# **🗄️ Booth: SQL (1974)** * **Creator:** Donald D. Chamberlin and Raymond F. Boyce (IBM) * **Design Philosophy:** A declarative query language built on Edgar F. Codd’s relational database model. Instead of detailing *how* to retrieve records procedurally, programmers declare *what* data they require. * **Key Innovations:** Declarative execution paradigm, relational tables (tuples and attributes), structural schemas, indexes, and aggregate mathematical relations. ## **🚀 Hello, World\!** While SQL does not compile into standalone runtimes, we can select a greeting literal from a system table or mock query. SELECT 'Hello, World\!' AS greeting; ## **🎨 Showpiece: Relational Database Query with Joins** This script creates relational tables representing a store schema, populates them, and runs an analytical aggregate query utilizing relational algebra mapping. Mathematically, we map a relational join and selection to compute aggregate sales: ![][image1]\-- 1\. Create schemas CREATE TABLE Products ( product\_id INTEGER PRIMARY KEY, name VARCHAR(50), category VARCHAR(50), price DECIMAL(10, 2\) ); CREATE TABLE Orders ( order\_id INTEGER PRIMARY KEY, product\_id INTEGER, quantity INT, order\_date DATE, FOREIGN KEY (product\_id) REFERENCES Products(product\_id) ); \-- 2\. Insert analytical data INSERT INTO Products VALUES (1, 'Compiler Principles', 'Books', 49.99); INSERT INTO Products VALUES (2, 'Mechanical Keyboard', 'Electronics', 120.00); INSERT INTO Products VALUES (3, 'LISP Mug', 'Merchandise', 15.50); INSERT INTO Orders VALUES (101, 1, 2, '1979-10-12'); \-- 2 books INSERT INTO Orders VALUES (102, 3, 5, '1979-10-14'); \-- 5 mugs INSERT INTO Orders VALUES (103, 2, 1, '1979-10-15'); \-- 1 keyboard \-- 3\. Calculate total revenue generated per product category SELECT p.category, SUM(o.quantity) AS total\_units\_sold, SUM(p.price \* o.quantity) AS total\_revenue FROM Orders o INNER JOIN Products p ON o.product\_id \= p.product\_id GROUP\_BY p.category ORDER BY total\_revenue DESC; [image1]: