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Question #161 Topic 1
You migrated a data backend for an application that serves 10 PB of historical product data for analytics. Only the last known state for a product, which is about 10 GB of data, needs to be served through an API to the other applications. You need to choose a cost-effective persistent storage solution that can accommodate the analytics requirements and the API performance of up to 1000 queries per second (QPS) with less than 1 second latency. What should you do?
A
1. Store the historical data in BigQuery for analytics.2. Use a materialized view to precompute the last state of a product.3. Serve the last state data directly from BigQuery to the API.
B
1. Store the products as a collection in Firestore with each product having a set of historical changes.2. Use simple and compound queries for analytics.3. Serve the last state data directly from Firestore to the API.
C
1. Store the historical data in Cloud SQL for analytics.2. In a separate table, store the last state of the product after every product change.3. Serve the last state data directly from Cloud SQL to the API.
D
1. Store the historical data in BigQuery for analytics.2. In a Cloud SQL table, store the last state of the product after every product change.3. Serve the last state data directly from Cloud SQL to the API.