DP-203 Develop data processing Practice Question
Your company uses Azure Synapse Analytics to run a data warehouse. You have a dedicated SQL pool with a hash-distributed fact table named Sales. The distribution column is ProductID. You notice that queries against the Sales table are slow due to data skew. After analysis, you find that a few products (e.g., ProductID 100, 200) account for 80% of the rows. You need to optimize query performance without redesigning the entire table. You also need to minimize data movement during queries. Which action should you take?
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
✓
Change the distribution to round-robin.
Round-robin distribution distributes data evenly across distributions, eliminating skew. However, it may increase data movement for joins. Given the severe skew, round-robin is a reasonable trade-off. Option B is wrong because increasing the number of distributions does not fix skew. Option C is wrong because changing to replicate distribution is not suitable for large fact tables. Option D is wrong because creating non-clustered indexes does not address distribution skew.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Change the distribution to round-robin.
Why this is correct
Correct. Round-robin distribution evenly distributes rows, eliminating skew. Although it can increase data movement during joins, it is an effective fix for severe skew without redesign.
- ✗
Increase the number of distributions to 120.
Why it's wrong here
Wrong. Increasing the number of distributions from 60 to 120 does not address the skew; the skewed data will still be concentrated on a few distributions.
- ✗
Change the distribution to replicate for the Sales table.
Why it's wrong here
Wrong. Replicated tables are suitable for small dimension tables, not large fact tables like Sales. Replicating a large table would consume excessive storage and cause high data movement.
- ✗
Create non-clustered indexes on the ProductID column.
Why it's wrong here
Wrong. Non-clustered indexes improve query performance for selective queries but do not solve the underlying distribution skew issue.
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