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.
In Cloud Bigtable, a table has a high ratio of garbage collection (GC) that causes performance degradation during compaction. What is the best practice to monitor and optimize this?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Use the bigtableadmin API to view table stats
Why wrong: Table stats do not provide real-time GC metrics.
Compact the table manually
Why wrong: Manual compaction can cause further performance issues.
Use Cloud Monitoring to track garbage collection count and adjust GC settings
Monitoring GC count and tuning GC settings can reduce compaction overhead.
Increase node count
Why wrong: More nodes may spread load but do not reduce GC ratio.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use Cloud Monitoring to track garbage collection count and adjust GC settings
Option C is correct because Cloud Monitoring provides the metrics (e.g., 'bigtable.googleapis.com/table/garbage_collection_count') needed to track GC activity, and adjusting GC settings (e.g., column family max versions or TTL) directly reduces the compaction overhead caused by excessive stale data. This aligns with best practices for proactive performance optimization in Cloud Bigtable.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Use the bigtableadmin API to view table stats
Why it's wrong here
Table stats do not provide real-time GC metrics.
Compact the table manually
Why it's wrong here
Manual compaction can cause further performance issues.
Use Cloud Monitoring to track garbage collection count and adjust GC settings
Why this is correct
Monitoring GC count and tuning GC settings can reduce compaction overhead.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Increase node count
Why it's wrong here
More nodes may spread load but do not reduce GC ratio.
Common exam traps
The trap here is that candidates confuse operational scaling (adding nodes) with tuning data retention policies, failing to recognize that GC-related compaction degradation is a schema design issue, not a capacity issue.
Detailed technical explanation
Cloud Bigtable uses a log-structured merge-tree (LSM-tree) architecture where compactions merge SSTables and remove deleted or expired cells based on GC settings (max versions and TTL). A high GC ratio means many cells are being dropped during compaction, which increases I/O and CPU overhead; monitoring the 'garbage_collection_count' metric helps identify column families with overly aggressive retention policies, allowing you to tune TTL or max versions to reduce compaction strain.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Monitor and optimize database performance — study guide chapter
Learn the concepts, then practise the questions
Monitor and optimize database performance practice questions
Targeted practice on this topic area only
All PCDE questions
503 questions across all exam domains
Google Professional Cloud Database Engineer study guide
Full concept coverage aligned to exam objectives
PCDE practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise PCDE questions linked to Plan and manage database infrastructure.
Practise PCDE questions linked to Define data structures and implement SQL for Business Intelligence.
Practise PCDE questions linked to Design and implement database schemas.
Practise PCDE questions linked to Monitor and optimize database performance.
Practise PCDE questions linked to PCDE fundamentals.
Practise PCDE questions linked to PCDE scenario.
Practise PCDE questions linked to PCDE troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
The correct answer is: Use Cloud Monitoring to track garbage collection count and adjust GC settings — Option C is correct because Cloud Monitoring provides the metrics (e.g., 'bigtable.googleapis.com/table/garbage_collection_count') needed to track GC activity, and adjusting GC settings (e.g., column family max versions or TTL) directly reduces the compaction overhead caused by excessive stale data. This aligns with best practices for proactive performance optimization in Cloud Bigtable.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
Last reviewed: Jun 25, 2026
This PCDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCDE exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.