Quick Answer
The answer is to resize the cluster to a larger node type or add nodes. This is the most cost-effective fix for a Redshift disk spill because the root cause is insufficient memory or compute capacity relative to the workload; when queries spill to disk, they are forced to use slower storage instead of RAM, directly degrading performance. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of scaling strategies versus tuning—a common trap is to suggest vacuuming or sorting keys, but those address data bloat, not the fundamental memory shortage causing the spill. Remember, disk spill is a resource starvation signal, not a data organization problem. Memory tip: "Spill means scale, not sort"—if queries are spilling to disk, scale up the cluster rather than tweaking table design.
This DEA-C01 practice question tests your understanding of data store management. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineer is troubleshooting an Amazon Redshift cluster that is experiencing slow query performance. The engineer notices that the disk space is heavily utilized and queries are spilling to disk. What is the most cost-effective solution to improve performance?
Run VACUUM command to reclaim space
Why wrong: Vacuum reclaims deleted space but does not add capacity.
Change distribution style to KEY
Why wrong: Distribution style affects data distribution, not disk space.
Resize the cluster to a larger node type or add nodes
Adding memory and disk reduces spilling to disk.
Apply compression encoding to tables
Why wrong: Compression reduces storage but does not solve current disk spill.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Resize the cluster to a larger node type or add nodes
When queries spill to disk due to heavy disk utilization, the root cause is insufficient memory or compute capacity relative to the workload. Resizing the cluster (adding nodes or moving to a larger node type) directly increases available memory and CPU, reducing or eliminating disk spill and improving query performance. This is the most cost-effective solution because it scales resources proportionally without requiring manual tuning or schema changes.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Run VACUUM command to reclaim space
Why it's wrong here
Vacuum reclaims deleted space but does not add capacity.
Change distribution style to KEY
Why it's wrong here
Distribution style affects data distribution, not disk space.
Resize the cluster to a larger node type or add nodes
Why this is correct
Adding memory and disk reduces spilling to disk.
Related concept
Read the scenario before looking for a memorised answer.
Apply compression encoding to tables
Why it's wrong here
Compression reduces storage but does not solve current disk spill.
Common exam traps
The trap here is that candidates confuse disk space management (VACUUM, compression) with memory/query execution issues, leading them to choose storage optimization options when the real bottleneck is insufficient compute resources.
Detailed technical explanation
Disk spill occurs when a query's working set exceeds the memory allocated to a slice (e.g., 1/16th of node memory for a 16-slice node). Resizing to a larger node type (e.g., from dc2.large to dc2.8xlarge) increases per-slice memory proportionally, while adding nodes increases the total number of slices and aggregate memory. In practice, a cluster at 80% disk usage with frequent spill may benefit from a 2x node count increase, which also improves I/O parallelism.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Resize the cluster to a larger node type or add nodes — When queries spill to disk due to heavy disk utilization, the root cause is insufficient memory or compute capacity relative to the workload. Resizing the cluster (adding nodes or moving to a larger node type) directly increases available memory and CPU, reducing or eliminating disk spill and improving query performance. This is the most cost-effective solution because it scales resources proportionally without requiring manual tuning or schema changes.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.
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