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Answer: Set up Cloud Pub/Sub to capture user activity data in real-time and use a Dataflow streaming job to process and ingest the data into BigQuery.
To ensure real-time ingestion of user activity data into BigQuery, the most efficient and scalable solution involves using Cloud Pub/Sub in conjunction with a Dataflow streaming job. Cloud Pub/Sub acts as a real-time messaging service to capture the data from the mobile applications, while Dataflow processes and streams this data into BigQuery. This approach is scalable, cost-effective, and capable of handling high volumes of data with low latency. Option B is more complex and resource-intensive for this specific need. Option C is not feasible because Cloud Pub/Sub alone cannot process or store data; it requires a consumer like Dataflow to handle the data. Option D lacks a direct data source from mobile apps without a message queue like Cloud Pub/Sub, making it less optimal for real-time ingestion.
Author: LeetQuiz Editorial Team
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Your company is launching a new mobile application and plans to use BigQuery for real-time analysis, transformation, and ML experimentation of user activity data. The team is considering various approaches to ensure real-time ingestion of this data into BigQuery. The solution must be scalable, cost-effective, and capable of handling high volumes of data with low latency. Which of the following approaches should your team adopt? (Choose one correct option)
A
Set up Cloud Pub/Sub to capture user activity data in real-time and use a Dataflow streaming job to process and ingest the data into BigQuery.
B
Deploy an Apache Spark streaming job on Dataproc to directly ingest the user activity data into BigQuery.
C
Configure Cloud Pub/Sub to stream the user activity data directly into BigQuery without any intermediate processing.
D
Implement a Dataflow streaming job to ingest the user activity data into BigQuery without using a message queue.
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