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Answer: Use Cloud Pub/Sub for message ingestion and Cloud Dataflow for streaming analysis.
The correct answer is D. This is because Google Cloud Dataflow is a serverless, fully-managed service for stream and batch processing that can automatically scale to handle increased loads. Meanwhile, Cloud Pub/Sub is designed for message ingestion with support for 'at least once' delivery. Together, they ensure that messages are processed at least once and can handle the requirement for ordered processing within specific time windows.
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You have been given the responsibility of designing a data processing pipeline for a system that experiences fluctuating loads. It is essential that this pipeline can automatically adjust its capacity to handle increased loads efficiently. Additionally, the system must ensure that each message is processed at least once, and messages should remain ordered within 1-hour time windows. What approach would you take to design this solution?
A
Use Apache Kafka for message ingestion and use Cloud Dataproc for streaming analysis.
B
Use Apache Kafka for message ingestion and use Cloud Dataflow for streaming analysis.
C
Use Cloud Pub/Sub for message ingestion and Cloud Dataproc for streaming analysis.
D
Use Cloud Pub/Sub for message ingestion and Cloud Dataflow for streaming analysis.