Question 282 of 315
Single answerTerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location, its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US, Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data.
What is the most cost-effective way to run this job?
What is the most cost-effective way to run this job?
AMove all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
BMove all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job
CLaunch a cluster in each region to preprocess and compress the raw data, then move the data into a multi-region bucket and use a Dataproc cluster to finish the job
✓DLaunch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the job
✓
Correct Answer: D
Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the job
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Explanation
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