An operations team notices that a few AWS Glue jobs for a given ETL application are failing. The AWS Glue jobs read a large number of small JSON files from an
Amazon S3 bucket and write the data to a different S3 bucket in Apache Parquet format with no major transformations. Upon initial investigation, a data engineer notices the following error message in the History tab on the AWS Glue console: `Command Failed with Exit Code 1.`
Upon further investigation, the data engineer notices that the driver memory profile of the failed jobs crosses the safe threshold of 50% usage quickly and reaches
90`"95% soon after. The average memory usage across all executors continues to be less than 4%.
The data engineer also notices the following error while examining the related Amazon CloudWatch Logs.
 
What should the data engineer do to solve the failure in the MOST cost-effective way?

A. Change the worker type from Standard to G.2X.

B. Modify the AWS Glue ETL code to use the 'groupFiles': 'inPartition' feature.

C. Increase the fetch size setting by using AWS Glue dynamics frame.

D. Modify maximum capacity to increase the total maximum data processing units (DPUs) used.








 

Suggested Answer: D

Community Answer: B




This question is in DAS-C01 AWS Certified Data Analytics – Specialty Exam
For getting AWS Certified Data Analytics – Specialty Certificate



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