AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ259

Data Operations and Support

A company uses an Amazon QuickSight dashboard to track usage of one of its applications. The company uses AWS Glue jobs to process data for the dashboard and stores the data in a single Amazon S3 bucket. The company adds new data each day.

A data engineer finds that dashboard queries are slowing over time. The data engineer identifies long-running AWS Glue jobs as the cause of the slower queries.

Which actions should the data engineer take to improve AWS Glue job performance?

Choose two
  • A Partition the data that is in the S3 bucket. Organize the data by year, month, and day.
  • B Increase the AWS Glue instance size by scaling up the worker type.
  • C Convert the AWS Glue schema to the DynamicFrame schema class.
  • D Adjust AWS Glue job scheduling frequency so the jobs run half as many times each day.
  • E Modify the IAM role that grants access to AWS glue to grant access to all S3 features.
Explanation

Partitioning S3 data by year, month, and day enables jobs to read only the relevant partitions rather than scanning an ever-growing dataset. Using a larger AWS Glue worker type vertically scales the workers with additional compute, memory, and storage, which can improve performance for intensive data integration workloads.

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