- A
Increase the executor memory to 16 GB.
Why wrong: Memory is likely not the bottleneck; latency is due to insufficient parallelism.
- B
Increase the number of shards in the Kinesis stream to 10 and increase the number of core nodes to 10.
More shards increase parallelism, and more nodes allow more concurrent processing.
- C
Use a larger instance type for the core nodes, such as r5.4xlarge.
Why wrong: Larger instances improve per-node throughput but do not increase parallelism if the shard count is the limiting factor.
- D
Change the output format from Parquet to CSV to reduce write time.
Why wrong: CSV is larger and slower to write, worsening latency.
Question 669 of 1,755
Spark Structured Streaming with Kinesis: Increase Parallelism on EMR
This MLS-C01 practice question tests your understanding of data engineering. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 engineering team is using Apache Spark on Amazon EMR to process streaming data from Amazon Kinesis Data Streams. The Spark application uses structured streaming to read from Kinesis, perform transformations, and write to Amazon S3 in Parquet format. The team notices that the application is falling behind and the processing latency is increasing. The Kinesis stream has 5 shards, and the EMR cluster has 5 core nodes of type r5.xlarge. The Spark application is configured with 5 executors, each with 2 cores and 8 GB memory. The team wants to reduce processing latency. Which change would be most effective?
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
✓
Increase the number of shards in the Kinesis stream to 10 and increase the number of core nodes to 10.
The number of shards (5) matches the number of executors (5), but each shard can be processed by a single executor. To increase parallelism, the team should increase the number of shards in the Kinesis stream and correspondingly increase the number of executors or cores. Alternatively, they can increase the number of cores per executor to allow parallel processing of multiple shards per executor.
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 executor memory to 16 GB.
Why it's wrong here
Memory is likely not the bottleneck; latency is due to insufficient parallelism.
- ✓
Increase the number of shards in the Kinesis stream to 10 and increase the number of core nodes to 10.
Why this is correct
More shards increase parallelism, and more nodes allow more concurrent processing.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a larger instance type for the core nodes, such as r5.4xlarge.
Why it's wrong here
Larger instances improve per-node throughput but do not increase parallelism if the shard count is the limiting factor.
- ✗
Change the output format from Parquet to CSV to reduce write time.
Why it's wrong here
CSV is larger and slower to write, worsening latency.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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: Increase the number of shards in the Kinesis stream to 10 and increase the number of core nodes to 10. — The number of shards (5) matches the number of executors (5), but each shard can be processed by a single executor. To increase parallelism, the team should increase the number of shards in the Kinesis stream and correspondingly increase the number of executors or cores. Alternatively, they can increase the number of cores per executor to allow parallel processing of multiple shards per executor.
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.
About these practice questions
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Last reviewed: Jun 20, 2026
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.
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