Oracle Database SQL Certified Associate
1 Introduction to SQL
1-1 Overview of SQL
1-2 History of SQL
1-3 SQL Standards
2 SQL Data Types
2-1 Numeric Data Types
2-2 Character Data Types
2-3 Date and Time Data Types
2-4 Large Object (LOB) Data Types
2-5 Miscellaneous Data Types
3 Creating and Managing Tables
3-1 Creating Tables
3-2 Modifying Tables
3-3 Dropping Tables
3-4 Table Constraints
3-5 Temporary Tables
4 Data Manipulation Language (DML)
4-1 Inserting Data
4-2 Updating Data
4-3 Deleting Data
4-4 Selecting Data
4-5 Using Subqueries
5 Data Control Language (DCL)
5-1 Granting Privileges
5-2 Revoking Privileges
6 Data Definition Language (DDL)
6-1 Creating Tables
6-2 Altering Tables
6-3 Dropping Tables
6-4 Creating Indexes
6-5 Dropping Indexes
6-6 Creating Views
6-7 Dropping Views
7 SQL Functions
7-1 Single-Row Functions
7-2 Aggregate Functions
7-3 Group Functions
7-4 Analytical Functions
8 Joins and Subqueries
8-1 Inner Joins
8-2 Outer Joins
8-3 Self-Joins
8-4 Cross Joins
8-5 Subqueries
9 Set Operators
9-1 UNION
9-2 UNION ALL
9-3 INTERSECT
9-4 MINUS
10 Grouping and Aggregation
10-1 GROUP BY Clause
10-2 HAVING Clause
10-3 ROLLUP and CUBE
10-4 GROUPING SETS
11 Transactions and Concurrency
11-1 Transaction Control Statements
11-2 Locking and Concurrency
11-3 Isolation Levels
12 Oracle SQL Developer
12-1 Overview of Oracle SQL Developer
12-2 Using SQL Worksheet
12-3 Managing Connections
12-4 Running Scripts
13 Advanced SQL Topics
13-1 Recursive Queries
13-2 Model Clause
13-3 PIVOT and UNPIVOT
13-4 Flashback Query
14 Performance Tuning
14-1 Query Optimization
14-2 Indexing Strategies
14-3 Analyzing Query Performance
15 Security and Auditing
15-1 User Management
15-2 Role Management
15-3 Auditing SQL Statements
16 Backup and Recovery
16-1 Backup Strategies
16-2 Recovery Strategies
16-3 Using RMAN
17 Oracle Database Architecture
17-1 Overview of Oracle Database Architecture
17-2 Memory Structures
17-3 Process Structures
17-4 Storage Structures
18 PLSQL Basics
18-1 Introduction to PLSQL
18-2 PLSQL Block Structure
18-3 Variables and Data Types
18-4 Control Structures
18-5 Exception Handling
19 Oracle SQL Certification Exam Preparation
19-1 Exam Objectives
19-2 Sample Questions
19-3 Practice Tests
19-4 Exam Tips
UNION ALL in Oracle SQL

UNION ALL in Oracle SQL

Key Concepts

UNION ALL in Oracle SQL is used to combine the result sets of two or more SELECT statements. Unlike UNION, which removes duplicate rows, UNION ALL includes all rows from each query, even if they are duplicates. Understanding the following key concepts is essential for effectively using UNION ALL:

1. Combining Result Sets

UNION ALL combines the result sets of multiple SELECT statements into a single result set. Each SELECT statement must have the same number of columns, and the corresponding columns must have compatible data types.

2. Including Duplicates

Unlike UNION, which removes duplicate rows, UNION ALL includes all rows from each query, including duplicates. This can be useful when you need to retain all data, even if there are overlapping rows.

3. Performance Considerations

UNION ALL is generally faster than UNION because it does not require the additional step of removing duplicates. However, it is important to ensure that the combined result set is not excessively large, as this can impact performance.

Detailed Explanation

1. Combining Result Sets

When using UNION ALL, each SELECT statement must have the same number of columns, and the corresponding columns must have compatible data types. For example, to combine the results of two queries from different tables:

SELECT EmployeeID, FirstName, LastName FROM Employees UNION ALL SELECT CustomerID, FirstName, LastName FROM Customers;

2. Including Duplicates

UNION ALL includes all rows from each query, even if they are duplicates. For example, if both queries return the same row, that row will appear twice in the combined result set:

SELECT OrderID, ProductID FROM Orders WHERE OrderDate = '2023-10-01' UNION ALL SELECT OrderID, ProductID FROM Orders WHERE OrderDate = '2023-10-01';

3. Performance Considerations

UNION ALL is generally faster than UNION because it does not require the additional step of removing duplicates. However, it is important to ensure that the combined result set is not excessively large, as this can impact performance. For example, combining large tables without proper indexing can lead to slow query execution:

SELECT * FROM LargeTable1 UNION ALL SELECT * FROM LargeTable2;

Examples and Analogies

Example 1: Combining Sales Data

Imagine you have sales data from two different regions and you want to combine them into a single report. Using UNION ALL will ensure that all sales records are included, even if there are duplicates:

SELECT Region, SalesAmount FROM Sales WHERE Region = 'North' UNION ALL SELECT Region, SalesAmount FROM Sales WHERE Region = 'South';

Example 2: Merging Customer Lists

Suppose you have two customer lists from different sources and you want to merge them into a single list. UNION ALL will include all customers, even if they appear in both lists:

SELECT CustomerID, FirstName, LastName FROM Customers1 UNION ALL SELECT CustomerID, FirstName, LastName FROM Customers2;

Example 3: Combining Inventory Records

If you have inventory records from two different warehouses and you want to combine them into a single inventory report, UNION ALL will ensure that all inventory records are included:

SELECT ProductID, Quantity FROM Inventory WHERE Warehouse = 'A' UNION ALL SELECT ProductID, Quantity FROM Inventory WHERE Warehouse = 'B';