- MariaDB - Insert Query
- MariaDB - Drop Tables
- MariaDB - Create Tables
- MariaDB - Data Types
- MariaDB - Select Database
- MariaDB - Drop Database
- MariaDB - Create Database
- MariaDB - Connection
- MariaDB - PHP Syntax
- MariaDB - Administration
- MariaDB - Installation
- MariaDB - Introduction
- MariaDB - Home
MariaDB Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
MariaDB - Like Clause
The WHERE clause provides a way to retrieve data when an operation uses an exact match. In situations requiring multiple results with shared characteristics, the LIKE clause accommodates broad pattern matching.
A LIKE clause tests for a pattern match, returning a true or false. The patterns used for comparison accept the following wildcard characters: “%”, which matches numbers of characters (0 or more); and “_”, which matches a single character. The “_” wildcard character only matches characters within its set, meaning it will ignore latin characters when using another set. The matches are case-insensitive by default requiring additional settings for case sensitivity.
A NOT LIKE clause allows for testing the opposite condition, much pke the not operator.
If the statement expression or pattern evaluate to NULL, the result is NULL.
Review the general LIKE clause syntax given below −
SELECT field, field2,... FROM table_name, table_name2,... WHERE field LIKE condition
Employ a LIKE clause either at the command prompt or within a PHP script.
The Command Prompt
At the command prompt, simply use a standard command −
root@host# mysql -u root -p password; Enter password:******* mysql> use TUTORIALS; Database changed mysql> SELECT * from products_tbl WHERE product_manufacturer LIKE XYZ% ; +-------------+----------------+----------------------+ | ID_number | Nomenclature | product_manufacturer | +-------------+----------------+----------------------+ | 12345 | Orbitron 4000 | XYZ Corp | +-------------+----------------+----------------------+ | 12346 | Orbitron 3000 | XYZ Corp | +-------------+----------------+----------------------+ | 12347 | Orbitron 1000 | XYZ Corp | +-------------+----------------+----------------------+
PHP Script Using Like Clause
Use the mysql_query() function in statements employing the LIKE clause
<?php $dbhost = localhost:3036 ; $dbuser = root ; $dbpass = rootpassword ; $conn = mysql_connect($dbhost, $dbuser, $dbpass); if(! $conn ) { die( Could not connect: . mysql_error()); } $sql = SELECT product_id, product_name, product_manufacturer, ship_date FROM products_tbl WHERE product_manufacturer LIKE "xyz%" ; mysql_select_db( PRODUCTS ); $retval = mysql_query( $sql, $conn ); if(! $retval ) { die( Could not get data: . mysql_error()); } while($row = mysql_fetch_array($retval, MYSQL_ASSOC)) { echo "Product ID:{$row[ product_id ]} <br> ". "Name: {$row[ product_name ]} <br> ". "Manufacturer: {$row[ product_manufacturer ]} <br> ". "Ship Date: {$row[ ship_date ]} <br> ". "--------------------------------<br>"; } echo "Fetched data successfully "; mysql_close($conn); ?>
On successful data retrieval, you will see the following output −
Product ID: 12345 Nomenclature: Orbitron 4000 Manufacturer: XYZ Corp Ship Date: 01/01/17 ---------------------------------------------- Product ID: 12346 Nomenclature: Orbitron 3000 Manufacturer: XYZ Corp Ship Date: 01/02/17 ---------------------------------------------- Product ID: 12347 Nomenclature: Orbitron 1000 Manufacturer: XYZ Corp Ship Date: 01/02/17 ---------------------------------------------- mysql> Fetched data successfullyAdvertisements