AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company transforms 2 TB of clickstream data stored in Amazon S3 every night by running a PySpark script that is version-controlled in an S3 path. Engineers want to invoke the job from a Jenkins pipeline through API calls, avoid managing any clusters, yet retain access to the Spark UI for detailed job troubleshooting. Which solution best satisfies these requirements?

  • Create an AWS Glue Spark job that references the script in Amazon S3; trigger the job by calling the StartJobRun API from Jenkins; use the AWS Glue Spark UI to debug failed runs.

  • Provision an Amazon EMR cluster on EC2 each night and submit the script as a step by calling the AddJobFlowSteps API; access the Spark UI on the cluster's master node for troubleshooting; terminate the cluster after completion.

  • Package the script in a Docker image and run it with AWS Batch on AWS Fargate; submit the job via the SubmitJob API; inspect the CloudWatch Logs stream for troubleshooting.

  • Load the script into an Amazon Athena Spark notebook and invoke it by calling the StartQueryExecution API; view execution output in Athena's query editor for debugging.

AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
Your Score:
Settings & Objectives
Random Mixed
Questions are selected randomly from all chosen topics, with a preference for those you haven’t seen before. You may see several questions from the same objective or domain in a row.
Rotate by Objective
Questions cycle through each objective or domain in turn, helping you avoid long streaks of questions from the same area. You may see some repeat questions, but the distribution will be more balanced across topics.

Check or uncheck an objective to set which questions you will receive.

Bash, the Crucial Exams Chat Bot
AI Bot