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Management and OperationsmediumMultiple ChoiceObjective-mapped

DBS-C01 Management and Operations Practice Question

A company has an Amazon Redshift cluster that is running slowly on complex queries. The cluster has 10 dc2.large nodes. The 'QueryDuration' metric shows high values for several queries. The team wants to improve performance without changing queries. Which action is MOST likely to help?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Add more nodes of the same type to the cluster.

Adding more nodes (scaling out) increases the cluster's compute capacity, allowing complex queries to process data in parallel without any query changes. Option C is incorrect because Redshift Spectrum requires data to be in S3 and external tables to be defined, which would require modifying queries to reference those tables. Option B reduces storage I/O but not CPU-bound complex queries. Option D increasing concurrency can cause resource contention, slowing queries.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Add more nodes of the same type to the cluster.

    Why this is correct

    Adding more nodes increases the cluster's compute capacity, allowing complex queries to process more data in parallel without any changes to the queries themselves.

  • Enable compression on all columns.

    Why it's wrong here

    Enabling compression reduces storage and I/O but does not directly improve the performance of complex queries that involve CPU-intensive operations.

  • Enable Redshift Spectrum to offload queries to Amazon S3.

    Why it's wrong here

    Redshift Spectrum allows querying data in S3, but it requires defining external tables and modifying queries to reference those tables, contradicting the requirement to not change queries.

  • Increase the workload management (WLM) concurrency level.

    Why it's wrong here

    Increasing WLM concurrency may lead to resource contention among concurrent queries, potentially degrading performance rather than improving it.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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