- A
Increase the Cloud SQL instance memory and CPU before the job starts.
Why wrong: Scaling up is not a precise solution and adds cost.
- B
Break the batch job into smaller transactions with a delay between batches.
Smaller transactions release locks faster and reduce contention.
- C
Disable binary logging during the batch window.
Why wrong: Disabling binary logging would prevent point-in-time recovery.
- D
Move batch reads to a read replica.
Why wrong: This helps with reads, but the batch job is performing updates.
Question 923 of 1,000
Cloud SQL MySQL Batch Updates Performance Tuning
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.
Your organization uses Cloud SQL for MySQL as the backend for a content management system. The Operations team reports that the database performance degrades every weekday morning at 9 AM, coinciding with a batch job that updates thousands of rows. You need to minimize the impact on end users. What is the best approach?
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.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Quick Answer
The answer is to break the batch job into smaller transactions with a delay between batches. This approach directly addresses Cloud SQL MySQL batch updates performance degradation by reducing lock contention; when a single large transaction holds row-level locks for an extended period, it blocks concurrent user queries, whereas smaller, spaced-out transactions allow the database engine to release locks frequently, improving concurrency and minimizing impact on end users. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of transaction management and lock escalation under write-heavy workloads—a common trap is assuming scaling up the instance or adding read replicas will solve write contention, but replicas only offload reads and larger instances mask rather than fix the root cause. Remember the memory tip: “Small batches, short locks; big batches, big blocks.”
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
✓
Break the batch job into smaller transactions with a delay between batches.
Breaking the batch job into smaller transactions with a delay between batches reduces lock contention and transaction log pressure on the primary Cloud SQL instance. This prevents a single large transaction from blocking concurrent user queries, thereby minimizing performance degradation for end users during the batch window.
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.
- ✗
Increase the Cloud SQL instance memory and CPU before the job starts.
Why it's wrong here
Scaling up is not a precise solution and adds cost.
- ✓
Break the batch job into smaller transactions with a delay between batches.
Why this is correct
Smaller transactions release locks faster and reduce contention.
Clue confirmation
The clue words "best", "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Disable binary logging during the batch window.
Why it's wrong here
Disabling binary logging would prevent point-in-time recovery.
- ✗
Move batch reads to a read replica.
Why it's wrong here
This helps with reads, but the batch job is performing updates.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume scaling up resources (Option A) is the universal fix for performance issues, but the PCDE exam tests understanding that write-heavy batch jobs on Cloud SQL require transaction management and concurrency control, not just vertical scaling.
Detailed technical explanation
How to think about this question
In MySQL, large transactions hold row-level locks and fill the InnoDB redo log (ib_logfile) and undo tablespace, which can cause the purge thread to lag and block concurrent reads. By splitting the batch into smaller transactions (e.g., 500 rows per commit) with a short delay (e.g., 100ms), each transaction commits quickly, releasing locks and allowing the redo log to flush incrementally, which reduces the chance of a 'lock wait timeout' for user queries. This approach aligns with MySQL best practices for bulk DML operations.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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: Break the batch job into smaller transactions with a delay between batches. — Breaking the batch job into smaller transactions with a delay between batches reduces lock contention and transaction log pressure on the primary Cloud SQL instance. This prevents a single large transaction from blocking concurrent user queries, thereby minimizing performance degradation for end users during the batch window.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best", "minimum / minimize". 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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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