Coding/Learn/sql/sql min max
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 MIN() & MAX(): Finding Extremes Across Types
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Lesson 22 of 61
5 mins read

SQL MIN() & MAX(): Finding Extremes Across Types

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In Plain English

`MIN()` returns the lowest value and `MAX()` returns the highest value in a column or expression. They operate seamlessly across numerical amounts, alphabetical text strings (A to Z), dates, and timestamps.

The Mental Model

"`MIN()` is finding the shortest person or earliest timestamp in a room; `MAX()` is finding the tallest person or most recent event."

Deep Dive: How It Works

Type Support: Numerical (lowest/highest numbers), Date/Time (`MIN(created_at)` = oldest record, `MAX(created_at)` = newest record), Text (`MIN(name)` = alphabetically first name).

Index Optimization: If the column is indexed with a B-Tree, `SELECT MIN(col)` and `SELECT MAX(col)` execute in O(1) instantaneous time by jumping directly to the left-most or right-most leaf node.

Subquery Pattern: Finding the full row holding the max value: `SELECT * FROM products WHERE price = (SELECT MAX(price) FROM products)`.

Syntax Blueprint

SELECT MIN(price) AS cheapest, MAX(price) AS most_expensive
FROM products;

-- Find newest user registration:
SELECT MAX(registered_at) AS latest_signup FROM users;

Use MIN and MAX to discover lowest and highest values across data types.

PointCore Rules to Remember

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Date Extremes: MIN finds oldest/earliest dates; MAX finds newest/latest dates.
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O(1) B-Tree Speed: MIN and MAX on indexed columns require zero table scanning.
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Full Row Extrema: Use subqueries or window functions to retrieve other columns alongside the maximum.

Common Beginner Traps & How to Fix Them

Mistake:Writing `SELECT name, MAX(price) FROM products` expecting the name belonging to the highest price product.

Why it happens: Without subqueries or GROUP BY, SQL returns the max price paired with an arbitrary name.

How to fix: Use `WHERE price = (SELECT MAX(price) FROM products)` or `ORDER BY price DESC LIMIT 1`.

Pro Tip: In PostgreSQL, use `LEAST(a, b)` and `GREATEST(a, b)` to find the min/max across columns in the SAME row.

Live Interactive Example

Hit Run Code to see it live
Finding Price and Date Extremes
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: MIN and MAX found the salary extremes ($45k/$110k) and date boundaries.

Your Turn: Micro Challenge

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

Micro Exercise

Query Min and Max Prices

  • PointSelect `MIN(price) AS min_p`, `MAX(price) AS max_p` from `catalog`.
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Sandbox Output
Click "Run & Check" to test your solution.

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