Coding/Learn/sql/sql union
SQL & Relational Database Engineering Complete Course
01.Introduction & Relational Database Architecture
02.Syntax, Clauses & Execution Order
03.SELECT: Column Projection & Expressions
04.SELECT DISTINCT & Row Deduplication
05.WHERE Clause: Filtering Predicates & Comparison
06.ORDER BY: Sorting, Multi-Column & NULLS Ordering
07.Logical Operators: AND, OR, NOT & Operator Precedence
08.Comments: Single-Line (--), Multi-Line (/* */) & Query Hints
09.Operators: Arithmetic, Bitwise & String Concatenation
10.LIKE Operator & Wildcard Characters (%, _)
11.IN & NOT IN: Membership Operators & Subqueries
12.BETWEEN: Range Filtering for Numbers, Dates & Text
13.NULL Values: Three-Valued Logic, IS NULL & IS NOT NULL
14.Aliases: AS Keyword for Columns & Tables
15.SELECT TOP, LIMIT & OFFSET Pagination
16.INSERT INTO: Single & Multi-Row Insertions
17.UPDATE: Modifying Existing Records & Safe WHERE Rules
18.DELETE: Removing Rows vs TRUNCATE TABLE
19.SELECT INTO & Table Backups (CREATE TABLE AS SELECT)
20.INSERT INTO SELECT: Bulk Data Migration
21.Aggregate Functions: Statistical Summaries
22.MIN() & MAX(): Finding Extremes Across Types
23.COUNT: COUNT(*), COUNT(column) & COUNT(DISTINCT)
24.SUM() & AVG(): Numerical Aggregation & Averages
25.GROUP BY: Aggregation Buckets & Categorical Metrics
26.HAVING: Filtering Aggregated Groups vs WHERE
27.Joins Architecture: Relational Modeling & Venn Diagrams
28.INNER JOIN: Matching Intersections Across Tables
29.LEFT JOIN: Preserving Unmatched Left Rows & Finding Orphans
30.RIGHT JOIN: Preserving Unmatched Right Rows
31.FULL JOIN: Full Outer Join & Complete Reconciliation
32.SELF JOIN: Hierarchies, Trees & Parent-Child Relationships
33.UNION: Combining Result Sets with Automatic Deduplication
34.UNION ALL vs UNION: Performance & Duplicates
35.EXISTS & NOT EXISTS: Correlated Subqueries
36.ANY & ALL: Quantified Comparison Subqueries
37.CASE: Conditional Expressions & Data Transposition
38.Null Functions: COALESCE, IFNULL, ISNULL & NULLIF
39.Stored Procedures, Functions & Query Parameters
40.CREATE & DROP DATABASE: Environment Lifecycle
41.CREATE TABLE: Defining Schemas & Types
42.DROP & TRUNCATE TABLE: Structure vs Data Purging
43.ALTER TABLE: Modifying Columns & Schema Evolution
44.AUTO INCREMENT & Sequences: Identity Generation
45.Date & Time Formats: Timestamp Manipulation
46.Views: Virtual Tables & Security Layers
47.Constraints Overview: Relational Integrity
48.NOT NULL & UNIQUE: Data Invariants
49.PRIMARY KEY: Entity Uniqueness & Clustering
50.FOREIGN KEY: Referential Integrity & Cascades
51.CHECK & DEFAULT: Business Rules at DB Layer
52.CREATE INDEX: B-Trees & Query Optimization
53.Injection Defense: Threat Models & Prevention
54.Parameters & Prepared Statements: Safe Execution
55.Database Engines & Hosting Architecture
56.Dialect References & Data Type Standards
57.Production Best Practices & Query Tuning Checklist
58.Interactive Exercises: Multi-Table Analytics Challenges
59.Comprehensive Assessment & Knowledge Check
60.Capstone Project: Enterprise Analytics Engine
61.Mastery Certification & Graduate Verification
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LearnSQL UNION: Combining Result Sets with Automatic Deduplication
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Lesson 33 of 61
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SQL UNION: Combining Result Sets with Automatic Deduplication

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In Plain English

The `UNION` operator combines the result sets of two or more `SELECT` statements into a single combined result set, automatically removing duplicate rows. Unlike joins (which combine columns horizontally), `UNION` stacks rows vertically.

The Mental Model

"A JOIN is taping two cards together side by side (wider); a UNION is stacking two decks of cards on top of each other into a single tall deck (taller)."

Deep Dive: How It Works

Structural Rules: 1) Each SELECT must have the EXACT SAME number of columns. 2) Corresponding columns must have compatible data types. 3) Output column names are taken from the FIRST SELECT statement.

Automatic Deduplication: `UNION` performs a sort and hash deduplication pass to eliminate duplicate rows across both queries.

Final ORDER BY: A single `ORDER BY` clause placed at the very end sorts the entire combined union result.

Syntax Blueprint

SELECT email, 'Customer' AS source FROM customers
UNION
SELECT email, 'Supplier' AS source FROM suppliers
ORDER BY email ASC;

UNION vertically stacks rows from multiple queries and removes duplicates.

PointCore Rules to Remember

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Vertical Stacking: Combines row outputs rather than expanding columns.
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Automatic Deduplication: Filters out duplicate records across both query results.
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First SELECT Headers: Column aliases declared in the first SELECT define final output column names.

Common Beginner Traps & How to Fix Them

Mistake:Putting an `ORDER BY` clause inside individual SELECT queries before the UNION keyword.

Why it happens: Syntax error in standard SQL: individual union branches cannot have isolated ORDER BY clauses.

How to fix: Place one single `ORDER BY` clause at the very end of the final union statement.

Pro Tip: If you do NOT need deduplication, always prefer `UNION ALL`: it is dramatically faster because it skips the expensive sorting and hashing pass.

Live Interactive Example

Hit Run Code to see it live
Combining Customer and Vendor Contacts with UNION
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: UNION combined emails from both tables and automatically eliminated the duplicate [email protected].

Your Turn: Micro Challenge

No pressure! Edit the starter code below and test your solution with instant feedback.

Micro Exercise

Combine Distinct Values with UNION

  • PointCombine `SELECT city FROM offices UNION SELECT city FROM warehouses ORDER BY city;`.
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Sandbox Output
Click "Run & Check" to test your solution.

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