Google Professional Data Engineer
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Ultimate access to all questions.
Your company is running its first dynamic marketing campaign, aiming to serve varied offers by analyzing real-time data throughout the holiday season. During this 30-day campaign, data scientists are accumulating terabytes of data, which rapidly increases in volume every hour. They utilize Google Cloud Dataflow to preprocess the incoming data and store the necessary feature (signals) data for their machine learning model in Google Cloud Bigtable. The team has observed suboptimal performance regarding reads and writes with their initial load of 10 TB of data. They seek to enhance this performance while minimizing costs. What actions should they take?
Explanation:
The correct answer is A. Redefine the schema by evenly distributing reads and writes across the row space of the table. This is because Google Cloud Bigtable performs best when reads and writes are evenly distributed throughout your table. This helps to avoid performance bottlenecks, which can occur if reads and writes are concentrated on a small number of rows, leading to hotspots. By distributing the load evenly, the workload is spread across all nodes in the cluster, resulting in better performance and minimizing cost.