- A
Redistribute the tables across nodes using HANA's table partitioning features.
Partitioning and redistribution ensures even data distribution.
- B
Increase the memory allocation for the HANA database.
Why wrong: Memory allocation does not affect data distribution.
- C
Add more worker nodes to the scale-out cluster to distribute the load.
Why wrong: Adding nodes does not automatically rebalance existing data.
- D
Upgrade the EC2 instance type of all nodes to a memory-optimized type.
Why wrong: Memory increase does not solve distribution problem.
Question 943 of 1,733
PAS-C01 Design of SAP Workloads on AWS Practice Question
This PAS-C01 practice question tests your understanding of design of sap workloads on aws. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 company is running SAP HANA on AWS using a scale-out architecture with multiple worker nodes. The system is used for real-time analytics. Recently, query performance has degraded. The HANA administrator notices that the data is not evenly distributed across nodes. What is the best course of action?
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
✓
Redistribute the tables across nodes using HANA's table partitioning features.
The correct answer is A because SAP HANA's table partitioning features allow you to redistribute data across worker nodes in a scale-out architecture, addressing the root cause of uneven data distribution. This rebalancing improves query performance by ensuring parallel processing and minimizing data movement between nodes. The HANA administrator can use commands like ALTER TABLE ... REBALANCE or partition management to achieve even distribution.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Redistribute the tables across nodes using HANA's table partitioning features.
Why this is correct
Partitioning and redistribution ensures even data distribution.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the memory allocation for the HANA database.
Why it's wrong here
Memory allocation does not affect data distribution.
- ✗
Add more worker nodes to the scale-out cluster to distribute the load.
Why it's wrong here
Adding nodes does not automatically rebalance existing data.
- ✗
Upgrade the EC2 instance type of all nodes to a memory-optimized type.
Why it's wrong here
Memory increase does not solve distribution problem.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse scaling up (increasing resources) or scaling out (adding nodes) with the need to rebalance existing data, assuming that more capacity alone will fix performance degradation caused by data skew.
Detailed technical explanation
How to think about this question
In SAP HANA scale-out, data is distributed using hash or round-robin partitioning across worker nodes. When distribution becomes skewed, queries on heavily loaded nodes experience higher I/O and CPU contention, while other nodes are idle. The ALTER TABLE ... REBALANCE command or partition splitting can redistribute data without downtime, leveraging HANA's internal data movement mechanisms to restore balance and optimize parallel query execution.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Questions learners often ask
What does this PAS-C01 question test?
Design of SAP Workloads on AWS — This question tests Design of SAP Workloads on AWS — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Redistribute the tables across nodes using HANA's table partitioning features. — The correct answer is A because SAP HANA's table partitioning features allow you to redistribute data across worker nodes in a scale-out architecture, addressing the root cause of uneven data distribution. This rebalancing improves query performance by ensuring parallel processing and minimizing data movement between nodes. The HANA administrator can use commands like ALTER TABLE ... REBALANCE or partition management to achieve even distribution.
What should I do if I get this PAS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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