A data engineer triggers a scheduled job but finds that the new run was not executed. The run history shows that the run was skipped with a concurrency-related queue message.
Which configuration should the engineer investigate?
A.
The cluster spot-instance availability in the cloud provider
B.
The SQL warehouse permissions for the task
C.
The job-level max_concurrent_runs setting and whether queueing is enabled
The engineer should inspect the job’s maximum concurrent-runs configuration and its queueing setting. max_concurrent_runs controls how many active runs of the same job can execute simultaneously. When that limit has already been reached, Databricks can skip the newly triggered run if queueing is disabled. When queueing is enabled, the additional run waits until capacity becomes available instead of being skipped. Spot-instance availability might delay or prevent compute startup, but it would not normally produce a job-level concurrency message. SQL warehouse permissions affect SQL task execution after a run begins, while timeout_seconds determines how long a task may run before timing out. Therefore, option C directly addresses the reported run state. This candidate was also compared against the existing Word question bank.
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