[Solved] Consider these two queries on tables orders and customers. Which one is likely to run faster on large datasets?Query 1:SELECT o.id FROM orders o WHERE o.customer_id IN (SELECT c.... | SQL

SQL - Subqueries

Consider these two queries on tables orders and customers. Which one is likely to run faster on large datasets?

Query 1:
SELECT o.id FROM orders o WHERE o.customer_id IN (SELECT c.id FROM customers c WHERE c.status = 'active');
Query 2:
SELECT o.id FROM orders o JOIN customers c ON o.customer_id = c.id WHERE c.status = 'active';

ABoth queries have the same performance always.

BQuery 1 is faster because subqueries are optimized better.

CQuery 2 is faster because JOINs allow better optimization and indexing.

DQuery 1 is faster because it avoids JOIN overhead.

Step-by-Step Solution

Solution:

Step 1: Analyze Query 1
Query 1 uses a subquery in IN(), which may run the subquery once but can be less efficient on large data.
Step 2: Analyze Query 2
Query 2 uses a JOIN, which databases optimize well with indexes, often faster on large datasets.
Final Answer:
Query 2 is faster because JOINs allow better optimization and indexing. -> Option C
Quick Check:
JOIN optimization = Query 2 faster [OK]

Quick Trick: JOINs usually outperform subqueries on large tables [OK]

Common Mistakes:

MISTAKES

Assuming subqueries always run faster
Ignoring indexing benefits of JOINs
Believing IN() subqueries scale well always

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More SQL Quizzes

Consider these two queries on tables orders and customers. Which one is likely to run faster on large datasets?

Step 1: Analyze Query 1

Step 2: Analyze Query 2

Final Answer:

Quick Check:

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