Question 1,185 of 1,755
Data EngineeringhardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to aggregate multiple records into a single file in a DynamoDB table, then periodically write the aggregated data to S3. This approach reduces the number of S3 PUT requests by buffering records in DynamoDB and writing them in batches, directly addressing the high latency caused by processing each record individually. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of optimizing S3 writes for streaming data pipelines, where Lambda functions often create too many small objects. A common trap is to increase Lambda memory or use multipart uploads, but those don’t reduce the PUT request count for many small files. Remember the key insight: for high-frequency writes, buffer first, then batch—think “DynamoDB as a staging buffer” to avoid S3 write throttling and cost spikes.

MLS-C01 Data Engineering Practice Question

This MLS-C01 practice question tests your understanding of data engineering. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.

A data engineer is building a data pipeline that uses AWS Lambda to process records from an SQS queue and write results to an S3 bucket. The Lambda function processes each record individually and writes a separate file to S3. The team notices high latency and wants to reduce the number of S3 PUT requests to improve performance and reduce cost. Which approach should the data engineer take?

Question 1hardmultiple choice
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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

Aggregate multiple records into a single file in a DynamoDB table, then periodically write the aggregated data to S3.

Option A is correct because buffering records in a DynamoDB table and then using a batch write to S3 reduces the number of PUT requests. Option B (increasing Lambda memory) does not reduce S3 PUT count. Option C (S3 batch operations) is for existing objects, not for incoming data. Option D (multipart upload) is for large objects, not for many small objects.

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.

  • Use S3 multipart upload for each record to improve throughput.

    Why it's wrong here

    Multipart upload is for large objects; for small records it adds overhead.

  • Increase the Lambda function's memory allocation to improve processing speed.

    Why it's wrong here

    More memory may speed up processing but does not reduce the number of S3 PUT requests.

  • Use S3 Batch Operations to process the records in batches.

    Why it's wrong here

    S3 Batch Operations are for batch processing of existing objects, not for incoming streaming data.

  • Aggregate multiple records into a single file in a DynamoDB table, then periodically write the aggregated data to S3.

    Why this is correct

    Aggregation reduces the number of S3 PUT requests by writing larger files less frequently.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

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.
  • Use explanations to understand the rule behind the answer.

TExam Day Tips

  • Underline the problem statement mentally.
  • 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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

What to study next

Got this wrong? Here's your next step.

Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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FAQ

Questions learners often ask

What does this MLS-C01 question test?

Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Aggregate multiple records into a single file in a DynamoDB table, then periodically write the aggregated data to S3. — Option A is correct because buffering records in a DynamoDB table and then using a batch write to S3 reduces the number of PUT requests. Option B (increasing Lambda memory) does not reduce S3 PUT count. Option C (S3 batch operations) is for existing objects, not for incoming data. Option D (multipart upload) is for large objects, not for many small objects.

What should I do if I get this MLS-C01 question wrong?

Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 20, 2026

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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.