UPDATE with JOIN in MySQL - Time & Space Complexity

Time Complexity: UPDATE with JOIN

O(n)

Understanding Time Complexity

When we update data in one table based on matching rows in another, it’s important to know how the work grows as data grows.

We want to understand how the time to complete the update changes when the tables get bigger.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

UPDATE orders o
JOIN customers c ON o.customer_id = c.id
SET o.status = 'processed'
WHERE c.region = 'North';
    

This code updates the status of orders for customers in the 'North' region by joining the orders and customers tables.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Scanning and matching rows between the orders and customers tables using the JOIN condition.
• How many times: For each order row, the database looks for matching customer rows to check the region condition.

How Execution Grows With Input

As the number of orders and customers grows, the database must check more rows to find matches.

Input Size (n)	Approx. Operations
10 orders, 5 customers	About 10 checks to find matching customers
100 orders, 50 customers	About 100 checks, each matching a customer
1000 orders, 500 customers	About 1000 checks, matching customers as needed

Pattern observation: The work grows roughly in proportion to the number of orders, assuming efficient customer lookup.

Final Time Complexity

Time Complexity: O(n)

This means the time to update grows roughly in direct proportion to the number of rows in the orders table.

Common Mistake

[X] Wrong: "The update will always take the same time no matter how many rows are in the tables."

[OK] Correct: More rows mean more matching checks, so the time grows with data size, not stays constant.

Interview Connect

Understanding how joins affect update speed helps you explain database performance clearly and shows you know how data size impacts work.

Self-Check

"What if the customers table had no index on the id column? How would the time complexity change?"

Practice

1. What is the main purpose of using UPDATE with JOIN in MySQL?

easy

A. To select data from multiple tables without updating

B. To delete rows from two tables at once

C. To update rows in one table based on matching rows in another table

D. To create a new table by joining two tables

Solution

1. Step 1: Understand the purpose of UPDATE with JOIN

   UPDATE with JOIN is used to change data in one table using related data from another table by matching rows.

2. Step 2: Compare options

   Only To update rows in one table based on matching rows in another table describes updating one table based on another, which matches the purpose.

3. Final Answer:

   To update rows in one table based on matching rows in another table -> Option C

4. Quick Check:

   UPDATE with JOIN = update one table using another [OK]

Hint: UPDATE with JOIN updates one table using another table's data [OK]

Common Mistakes:

• Confusing UPDATE with JOIN as a SELECT operation
• Thinking UPDATE with JOIN deletes data
• Believing it creates new tables

2. Which of the following is the correct syntax to update table1 using table2 with a JOIN on id in MySQL?

easy

A. UPDATE table1 JOIN table2 ON table1.id = table2.id SET table1.value = table2.value;

B. UPDATE table1 SET table1.value = table2.value JOIN table2 ON table1.id = table2.id;

C. UPDATE table1 SET value = table2.value WHERE table1.id = table2.id JOIN table2;

D. UPDATE table1, table2 SET table1.value = table2.value WHERE table1.id = table2.id;

Solution

1. Step 1: Recall correct UPDATE with JOIN syntax

   The correct syntax places JOIN after UPDATE, then ON condition, then SET clause.

2. Step 2: Check each option

   UPDATE table1 JOIN table2 ON table1.id = table2.id SET table1.value = table2.value; matches the correct syntax: UPDATE table1 JOIN table2 ON ... SET ...; others misuse JOIN placement or syntax.

3. Final Answer:

   UPDATE table1 JOIN table2 ON table1.id = table2.id SET table1.value = table2.value; -> Option A

4. Quick Check:

   UPDATE + JOIN + ON + SET order = B [OK]

Hint: JOIN comes right after UPDATE, then ON, then SET [OK]

Common Mistakes:

• Placing JOIN after SET clause
• Using WHERE instead of ON for JOIN condition
• Separating tables with commas instead of JOIN

3. Given these tables:

users(id, name, city_id)
cities(id, city_name)

What will this query do?

UPDATE users u JOIN cities c ON u.city_id = c.id SET u.name = CONCAT(u.name, ' - ', c.city_name) WHERE c.city_name = 'Paris';

medium

A. Delete users who live in Paris

B. Replace all user names with 'Paris'

C. Add a new user with name 'Paris'

D. Append ' - Paris' to the name of users living in Paris

Solution

1. Step 1: Understand the JOIN and SET clauses

   The query joins users with cities on city_id, then updates user names by appending city name for users in Paris.

2. Step 2: Analyze WHERE condition

   Only users with city_name 'Paris' are updated, so their names get ' - Paris' appended.

3. Final Answer:

   Append ' - Paris' to the name of users living in Paris -> Option D

4. Quick Check:

   UPDATE with JOIN + WHERE filters = append city name [OK]

Hint: JOIN matches rows; SET changes only filtered rows [OK]

Common Mistakes:

• Thinking it replaces all names with 'Paris'
• Confusing UPDATE with INSERT
• Assuming it deletes rows

4. Identify the error in this query:

UPDATE orders o JOIN customers c SET o.status = 'shipped' ON o.customer_id = c.id WHERE c.region = 'West';

medium

A. The ON clause is after SET instead of after JOIN

B. Missing WHERE clause

C. Using JOIN instead of INNER JOIN

D. No error, query is correct

Solution

1. Step 1: Check JOIN syntax order

   ON clause must come immediately after JOIN, before SET clause.

2. Step 2: Locate ON clause in query

   ON is incorrectly placed after SET, causing syntax error.

3. Final Answer:

   The ON clause is after SET instead of after JOIN -> Option A

4. Quick Check:

   ON must follow JOIN, not SET [OK]

Hint: ON clause always follows JOIN, never SET [OK]

Common Mistakes:

• Placing ON after SET clause
• Confusing WHERE and ON clauses
• Assuming JOIN needs INNER keyword

5. You have two tables:

products(id, price, category_id)
categories(id, discount_percent)

You want to reduce the price of all products by their category discount. Which query correctly updates products.price applying the discount using UPDATE with JOIN?

hard

A. UPDATE products p, categories c SET p.price = p.price - (p.price * c.discount_percent / 100) WHERE p.category_id = c.id;

B. UPDATE products p JOIN categories c ON p.category_id = c.id SET p.price = p.price - (p.price * c.discount_percent / 100);

C. UPDATE products p SET p.price = p.price - (p.price * c.discount_percent / 100) JOIN categories c ON p.category_id = c.id;

D. UPDATE products p INNER JOIN categories c WHERE p.category_id = c.id SET p.price = p.price * c.discount_percent;

Solution

1. Step 1: Write correct UPDATE with JOIN syntax

   JOIN must come after UPDATE, then ON condition, then SET clause with calculation.

2. Step 2: Verify discount calculation

   Price is reduced by price * discount_percent / 100, which is correct formula.

3. Step 3: Check other options

   Other options misuse JOIN placement, use comma syntax instead of explicit JOIN, or have incorrect syntax/order and discount formulas.

4. Final Answer:

   UPDATE products p JOIN categories c ON p.category_id = c.id SET p.price = p.price - (p.price * c.discount_percent / 100); -> Option B

5. Quick Check:

   UPDATE + JOIN + ON + SET with correct formula = C [OK]

Hint: JOIN after UPDATE, ON before SET, formula subtracts discount [OK]

Common Mistakes:

• Placing JOIN after SET clause
• Using WHERE instead of ON for JOIN
• Incorrect discount formula