Coding/Learn/sql/sql check default
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 CHECK & DEFAULT: Business Rules at DB Layer
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Lesson 51 of 61
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SQL CHECK & DEFAULT: Business Rules at DB Layer

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In Plain English

`CHECK` constraints evaluate arbitrary boolean expressions on inserted or updated row values, rejecting values outside allowable domain ranges (e.g. positive prices, valid discount percentages, acceptable enum statuses). `DEFAULT` supplies automatic values whenever an insertion omits the column, standardizing initial states.

The Mental Model

"`CHECK` is a height requirement sign at a roller coaster: anyone shorter than 48 inches is stopped at the gate; `DEFAULT` is the automatic admission wristband given to everyone who enters."

Deep Dive: How It Works

CHECK Expressions: Can reference multiple columns in the same row (`CHECK(end_date >= start_date)`).

Emulating Enums: `CHECK(status IN ('draft', 'published', 'archived'))` provides lightweight enum validation without proprietary type creation.

Dynamic Defaults: `DEFAULT CURRENT_TIMESTAMP` or `DEFAULT (datetime('now'))` records insertion time automatically.

Syntax Blueprint

CREATE TABLE events (
  id INTEGER PRIMARY KEY,
  status TEXT DEFAULT 'active' CHECK(status IN ('active', 'closed')),
  capacity INTEGER CHECK(capacity > 0),
  discount REAL DEFAULT 0.0 CHECK(discount >= 0.0 AND discount <= 1.0)
);

Applies boolean range assertions and default values to columns.

PointCore Rules to Remember

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Domain Validation: Guarantees numbers remain in range and strings match allowable status lists.
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Multi-Column Invariants: Enforces temporal logic such as `end_date >= start_date`.
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Automatic Fallbacks: Supplies standard initial values when columns are omitted in INSERTs.

Common Beginner Traps & How to Fix Them

Mistake:Using subqueries inside a `CHECK` constraint.

Why it happens: Standard SQL forbids subqueries inside CHECK expressions (CHECK only evaluates the current row).

How to fix: Use foreign keys or database triggers for cross-table validation.

Pro Tip: Combine `CHECK` with `LOWER()` to ensure case-insensitive enum validation: `CHECK(LOWER(status) IN ('active', 'archived'))`.

Live Interactive Example

Hit Run Code to see it live
Enforcing Business Domain Rules with CHECK and DEFAULT
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: The default status CONFIRMED was applied and nights/rates passed validation.

Your Turn: Micro Challenge

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

Micro Exercise

Apply CHECK and DEFAULT to Products

  • PointCreate a table `products_v2` with `id INTEGER PRIMARY KEY`, `name TEXT NOT NULL`, `rating REAL DEFAULT 5.0 CHECK(rating >= 1.0 AND rating <= 5.0)`.
  • PointInsert a product ("Laptop") without specifying rating, then select all columns.
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Sandbox Output
Click "Run & Check" to test your solution.

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