Join order and performance impact in SQL - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Effect of Join Order on Result Set

Consider two tables: Employees and Departments. Employees have a department_id linking to Departments. What is the output of the following queries?

Query 1:
SELECT e.name, d.name FROM Employees e JOIN Departments d ON e.department_id = d.id;

Query 2:
SELECT d.name, e.name FROM Departments d JOIN Employees e ON e.department_id = d.id;

Do both queries return the same rows and order?

SQL

SELECT e.name, d.name FROM Employees e JOIN Departments d ON e.department_id = d.id;
SELECT d.name, e.name FROM Departments d JOIN Employees e ON e.department_id = d.id;

A Both queries return the same rows but the column order is different.

B The queries return different rows because join order changes the result.

C The queries cause a syntax error due to join order.

D Both queries return the same rows in the same order.

💡 Hint

Think about how SQL handles join order and column selection.

Both queries join the same tables on the same condition, so the rows returned are the same. However, the selected columns are in different order, so the column order differs.

🧠 Conceptual

intermediate

Impact of Join Order on Query Performance

Which statement best describes how join order can affect query performance in SQL databases?

A Join order only affects performance if using outer joins, not inner joins.

B Join order affects performance only when joining more than two tables.

C Join order can affect performance because some join sequences reduce intermediate result sizes earlier.

D Join order never affects performance because the database optimizer always rearranges joins optimally.

💡 Hint

Consider how filtering early can reduce work.

Join order matters because joining tables that reduce the number of rows early can improve performance by reducing the size of intermediate results.

📝 Syntax

advanced

Identify the Syntax Error in Join Query

Which of the following SQL queries will cause a syntax error due to incorrect join order or syntax?

SQL

SELECT * FROM A JOIN B ON A.id = B.a_id JOIN C ON B.id = C.b_id;

A SELECT * FROM A JOIN B ON A.id = B.a_id JOIN C B ON B.id = C.b_id;

B SELECT * FROM A JOIN ON A.id = B.a_id B JOIN C ON B.id = C.b_id;

C SELECT * FROM A JOIN B ON A.id = B.a_id JOIN C ON B.id = C.b_id;

D SELECT * FROM A JOIN B ON A.id = B.a_id JOIN C ON C.id = B.b_id;

💡 Hint

Look carefully at the placement of keywords in the JOIN clauses.

Option B has 'JOIN ON' without specifying the table to join before ON, causing a syntax error.

❓ optimization

advanced

Choosing Join Order for Performance

You have three tables: Orders (large), Customers (medium), and Countries (small). Which join order is likely to be most efficient?

A Join Countries to Customers first, then join the result to Orders.

B Join Orders to Customers first, then join the result to Countries.

C Join Orders to Countries first, then join the result to Customers.

D Join Customers to Orders first, then join the result to Countries.

💡 Hint

Think about joining smaller tables first to reduce intermediate results.

Joining the smaller tables (Countries and Customers) first reduces the number of rows before joining the large Orders table, improving performance.

🔧 Debug

expert

Diagnose Performance Issue from Join Order

A query joining four tables runs very slowly. The join order is:

SELECT * FROM A JOIN B ON A.id = B.a_id JOIN C ON B.id = C.b_id JOIN D ON C.id = D.c_id;

Tables sizes: A (1 million rows), B (10 rows), C (1000 rows), D (500 rows). Which change to join order will most likely improve performance?

A Join C to D first, then join B, then join A.

B Join A to B first, then join C, then join D.

C Join D to C first, then join B, then join A.

D Join B to C first, then join D, then join A last.

💡 Hint

Try to join the smallest tables first to reduce intermediate results before joining the largest table.

Joining the smallest tables B and C first reduces the number of rows early, then joining D and finally the large table A improves performance.