MLS-C01 · Question #338
A data engineer wants to perform exploratory data analysis (EDA) on a petabyte of data. The data engineer does not want to manage compute resources and wants to pay only for queries that are run…
The correct answer is B. Use Apache Spark from within Amazon SageMaker. Sagemaker is serverless and SageMaker Processing allows you to run Spark jobs from a Jupyter notebook using Python. You only pay for resources used during processing jobs.
Question
A data engineer wants to perform exploratory data analysis (EDA) on a petabyte of data. The data engineer does not want to manage compute resources and wants to pay only for queries that are run. The data engineer must write the analysis by using Python from a Jupyter notebook. Which solution will meet these requirements?
Options
- AUse Apache Spark from within Amazon Athena.
- BUse Apache Spark from within Amazon SageMaker.
- CUse Apache Spark from within an Amazon EMR cluster.
- DUse Apache Spark through an integration with Amazon Redshift.
How the community answered
(42 responses)- A10% (4)
- B83% (35)
- C2% (1)
- D5% (2)
Explanation
Sagemaker is serverless and SageMaker Processing allows you to run Spark jobs from a Jupyter notebook using Python. You only pay for resources used during processing jobs.
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