DEA-C01 practice questions 231–240

1. Question 231 · 313 in bank

   A company runs multiple applications on AWS. The company configured each application to output logs. The company wants to query and visualize the application logs in near real time. Which solution will meet these requirements?

   • AConfigure the applications to output logs to Amazon CloudWatch Logs log groups. Create an Amazon S3 bucket. Create an AWS Lambda function that runs on a schedule to export the required log groups to the S3 bucket. Use Amazon Athena to query the log data in the S3 bucket.
   • BCreate an Amazon OpenSearch Service domain. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an OpenSearch Service subscription filter for each log group to stream the data to OpenSearch. Create the required queries and dashboards in OpenSearch Service to analyze and visualize the data.
   • CConfigure the applications to output logs to Amazon CloudWatch Logs log groups. Use CloudWatch log anomaly detection to query and visualize the log data.
   • DUpdate the application code to send the log data to Amazon QuickSight by using Super-fast, Parallel, In-memory Calculation Engine (SPICE). Create the required analyses and dashboards in QuickSight.

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   Answer: B

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2. Question 232 · 313 in bank

   An ecommerce company processes millions of orders each day. The company uses AWS Glue ETL to collect data from multiple sources, clean the data, and store the data in an Amazon S3 bucket in CSV format by using the S3 Standard storage class. The company uses the stored data to conduct daily analysis. The company wants to optimize costs for data storage and retrieval. Which solution will meet this requirement?

   • ATransition the data to Amazon S3 Glacier Flexible Retrieval.
   • BTransition the data from Amazon S3 to an Amazon Aurora cluster.
   • CConfigure AWS Glue ETL to transform the incoming data to Apache Parquet format.
   • DConfigure AWS Glue ETL to use Amazon EMR to process incoming data in parallel.

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   Answer: C

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3. Question 233 · 313 in bank

   A data engineer is optimizing query performance in Amazon Athena notebooks that use Apache Spark to analyze large datasets that are stored in Amazon S3. The data is partitioned. An AWS Glue crawler updates the partitions. The data engineer wants to minimize the amount of data that is scanned to improve efficiency of Athena queries. Which solution will meet these requirements?

   • AApply partition filters in the queries.
   • BIncrease the frequency of AWS Glue crawler invocations to update the data catalog more often.
   • COrganize the data that is in Amazon S3 by using a nested directory structure.
   • DConfigure Spark to use in-memory caching for frequently accessed data.

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   Answer: A

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4. Question 234 · 313 in bank

   A company manages an Amazon Redshift data warehouse. The data warehouse is in a public subnet inside a custom VPC. A security group allows only traffic from within itself. An ACL is open to all traffic. The company wants to generate several visualizations in Amazon QuickSight for an upcoming sales event. The company will run QuickSight Enterprise edition in a second AWS account inside a public subnet within a second custom VPC. The new public subnet has a security group that allows outbound traffic to the existing Redshift cluster. A data engineer needs to establish connections between Amazon Redshift and QuickSight. QuickSight must refresh dashboards by querying the Redshift cluster. Which solution will meet these requirements?

   • AConfigure the Redshift security group to allow inbound traffic on the Redshift port from the QuickSight security group.
   • BAssign Elastic IP addresses to the QuickSight visualizations. Configure the QuickSight security group to allow inbound traffic on the Redshift port from the Elastic IP addresses.
   • CConfirm that the CIDR ranges of the Redshift VPC and the QuickSight VPC are the same. If CIDR ranges are different, reconfigure one CIDR range to match the other. Establish network peering between the VPCs.
   • DCreate a QuickSight gateway endpoint in the Redshift VPC. Attach an endpoint policy to the gateway endpoint to ensure only specific QuickSight accounts can use the endpoint.

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   Answer: A

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5. Question 235 · 313 in bank

   A data engineer is building a data pipeline. A large data file is uploaded to an Amazon S3 bucket once each day at unpredictable times. An AWS Glue workflow uses hundreds of workers to process the file and load the data into Amazon Redshift. The company wants to process the file as quickly as possible. Which solution will meet these requirements?

   • ACreate an on-demand AWS Glue trigger to start the workflow. Create an AWS Lambda function that runs every 15 minutes to check the S3 bucket for the daily file. Configure the function to start the AWS Glue workflow if the file is present.
   • BCreate an event-based AWS Glue trigger to start the workflow. Configure Amazon S3 to log events to AWS CloudTrail. Create a rule in Amazon EventBridge to forward PutObject events to the AWS Glue trigger.
   • CCreate a scheduled AWS Glue trigger to start the workflow. Create a cron job that runs the AWS Glue job every 15 minutes. Set up the AWS Glue job to check the S3 bucket for the daily file. Configure the job to stop if the file is not present.
   • DCreate an on-demand AWS Glue trigger to start the workflow. Create an AWS Database Migration Service (AWS DMS) migration task. Set the DMS source as the S3 bucket. Set the target endpoint as the AWS Glue workflow.

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   Answer: B

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6. Question 236 · 313 in bank

   A data engineer needs to run a data transformation job whenever a user adds a file to an Amazon S3 bucket. The job will run for less than 1 minute. The job must send the output through an email message to the data engineer. The data engineer expects users to add one file every hour of the day. Which solution will meet these requirements in the MOST operationally efficient way?

   • ACreate a small Amazon EC2 instance that polls the S3 bucket for new files. Run transformation code on a schedule to generate the output. Use operating system commands to send email messages.
   • BRun an Amazon Elastic Container Service (Amazon ECS) task to poll the S3 bucket for new files. Run transformation code on a schedule to generate the output. Use operating system commands to send email messages.
   • CCreate an AWS Lambda function to transform the data. Use Amazon S3 Event Notifications to invoke the Lambda function when a new object is created. Publish the output to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the data engineer’s email account to the topic.
   • DDeploy an Amazon EMR cluster. Use EMR File System (EMRFS) to access the files in the S3 bucket. Run transformation code on a schedule to generate the output to a second S3 bucket. Create an Amazon Simple Notification Service (Amazon SNS) topic. Configure Amazon S3 Event Notifications to notify the topic when a new object is created.

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   Answer: C

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7. Question 237 · 313 in bank

   A company uses Amazon S3 and AWS Glue Data Catalog to manage a data lake that contains contact information for customers. The company uses PySpark and AWS Glue jobs with a DynamicFrame to run a workflow that processes data within the data lake. A data engineer notices that the workflow is generating errors as a result of how customer postal codes are stored in the data lake. Some postal codes include unnecessary numbers or invalid characters. The data engineer needs a solution to address the errors and correct the postal codes in the data lake.

   • ACreate a schema definition for PySpark that matches the format the processing workflow requires for postal codes. Pass the schema to the DynamicFrame during processing.
   • BUse AWS Glue workflow properties to allow job state sharing. Configure the AWS Glue jobs to read values from the postal code column by using the properties from a previously successful run of the jobs.
   • CConfigure the column.push_down_predicate setting and the catalogPartitionPredicate settings for the postal code column in the DynamicFrame.
   • DSet the DynamicFrame additional_options parameter ‘useS3ListImplementation’ to True.

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   Answer: A

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8. Question 238 · 313 in bank

   A data engineer is troubleshooting an AWS Glue workflow that occasionally fails. The engineer determines that the failures are a result of data quality issues. A business reporting team needs to receive an email notification any time the workflow fails in the future. Which solution will meet this requirement?

   • ACreate an Amazon Simple Notification Service (Amazon SNS) FIFO topic. Subscribe the team’s email account to the SNS topic. Create an AWS Lambda function that initiates when the AWS Glue job state changes to FAILED. Set the SNS topic as the target.
   • BCreate an Amazon Simple Notification Service (Amazon SNS) standard topic. Subscribe the team’s email account to the SNS topic. Create an Amazon EventBridge rule that triggers when the AWS Glue job state changes to FAILED. Set the SNS topic as the target.
   • CCreate an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Subscribe the team’s email account to the SQS queue. Create an AWS Config rule that triggers when the AWS Glue job state changes to FAILED. Set the SQS queue as the target.
   • DCreate an Amazon Simple Queue Service (Amazon SQS) standard queue. Subscribe the team’s email account to the SQS queue. Create an Amazon EventBridge rule that triggers when the AWS Glue job state changes to FAILESet the SQS queue as the target.

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   Answer: B

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9. Question 239 · 313 in bank

   A company uses AWS Glue jobs to implement several data pipelines. The pipelines are critical to the company. The company needs to implement a monitoring mechanism that will alert stakeholders if the pipelines fail. Which solution will meet these requirements with the LEAST operational overhead?

   • ACreate an Amazon EventBridge rule to match AWS Glue job failure events. Configure the rule to target an AWS Lambda function to process events. Configure the function to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.
   • BConfigure an Amazon CloudWatch Logs log group for the AWS Glue jobs. Create an Amazon EventBridge rule to match new log creation events in the log group. Configure the rule to target an AWS Lambda function that reads the logs and sends notifications to an Amazon Simple Notification Service (Amazon SNS) topic if AWS Glue job failure logs are present.
   • CCreate an Amazon EventBridge rule to match AWS Glue job failure events. Define an Amazon CloudWatch metric based on the EventBridge rule. Set up a CloudWatch alarm based on the metric to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.
   • DConfigure an Amazon CloudWatch Logs log group for the AWS Glue jobs. Create an Amazon EventBridge rule to match new log creation events in the log group. Configure the rule to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.

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   Answer: C

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10. Question 240 · 313 in bank

    A company uses AWS Glue Apache Spark jobs to handle extract, transform, and load (ETL) workloads. The company has enabled logging and monitoring for all AWS Glue jobs. One of the AWS Glue jobs begins to fail. A data engineer investigates the error and wants to examine metrics for all individual stages within the job. How can the data engineer access the stage metrics?

    • AExamine the AWS Glue job and stage details in the Spark UI.
    • BExamine the AWS Glue job and stage metrics in Amazon CloudWatch.
    • CExamine the AWS Glue job and stage logs in AWS CloudTrail logs.
    • DExamine the AWS Glue job and stage details by using the run insights feature on the job.

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    Answer: A

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DEA-C01 practice, question 231. 313 questions available.