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MLS-C01 · Question #33

MLS-C01 Question #33: Real Exam Question with Answer & Explanation

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Data Engineering

Question

A Data Scientist needs to migrate an existing on-premises ETL process to the cloud. The current process runs at regular time intervals and uses PySpark to combine and format multiple large data sources into a single consolidated output for downstream processing. The Data Scientist has been given the following requirements to the cloud solution: - Combine multiple data sources. - Reuse existing PySpark logic. - Run the solution on the existing schedule. - Minimize the number of servers that will need to be managed. Which architecture should the Data Scientist use to build this solution?

Options

  • AWrite the raw data to Amazon S3. Schedule an AWS Lambda function to submit a Spark step to a
  • BWrite the raw data to Amazon S3. Create an AWS Glue ETL job to perform the ETL processing
  • CWrite the raw data to Amazon S3. Schedule an AWS Lambda function to run on the existing
  • DUse Amazon Kinesis Data Analytics to stream the input data and perform real-time SQL queries

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Topics

#AWS Glue#ETL#PySpark#Serverless Data Processing
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