Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A company's nightly AWS Glue 3.0 Spark job reads 3 TB of Parquet data from Amazon S3 and loads it into an Amazon Redshift table. The job used to finish in 40 minutes, but the most recent runs take more than 2 hours, and several tasks stay in the READY state for an extended time. To quickly identify stage bottlenecks such as partition skew or insufficient executor memory without increasing cost, which action should a data engineer perform first?

  • Increase the job's maximum DPUs and enable continuous logging to Amazon CloudWatch Logs.

  • Configure the CloudWatch log group for the job to stream to Amazon S3 and query the logs with Amazon Athena.

  • Open the job's Spark UI from the AWS Glue console and review stage and executor metrics in the Spark History Server.

  • Enable job bookmarks so the job can skip partitions that have already been processed.

AWS Certified Data Engineer Associate DEA-C01
Data Operations and Support
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