Question 327 of 503
Monitor and optimize database performancehardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to create a composite index on orders(product_id, order_date) for optimal query performance. This ordering works because MySQL can use a single index scan to both filter on the highly selective product_id column and then satisfy the subsequent range or sort operation on order_date, eliminating the need for a costly filesort or extra table lookups. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of leftmost prefix rules and how composite index column order directly impacts execution plans—a common trap is placing the range column first, which would render the index useless for the equality filter. Remember the memory tip: "Equality first, then range" to ensure your composite index serves both the WHERE and ORDER BY clauses efficiently.

PCDE Monitor and optimize database performance Practice Question

This PCDE practice question tests your understanding of monitor and optimize database performance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Query: SELECT p.*, o.* FROM products p JOIN orders o ON p.product_id = o.product_id WHERE o.order_date BETWEEN '2023-01-01' AND '2023-01-31';
Time: 12.345 sec
Rows examined: 1 million
Rows sent: 5000

A slow query log entry shows the above for a Cloud SQL for MySQL instance. Which index would most improve performance?

Question 1hardmultiple choice
Full question →

Exhibit

Query: SELECT p.*, o.* FROM products p JOIN orders o ON p.product_id = o.product_id WHERE o.order_date BETWEEN '2023-01-01' AND '2023-01-31';
Time: 12.345 sec
Rows examined: 1 million
Rows sent: 5000

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Composite index on orders(product_id, order_date)

The query likely filters or joins on product_id and then sorts or filters by order_date, so a composite index on orders(product_id, order_date) allows the database to satisfy both conditions with a single index scan, avoiding a filesort or extra lookups. In MySQL, a composite index with the most selective column first (product_id) followed by the range/order column (order_date) is optimal for queries that filter on product_id and then order or filter by order_date.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Index on products(product_id)

    Why it's wrong here

    Index on the products table helps the join but does not reduce rows examined in orders.

  • Index on orders(order_date)

    Why it's wrong here

    This index helps filter by date but does not cover the join column product_id, leading to many random lookups.

  • Composite index on orders(product_id, order_date)

    Why this is correct

    This index allows the join to quickly find matching product_ids and then apply the date range, reducing the number of rows examined.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Composite index on orders(order_date, product_id)

    Why it's wrong here

    This index scans the entire date range (potentially many rows) and then join, which may still examine many rows.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the leftmost prefix rule and the importance of column order in composite indexes, trapping candidates who think any composite index covering both columns is equally effective regardless of column order.

Detailed technical explanation

How to think about this question

MySQL uses the leftmost prefix rule for composite indexes, meaning the index is sorted by the first column, then the second, etc. When a query has an equality condition on product_id and a range or order by on order_date, the index (product_id, order_date) allows a tight range scan on order_date within each product_id group, while the reverse order would require scanning all order_date ranges and then filtering by product_id. In practice, this can reduce query execution time from seconds to milliseconds for large tables.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

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FAQ

Questions learners often ask

What does this PCDE question test?

Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Composite index on orders(product_id, order_date) — The query likely filters or joins on product_id and then sorts or filters by order_date, so a composite index on orders(product_id, order_date) allows the database to satisfy both conditions with a single index scan, avoiding a filesort or extra lookups. In MySQL, a composite index with the most selective column first (product_id) followed by the range/order column (order_date) is optimal for queries that filter on product_id and then order or filter by order_date.

What should I do if I get this PCDE question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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