Question 10
A Fabric workspace runs long and short Spark sessions under a shared capacity. The current environment exhibits the following problem: session settings changed in the UI but a job retains old values. What is the most defensible next action?
Explanation
Correct Answer
Inspect notebook-specific settings and environment overrides against workspace defaults. Item-level or environment configuration can supersede the workspace's defaults.
Incorrect Answers
A large shuffle job repeatedly exhausts its executors. Insufficient executor resources or skew can fail shuffles despite available capacity.
Idle interactive sessions retain resources unnecessarily. Stopping idle sessions releases shared Spark capacity for new work.
Spark startup latency is high when every notebook provisions new executors. Appropriate pool/session settings can reduce repeated startup overhead.