Google Cloud Professional Data Engineer — Question 320

You have a data pipeline with a Dataflow job that aggregates and writes time series metrics to Bigtable. You notice that data is slow to update in Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the data. Which two actions should you take? (Choose two.)

Answer options

• A. Configure your Dataflow pipeline to use local execution
• B. Increase the maximum number of Dataflow workers by setting maxNumWorkers in PipelineOptions
• C. Increase the number of nodes in the Bigtable cluster
• D. Modify your Dataflow pipeline to use the Flatten transform before writing to Bigtable
• E. Modify your Dataflow pipeline to use the CoGroupByKey transform before writing to Bigtable

Correct answer: B, C

Explanation

Increasing the maximum number of Dataflow workers (Option B) allows for better parallel processing and can significantly speed up data writing. Adding more nodes to the Bigtable cluster (Option C) enhances its capacity and performance, supporting more concurrent users and reducing update times. The other options do not directly address the performance bottlenecks related to writing data to Bigtable.