AWS Certified SysOps Administrator – AssociateCost and Performance OptimizationHard
A retail company uses Amazon Redshift as its data warehouse for business intelligence reporting. Analysts frequently run complex queries that involve large joins and aggregations on multiple tables. During peak business hours, these queries often compete for resources, leading to increased query execution times and frustrated users. The company needs to improve query performance and ensure critical reports are processed efficiently. Which Redshift feature should they configure and optimize?
- AAdjust Workload Management (WLM) queues.
- BEnable Concurrency Scaling.
- CMigrate to a larger Redshift cluster instance type.
- DImplement Short Query Acceleration (SQA).
Show answer & explanationAnswer & explanation
Correct answer: A. Adjust Workload Management (WLM) queues.
Workload Management (WLM) allows you to define multiple query queues and assign different priorities and resource allocations (concurrency levels, memory) to each queue. By creating separate queues for critical reports and less critical ad-hoc queries, and configuring appropriate resource limits, the company can ensure critical reports are processed efficiently without being starved of resources by other queries.
Why the other options are wrong
- B. Concurrency Scaling allows Redshift to add temporary capacity for bursty workloads, but without proper WLM, queries might still compete for resources on the main cluster or the scaled capacity might not prioritize critical queries.
- C. Migrating to a larger cluster might provide more overall resources, but without WLM, the same resource contention issues between different query types could persist.
- D. Short Query Acceleration (SQA) prioritizes short-running queries, but the problem describes *complex* queries (large joins, aggregations) and critical *reports*, which are typically not short queries. SQA would not address the core issue of resource contention for these complex reports.
Redshift Workload Management (WLM)
A feature in Amazon Redshift that allows you to manage query concurrency and resource allocation for different types of workloads.
- Defines query queues with specific resource limits and priorities.
- Ensures critical queries receive necessary resources.
- Can use automatic WLM or manual WLM for fine-grained control.
Memory trick: WLM brings order to query chaos, ensuring critical reports run.