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Answer: Ingest the data into Cloud Bigtable. Create a row key based on the event timestamp.
The correct answer is D, 'Ingest the data into Cloud Bigtable. Create a row key based on the event timestamp.' This is because Cloud Bigtable is designed to handle high throughput, such as thousands of events per hour per device, and provides consistent, atomic operations. It is also well-suited for time-series data, which fits the requirement of retrieving data based on the time of the event. Options A and B are not suitable as they do not provide the necessary atomic operations and high throughput. Option C, while it can manage high throughput to some extent, is not as optimized for this specific use case as Cloud Bigtable.
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Your company's primary business is large-scale construction equipment rentals. Each piece of equipment has multiple sensors that transmit event data every few seconds, which includes metrics like engine status, distance traveled, and fuel level. Billing customers is based on the consumption data monitored by these sensors. You anticipate receiving thousands of events per hour for each device and require consistent data retrieval based on the event timestamp. Ensuring atomic storage and retrieval of each individual signal is crucial. What action should you take?
A
Create a file in Cloud Storage per device and append new data to that file.
B
Create a file in Cloud Filestore per device and append new data to that file.
C
Ingest the data into Datastore. Store data in an entity group based on the device.
D
Ingest the data into Cloud Bigtable. Create a row key based on the event timestamp.