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Topics

Introduction to SQL

What is SQL?SQL HistorySQL StandardsSQL vs NoSQLSQL Database Management Systems

SQL Basics

SQL SyntaxSQL CommentsSQL Data TypesSQL OperatorsSQL ExpressionsSQL LiteralsSQL IdentifiersSQL KeywordsSQL Case Sensitivity

SQL Database Fundamentals

Database ConceptsTables and FieldsPrimary KeysForeign KeysIndexesConstraintsNormalizationDenormalizationSQL Schema Design

SQL Data Manipulation

SQL SELECT StatementSQL INSERT StatementSQL UPDATE StatementSQL DELETE StatementSQL MERGE StatementSQL AliasesSQL WildcardsSQL LIKE OperatorSQL IN OperatorSQL BETWEEN OperatorSQL NULL ValuesSQL ORDER BY ClauseSQL LIMIT ClauseSQL OFFSET Clause

SQL Filtering and Sorting

SQL WHERE ClauseSQL AND, OR, NOT OperatorsSQL GROUP BY ClauseSQL HAVING ClauseSQL DISTINCT KeywordSQL TOP Clause

SQL Joins

SQL INNER JOINSQL LEFT JOINSQL RIGHT JOINSQL FULL OUTER JOINSQL CROSS JOINSQL Self JOINSQL Natural JOINSQL Multiple JOINs

SQL Functions

SQL Aggregate FunctionsSQL Scalar FunctionsSQL String FunctionsSQL Numeric FunctionsSQL Date FunctionsSQL Conversion FunctionsSQL System FunctionsSQL User-Defined Functions

SQL Subqueries

SQL Subquery BasicsCorrelated SubqueriesNested SubqueriesSQL EXISTS OperatorSQL ANY and ALL OperatorsSubqueries in SELECTSubqueries in FROMSubqueries in WHERE

SQL Views

Creating SQL ViewsAltering SQL ViewsDropping SQL ViewsUpdatable ViewsMaterialized ViewsView Limitations

SQL Transactions

SQL Transaction BasicsACID PropertiesBEGIN TRANSACTIONCOMMITROLLBACKSAVEPOINTTransaction Isolation Levels

SQL Data Definition

SQL CREATE TABLESQL ALTER TABLESQL DROP TABLESQL TRUNCATE TABLESQL CREATE INDEXSQL DROP INDEXSQL CREATE DATABASESQL ALTER DATABASESQL DROP DATABASE

SQL Data Control

SQL GRANTSQL REVOKESQL RolesSQL UsersSQL Privileges

SQL Performance Optimization

SQL Query OptimizationSQL Execution PlansSQL Index OptimizationSQL Query TuningSQL CachingSQL Partitioning

Advanced SQL Concepts

SQL Stored ProceduresSQL TriggersSQL CursorsSQL Common Table ExpressionsSQL Window FunctionsSQL Pivot and UnpivotSQL JSON OperationsSQL XML OperationsSQL Full-Text Search

SQL Best Practices

SQL Naming ConventionsSQL Code OrganizationSQL Error HandlingSQL Security Best PracticesSQL Backup and RecoverySQL Version Control

SQL Wildcards: Enhancing Pattern Matching in Queries

SQL wildcards are special characters used in WHERE clauses to perform pattern matching. They allow for more flexible and powerful searches within databases.

Common SQL Wildcards

The two most frequently used SQL wildcards are:

  • % (percent sign): Matches any sequence of zero or more characters
  • _ (underscore): Matches any single character

Using Wildcards with the LIKE Operator

Wildcards are typically used in conjunction with the LIKE operator to perform pattern matching in SQL queries.

Example 1: Using the % Wildcard

SELECT * FROM customers
WHERE last_name LIKE 'Sm%';

This query will return all customers whose last name starts with "Sm", such as Smith, Smart, or Smythe.

Example 2: Using the _ Wildcard

SELECT * FROM products
WHERE product_code LIKE 'A_C';

This query will match product codes that are three characters long, start with 'A', end with 'C', and have any single character in between, such as ABC, AXC, or A9C.

Combining Wildcards

You can use multiple wildcards in a single pattern for more complex matching:

SELECT * FROM employees
WHERE email LIKE '%@__%.com';

This query matches email addresses that end with ".com" and have at least two characters in the domain name.

Escaping Wildcards

If you need to search for the actual % or _ characters, you can escape them using a backslash:

SELECT * FROM messages
WHERE content LIKE '%50\% off%' ESCAPE '\';

This query searches for messages containing the phrase "50% off", escaping the % character.

Best Practices and Considerations

  • Use wildcards sparingly, as they can negatively impact query performance, especially on large datasets.
  • Consider using indexes on columns frequently searched with wildcards to improve performance.
  • Be aware that wildcard searches at the beginning of a pattern (e.g., '%text') can be particularly slow.
  • Remember that wildcards work differently across various database management systems. Always consult your specific DBMS documentation.

Alternatives to Wildcards

For more advanced pattern matching, consider using:

  • Regular expressions (if supported by your DBMS)
  • Full-text search capabilities for more efficient text searching

By mastering SQL wildcards, you can create more flexible and powerful queries, enabling more precise data retrieval from your databases.