A data analytics specialist is setting up workload management in manual mode for an Amazon Redshift environment. The data analytics specialist is defining query monitoring rules to manage system…

Question

Options

• AA unique rule name, a query runtime condition, and an AWS Lambda function to resubmit any
• BA queue name, a unique rule name, and a predicate-based stop condition
• CA unique rule name, one to three predicates, and an action
• DA workload name, a unique rule name, and a query runtime-based condition

• A
  3% (1)
• B
  6% (2)
• C
  91% (31)

Explanation

Amazon Redshift WLM query monitoring rules have exactly three required elements: (1) a unique rule name to identify the rule; (2) one to three predicates that define the condition(s) to monitor (e.g., query_execution_time > 100, query_cpu_time > 50, rows_returned > 1000000); and (3) an action to take when all predicates are met - valid actions are log (record to STL_WLM_RULE_ACTION), hop (move query to next matching queue), or abort (terminate the query). This is the AWS-documented structure. Option A incorrectly includes a Lambda function, which is not a native WLM rule action. Option B incorrectly specifies a queue name as a required element of the rule itself (queues and rules are separate WLM constructs). Option D introduces 'workload name' which is not a defined WLM rule component.

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