Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 131 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01

Question #: 131
Topic #: 1

[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A company currently uses a provisioned Amazon EMR cluster that includes general purpose Amazon EC2 instances. The EMR cluster uses EMR managed scaling between one to five task nodes for the company’s long-running Apache Spark extract, transform, and load (ETL) job. The company runs the ETL job every day.

When the company runs the ETL job, the EMR cluster quickly scales up to five nodes. The EMR cluster often reaches maximum CPU usage, but the memory usage remains under 30%.

The company wants to modify the EMR cluster configuration to reduce the EMR costs to run the daily ETL job.

Which solution will meet these requirements MOST cost-effectively?

A. Increase the maximum number of task nodes for EMR managed scaling to 10.
B. Change the task node type from general purpose EC2 instances to memory optimized EC2 instances.
C. Switch the task node type from general purpose Re instances to compute optimized EC2 instances.
D. Reduce the scaling cooldown period for the provisioned EMR cluster.

Show Suggested Answer

Suggested Answer: C 🗳️

by Shanmahi at Aug. 6, 2024, 7:33 a.m.

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Comments

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Tester_TKK

1 month, 3 weeks ago

Selected Answer: C

Your Spark ETL is clearly CPU‑bound (100% CPU, <30% memory), so you’ll get better price‑performance by trading in excess RAM for extra vCPUs rather than adding nodes, upsizing memory, or tweaking cooldowns.

upvoted 1 times

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AgboolaKun

7 months, 1 week ago

Selected Answer: C

C is the correct answer. Here is why: Compute optimized Amazon EC2 instances are less expensive per CPU core than general purpose instances, making them the better choice for workloads that require high processing power, as they prioritize CPU cores over memory, resulting in a lower cost per vCPU compared to general purpose instances.

upvoted 1 times

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antun3ra

10 months, 1 week ago

Selected Answer: C

current situation shows that the EMR cluster is reaching maximum CPU usage, but memory usage remains low (under 30%). This indicates that the workload is CPU-bound rather than memory-bound.

upvoted 4 times

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Shanmahi

10 months, 2 weeks ago

Selected Answer: C

Since the ETL job reaches maximum CPU usage but not memory usage, switching from general-purpose instances to compute-optimized instances (such as C5 or C6g instances) can provide better performance per dollar for CPU-bound workloads.

upvoted 4 times

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