Databricks Certified Data Engineer Professional — Question 139

A Structured Streaming job deployed to production has been resulting in higher than expected cloud storage costs. At present, during normal execution, each microbatch of data is processed in less than 3s; at least 12 times per minute, a microbatch is processed that contains 0 records. The streaming write was configured using the default trigger settings. The production job is currently scheduled alongside many other Databricks jobs in a workspace with instance pools provisioned to reduce start-up time for jobs with batch execution.

Holding all other variables constant and assuming records need to be processed in less than 10 minutes, which adjustment will meet the requirement?

Answer options

• A. Set the trigger interval to 3 seconds; the default trigger interval is consuming too many records per batch, resulting in spill to disk that can increase volume costs.
• B. Use the trigger once option and configure a Databricks job to execute the query every 10 minutes; this approach minimizes costs for both compute and storage.
• C. Set the trigger interval to 10 minutes; each batch calls APIs in the source storage account, so decreasing trigger frequency to maximum allowable threshold should minimize this cost.
• D. Set the trigger interval to 500 milliseconds; setting a small but non-zero trigger interval ensures that the source is not queried too frequently.

Correct answer: B

Explanation

The correct answer is B because using the trigger once option and scheduling the job to run every 10 minutes effectively minimizes unnecessary processing of empty microbatches, thereby reducing both compute and storage costs. Option A does not address the root cause of the empty batches, while option C may lead to delayed processing beyond the 10-minute requirement. Option D would still lead to the frequent querying of the source, which does not resolve the cost issue.