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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q130-Q135):

NEW QUESTION # 130
A company currently uses a provisioned Amazon EMR cluster that includes general purpose Amazon EC2 instances. The EMR cluster uses EMR managed scaling betweenone 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. Switch the task node type from general purpose EC2 instances to compute optimized EC2 instances.
B. Increase the maximum number of task nodes for EMR managed scaling to 10.
C. Change the task node type from general purpose EC2 instances to memory optimized EC2 instances.
D. Reduce the scaling cooldown period for the provisioned EMR cluster.

Answer: A

Explanation:
The company's Apache Spark ETL job on Amazon EMR uses high CPU but low memory, meaning that compute-optimized EC2 instanceswould be the most cost-effective choice. These instances are designed for high-performance compute applications, where CPU usage is high, but memory needs are minimal, which is exactly the case here.
* Compute Optimized Instances:
* Compute-optimized instances, such as the C5 series, provide a higher ratio of CPU to memory, which is more suitable for jobs with high CPU usage and relatively low memory consumption.
* Switching from general-purpose EC2 instances to compute-optimized instances canreduce costs while improving performance, as these instances are optimized for workloads like Spark jobs that perform a lot of computation.
Reference:Amazon EC2 Compute Optimized Instances
Managed Scaling: The EMR cluster's scaling is currently managed between 1 and 5 nodes, so changing the instance type will leverage the current scaling strategy but optimize it for the workload.
Alternatives Considered:
A (Increase task nodes to 10): Increasing the number of task nodes would increase costs without necessarily improving performance. Since memory usageis low, the bottleneck is more likely the CPU, which compute- optimized instances can handle better.
B (Memory optimized instances): Memory-optimized instances are not suitable since the current job is CPU- bound, and memory usage remains low (under 30%).
D (Reduce scaling cooldown): This could marginally improve scaling speed but does not address the need for cost optimization and improved CPU performance.
References:
Amazon EMR Cluster Optimization
Compute Optimized EC2 Instances

NEW QUESTION # 131
A data engineer is launching an Amazon EMR duster. The data that the data engineer needs to load into the new cluster is currently in an Amazon S3 bucket. The data engineer needs to ensure that data is encrypted both at rest and in transit.
The data that is in the S3 bucket is encrypted by an AWS Key Management Service (AWS KMS) key. The data engineer has an Amazon S3 path that has a Privacy Enhanced Mail (PEM) file.
Which solution will meet these requirements?

A. Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for local disk encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption. Use the security configuration during EMR cluster creation.
B. Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption. Use the security configuration during EMR cluster creation.
C. Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Create a second security configuration. Specify the Amazon S3 path of the PEM file for in-transit encryption. Create the EMR cluster, and attach both security configurations to the cluster.
D. Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption.Create the EMR cluster, and attach the security configuration to the cluster.

Answer: B

Explanation:
The data engineer needs to ensure that the data in an Amazon EMR cluster is encrypted both at rest and in transit. The data in Amazon S3 is already encrypted using an AWS KMS key. To meet the requirements, the most suitable solution is to create an EMR security configuration that specifies the correct KMS key for at- rest encryption and use the PEM file for in-transit encryption.
* Option C: Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in- transit encryption. Use the security configuration during EMR cluster creation.This option configures encryption for both data at rest (using KMS keys) and data in transit (using the PEM file for SSL/TLS encryption). This approach ensures that data is fully protected during storage and transfer.
Options A, B, and D either involve creating unnecessary additional security configurations or make inaccurate assumptions about the way encryption configurations are attached.
References:
* Amazon EMR Security Configuration
* Amazon S3 Encryption

NEW QUESTION # 132
A transportation company wants to track vehicle movements by capturing geolocation records. The records are 10 bytes in size. The company receives up to 10,000 records every second. Data transmission delays of a few minutes are acceptable because of unreliable network conditions.
The transportation company wants to use Amazon Kinesis Data Streams to ingest the geolocation data. The company needs a reliable mechanism to send data to Kinesis Data Streams. The company needs to maximize the throughput efficiency of the Kinesis shards.
Which solution will meet these requirements in the MOST operationally efficient way?

A. Kinesis Producer Library (KPL)
B. Kinesis SDK
C. Kinesis Agent
D. Amazon Data Firehose

Answer: A

Explanation:
Problem Analysis:
The company ingests geolocation records (10 bytes each) at 10,000 records per second into Kinesis Data Streams.
Data transmission delays are acceptable, but the solution must maximize throughput efficiency.
Key Considerations:
The Kinesis Producer Library (KPL) batches records and uses aggregation to optimize shard throughput.
Efficiently handles high-throughput scenarios with minimal operational overhead.
Solution Analysis:
Option A: Kinesis Agent
Designed for file-based ingestion; not optimized for geolocation records.
Option B: KPL
Aggregates records into larger payloads, significantly improving shard throughput.
Suitable for applications generating small, high-frequency records.
Option C: Kinesis Firehose
Firehose is for delivery to destinations like S3 or Redshift and is not optimized for direct ingestion to Kinesis Data Streams.
Option D: Kinesis SDK
The SDK lacks advanced features like aggregation, resulting in lower throughput efficiency.
Final Recommendation:
Use Kinesis Producer Library (KPL) for its built-in aggregation and batching capabilities.
Reference:
Kinesis Producer Library (KPL) Overview

NEW QUESTION # 133
A data engineer needs to create an empty copy of an existing table in Amazon Athena to perform data processing tasks. The existing table in Athena contains 1,000 rows.
Which query will meet this requirement?

A. CREATE TABLE new_table AS SELECT * FROM old_table WITH NO DATA;
B. CREATE TABLE new_table AS SELECT * FROM old_table WHERE 1=1;
C. CREATE TABLE new_table AS SELECT * FROM old_table;
D. CREATE TABLE new_table LIKE old_table;

Answer: A

Explanation:
In Amazon Athena, you can use CREATE TABLE AS SELECT with WITH NO DATA to create an empty copy of an existing table's schema:
"The query CREATE TABLE new_table AS SELECT * FROM old_table WITH NO DATA; creates a new table with the same schema but without copying over the data."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf This is the most efficient way to create an empty version of the existing table.

NEW QUESTION # 134
A company has a data warehouse in Amazon Redshift. To comply with security regulations, the company needs to log and store all user activities and connection activities for the data warehouse.
Which solution will meet these requirements?

A. Create an Amazon Elastic Block Store (Amazon EBS) volume. Enable logging for the Amazon Redshift cluster. Write the logs to the EBS volume.
B. Create an Amazon Aurora MySQL database. Enable logging for the Amazon Redshift cluster. Write the logs to a table in the Aurora MySQL database.
C. Create an Amazon Elastic File System (Amazon EFS) file system. Enable logging for the Amazon Redshift cluster. Write logs to the EFS file system.
D. Create an Amazon S3 bucket. Enable logging for the Amazon Redshift cluster. Specify the S3 bucket in the logging configuration to store the logs.

Answer: D

Explanation:
* Problem Analysis:
* The company must log alluser activitiesandconnection activitiesin Amazon Redshift for security compliance.
* Key Considerations:
* Redshift supportsaudit logging, which can be configured to write logs to an S3 bucket.
* S3 provides durable, scalable, and cost-effective storage for logs.
* Solution Analysis:
* Option A: S3 for Logging
* Standard approach for storing Redshift logs.
* Easy to set up and manage with minimal cost.
* Option B: Amazon EFS
* EFS is unnecessary for this use case and less cost-efficient than S3.
* Option C: Aurora MySQL
* Using a database to store logs increases complexity and cost.
* Option D: EBS Volume
* EBS is not a scalable option for log storage compared to S3.
* Final Recommendation:
* EnableRedshift audit loggingand specify anS3 bucketas the destination.
:
Amazon Redshift Audit Logging
Storing Logs in Amazon S3

NEW QUESTION # 135
......

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Reliable Data-Engineer-Associate Exam Papers, Data-Engineer-Associate Study Demo

Data-Engineer-Associate Study Demo | Data-Engineer-Associate Exam Actual Tests

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q130-Q135):

Reliable Data-Engineer-Associate Exam Papers & SurePassExams - Leader in Certification Exam Materials & Data-Engineer-Associate: AWS Certified Data Engineer - Associate (DEA-C01)

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