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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

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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 GROUP BY Clause

The SQL GROUP BY clause is a powerful feature that allows you to group rows based on one or more columns. It's commonly used with aggregate functions to perform calculations on grouped data.

Purpose and Functionality

GROUP BY serves two primary purposes:

  1. Organizing data into groups based on specified columns
  2. Enabling the use of aggregate functions on these groups

This clause is particularly useful when you need to analyze data across categories or perform summary calculations.

Basic Syntax

SELECT column1, column2, aggregate_function(column3)
FROM table_name
GROUP BY column1, column2;

In this syntax, columns after SELECT that are not inside an aggregate function must appear in the GROUP BY clause.

Common Use Cases

1. Counting Records per Group

SELECT department, COUNT(*) as employee_count
FROM employees
GROUP BY department;

This query counts the number of employees in each department.

2. Calculating Averages

SELECT product_category, AVG(price) as average_price
FROM products
GROUP BY product_category;

Here, we're calculating the average price for each product category.

Important Considerations

  • GROUP BY is executed after the WHERE clause but before the ORDER BY clause.
  • Columns in the SELECT statement that are not aggregated must appear in the GROUP BY clause.
  • You can group by multiple columns to create more specific groups.
  • Use the HAVING Clause to filter grouped results, similar to how WHERE filters individual rows.

Advanced Usage: Multiple Column Grouping

SELECT department, job_title, AVG(salary) as avg_salary
FROM employees
GROUP BY department, job_title;

This query groups employees by both department and job title, then calculates the average salary for each group.

Combining with Other Clauses

GROUP BY is often used in conjunction with other SQL clauses to create more complex queries:

SELECT department, COUNT(*) as employee_count
FROM employees
WHERE hire_date > '2020-01-01'
GROUP BY department
HAVING COUNT(*) > 5
ORDER BY employee_count DESC;

This query combines WHERE, GROUP BY, HAVING, and ORDER BY clauses to find departments with more than 5 employees hired after January 1, 2020, sorted by the number of employees.

Best Practices

  • Always ensure that non-aggregated columns in the SELECT statement are included in the GROUP BY clause.
  • Use GROUP BY with Aggregate Functions to get meaningful results.
  • Consider the performance impact on large datasets and use indexes on grouped columns when necessary.
  • Use HAVING for conditions on grouped results, not WHERE.

By mastering the GROUP BY clause, you'll be able to efficiently analyze and summarize data in your SQL queries, unlocking powerful insights from your databases.