DBS-C01 Management and Operations Practice Question
A data warehouse team is migrating from Amazon Redshift to Amazon Redshift RA3 nodes. The current cluster uses 10 DC2.large nodes. The new cluster will use 4 RA3.xlarge nodes. After the migration, the team notices that query performance is significantly slower. Which factor is the MOST likely cause of the performance degradation?
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
✓
The cluster has fewer nodes, reducing parallelism.
Reducing the number of nodes from 10 to 4 decreases the parallelism, even though RA3 nodes have more compute capacity per node. Redshift distributes data across slices, and each node has multiple slices. With fewer nodes, the total number of slices is lower, reducing the degree of parallelism for query execution, which can lead to slower performance for large queries. Option A is incorrect because the distribution style (EVEN vs KEY) affects data distribution but is not the most likely cause here; the question does not indicate a change in distribution style. Option B is incorrect because RA3 nodes use managed storage with ample capacity; disk space is not constrained. Option D is incorrect because RA3 nodes are optimized for large datasets; the issue is not the node type but the reduction in parallelism due to fewer nodes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The data distribution style is set to EVEN instead of KEY.
Why it's wrong here
Distribution style affects performance but is not the most likely cause.
- ✗
The cluster does not have enough disk space for the workload.
Why it's wrong here
RA3 uses managed storage and does not require local disk sizing.
- ✓
The cluster has fewer nodes, reducing parallelism.
Why this is correct
RA3 nodes separate compute and storage; fewer compute nodes reduce parallelism.
- ✗
RA3 nodes are not optimized for large datasets.
Why it's wrong here
RA3 nodes are optimized for large datasets with managed storage.
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