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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 DISTINCT Keyword

The SQL DISTINCT keyword is a powerful tool used in SELECT statements to eliminate duplicate rows from query results. It's an essential feature for data analysis and reporting, ensuring that only unique values are returned.

Purpose and Functionality

DISTINCT serves a crucial role in data retrieval:

  • Removes duplicate rows from the result set
  • Helps in identifying unique values in a column or set of columns
  • Simplifies data analysis by reducing redundancy

Basic Syntax

The DISTINCT keyword is placed immediately after the SELECT keyword in a query:

SELECT DISTINCT column1, column2, ...
FROM table_name;

Usage Examples

Example 1: Single Column

To retrieve unique values from a single column:

SELECT DISTINCT city
FROM customers;

This query returns a list of unique cities from the customers table, eliminating any duplicates.

Example 2: Multiple Columns

DISTINCT can also be applied to multiple columns:

SELECT DISTINCT country, city
FROM customers;

This query returns unique combinations of country and city, treating each combination as a distinct entity.

Important Considerations

  • DISTINCT operates on the entire row, not just individual columns when multiple columns are specified.
  • It can impact query performance, especially on large datasets.
  • NULL values are considered equal for the purpose of DISTINCT.
  • DISTINCT cannot be used with aggregate functions directly, but can be used in subqueries.

Best Practices

  1. Use DISTINCT judiciously, as it can affect query performance.
  2. Consider using GROUP BY for more complex scenarios involving aggregations.
  3. Combine DISTINCT with other SQL clauses like WHERE and ORDER BY for more refined results.
  4. Be aware of the impact on large datasets and optimize queries accordingly.

Common Use Cases

The DISTINCT keyword is particularly useful in scenarios such as:

  • Identifying unique customer locations
  • Finding distinct product categories in an inventory
  • Analyzing unique combinations of attributes in datasets
  • Removing duplicate entries in data cleaning processes

Conclusion

The SQL DISTINCT keyword is a valuable tool for data analysis and query optimization. By understanding its proper usage and considering its impact on query performance, you can effectively leverage DISTINCT to retrieve unique data sets and gain valuable insights from your databases.