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Question 32/70
For this question, refer to the TerramEarth case study.
TerramEarth'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?
TerramEarth'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?
Correct Answer: A
- Question List (70q)
- 2 commentQuestion 1: For this question, refer to the JencoMart case study. JencoM...
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- 10 commentQuestion 3: Your application needs to process credit card transactions. ...
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- 5 commentQuestion 20: For this question, refer to the TerramEarth case study. To s...
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- 3 commentQuestion 22: For this question, refer to the JencoMart case study. JencoM...
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- 1 commentQuestion 31: For this question, refer to the Mountkirk Games case study. ...
- 5 commentQuestion 32: For this question, refer to the TerramEarth case study. Terr...
- 6 commentQuestion 33: For this question, refer to the TerramEarth case study. Terr...
- 5 commentQuestion 34: For this question, refer to the Dress4Win case study. Dress4...
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- Question 36: You need to reduce the number of unplanned rollbacks of erro...
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- 1 commentQuestion 39: Your company plans to migrate a multi-petabyte data set to t...
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Recent Comments (The most recent comments are at the top.)
Answer is A. It has to be cost-effective. Compress and pre-process (less data to move) seem to be a good option here. On top of that, why would you need a multi-regional bucket? Multi-regional bucket is only if you need to distribute data across geographic areas, it is not the case here. You have to move the pre-processed data to a bucket to centrally process. The data in that latter bucket will never be retrieved from different areas. Multi-regional is a more expensive than regional.
Regional bucket offers higher bandwith so improves the performance, this excludes C, so answer is A
Why not C?
I mean D
B: Use a single zone when low-latency and low-cost is most important