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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 Logical Operators: AND, OR, NOT & Operator Precedence
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Lesson 07 of 61
5 mins read

SQL Logical Operators: AND, OR, NOT & Operator Precedence

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In Plain English

Logical operators combine multiple search conditions in a `WHERE` clause: `AND` requires ALL conditions to be true, `OR` requires AT LEAST ONE condition to be true, and `NOT` reverses a condition. Crucially, `AND` has higher precedence than `OR`, requiring parentheses `()` to enforce correct evaluation logic.

The Mental Model

"`AND` is two keys required to open a safe; `OR` is having a physical key OR an electronic passcode; Parentheses `()` are mathematical brackets ensuring operations calculate in intended order."

Deep Dive: How It Works

Operator Precedence: `NOT` evaluates first, then `AND`, then `OR`.

The Deadly Precedence Trap: `WHERE role = 'Admin' OR role = 'Manager' AND status = 'active'` evaluates as `role = 'Admin' OR (role = 'Manager' AND status = 'active')`, unintentionally exposing inactive admins!

Fixing with Parentheses: `WHERE (role = 'Admin' OR role = 'Manager') AND status = 'active'`.

Syntax Blueprint

SELECT *
FROM table_name
WHERE (condition1 OR condition2) AND NOT condition3;

Always group OR conditions inside parentheses when combining with AND.

PointCore Rules to Remember

Point star
Precedence Rule: AND binds tighter than OR. Always use parentheses when mixing them.
Point star
NOT Operator: Inverts conditions: `WHERE NOT status = 'banned'` or `WHERE NOT (age < 18)`.
Point star
Short-Circuit Optimization: Database engines evaluate cheaper predicates first when possible.

Common Beginner Traps & How to Fix Them

Mistake:Writing `WHERE status = 'active' AND role = 'admin' OR role = 'editor'` without parentheses.

Why it happens: Assuming left-to-right evaluation order.

How to fix: Group OR branches explicitly: `WHERE status = 'active' AND (role = 'admin' OR role = 'editor')`.

Pro Tip: When testing a column against multiple possible values, prefer `IN ('admin', 'editor')` over chained `OR` statements for clarity.

Live Interactive Example

Hit Run Code to see it live
Combining Logic with Parentheses and NOT
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: Parentheses ensured that inactive VIP Bob was excluded and only active US VIP/Premiums matched.

Your Turn: Micro Challenge

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

Micro Exercise

Filter with AND, OR, and Parentheses

  • PointSelect `name` from `vehicles` where `(type = 'Car' OR type = 'Truck') AND available = 1`.
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Sandbox Output
Click "Run & Check" to test your solution.

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