Google Professional Data Engineer Question 70
Single answerGoogle Cloud PlatformYou are designing a data pipeline on Google Cloud and need to configure both the data source and sink for a batch processing job. The pipeline reads structured data from a transactional database and writes the aggregated results to a BigQuery table. Which of the following data source and sink configurations would be most appropriate for this use case?
- A
Use Cloud SQL as the data source and BigQuery as the data sink.
- B
Use Cloud Spanner as the data source and Cloud Storage as the data sink.
- C
Use Cloud Storage as the data source and Bigtable as the data sink.
- D
Use Pub/Sub as the data source and Dataflow as the data sink.
Show answer and explanation
Correct answer: A
Explanation
The correct choice is to use Cloud SQL as the data source and BigQuery as the data sink. Cloud SQL is ideal for ingesting structured, transactional data, while BigQuery is optimized for storing and analyzing aggregated results. The other options either use inappropriate services for the scenario or are mismatched for the use case.
- A. Correct.
This is the correct configuration. Cloud SQL is a fully managed relational database suitable for transactional workloads, and BigQuery is a serverless data warehouse optimized for analytics use cases such as aggregations.
- B. Incorrect.
This is incorrect because Cloud Spanner is designed for horizontally scalable, globally distributed databases, and Cloud Storage is better suited for unstructured data rather than processing and querying structured, aggregated results.
- C. Incorrect.
This is incorrect because Cloud Storage is typically used for unstructured data, while Bigtable is optimized for high-throughput, low-latency workloads rather than analytics.
- D. Incorrect.
This is incorrect because Pub/Sub is a messaging service and not a database; it is unsuitable as a source for structured, transactional data. Similarly, Dataflow is a data processing service, not a storage sink.