Crucial Exams

GCP Professional Data Engineer Practice Question

An online marketplace receives approximately 150 000 JSON click-stream events per second (about 10 TB/day). Analysts need sub-second, ad-hoc SQL analytics on two years of data, while data scientists occasionally train TensorFlow models that read the same dataset. The engineering team wants a fully managed, low-ops solution that automatically provides cheaper rates for rarely accessed historical data. Which Google Cloud storage approach best satisfies these requirements?

  • Write the events to Cloud Bigtable and export snapshots to Cloud Storage when analysts need to query historical data with Dataproc.

  • Ingest the events into partitioned tables in Cloud SQL for PostgreSQL and connect Data Studio for analyst queries.

  • Persist the raw JSON files in Cloud Storage Nearline and query them through Dataproc Spark SQL jobs scheduled by Cloud Composer.

  • Stream the events to BigQuery using the Storage Write API, store them in a time-partitioned and clustered native table, and rely on BigQuery's automatic long-term storage pricing for older partitions.

GCP Professional Data Engineer
Storing the data
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