MLA-C01 · Question #96
MLA-C01 Question #96: Real Exam Question with Answer & Explanation
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Question
An ML engineer needs to merge and transform data from two sources to retrain an existing ML model. One data source consists of .csv files that are stored in an Amazon S3 bucket. Each .csv file consists of millions of records. The other data source is an Amazon Aurora DB cluster. The result of the merge process must be written to a second S3 bucket. The ML engineer needs to perform this merge-and-transform task every week. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ACreate a transient Amazon EMR cluster every week. Use the cluster to run an Apache Spark job
- BCreate a weekly AWS Glue job that uses the Apache Spark engine. Use DynamicFrame native
- CCreate an AWS Lambda function that runs Apache Spark code every week to merge and
- DCreate an AWS Batch job that runs Apache Spark code on Amazon EC2 instances every week.
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