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GCP Professional Data Engineer Practice Question

Your analytics team runs Looker dashboards that issue interactive queries against BigQuery in the analytics-prod project. At the top of every hour, an hourly scheduled job in the same project runs heavy aggregation queries on raw event data. During that window, dashboard requests fail because the project's interactive query concurrency limit is exceeded. You cannot add projects or buy more capacity, and the aggregation must still execute hourly. Which change will prevent the scheduled workload from blocking the dashboards while keeping the schedule unchanged?

  • Execute the scheduled queries using a dedicated service account to separate them from user traffic.

  • Add a LIMIT clause to each dashboard query so they scan fewer rows and return faster.

  • Set the hourly scheduled queries to run with BATCH priority instead of INTERACTIVE.

  • Increase the maximum_bytes_billed setting for the scheduled queries to allow greater parallelism.

GCP Professional Data Engineer
Maintaining and automating data workloads
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