DP-203 Develop data processing Practice Question
A company uses Azure Synapse Analytics dedicated SQL pool. The data engineering team notices that queries against a large fact table are running slowly. The table uses round-robin distribution and has a columnstore index. The team wants to improve query performance without adding more resources. Which action should the team 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 hash on the column that is most frequently used in joins.
Hash-distributing the large fact table on the column most frequently used in joins minimizes data movement during query processing, improving performance. Round-robin distribution distributes data evenly but does not optimize for join operations. Hash distribution on a join key ensures that rows with the same key value are placed in the same distribution, reducing shuffling. Option A is incorrect because increasing the degree of parallelism does not address the distribution issue and may not improve performance without additional resources. Option B is incorrect because hash on multiple columns is not supported in Azure Synapse dedicated SQL pool; only a single column can be used as the distribution key. Option D is incorrect because a heap table would lack indexing, degrading query performance for analytical workloads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Keep round-robin distribution but increase the degree of parallelism.
Why it's wrong here
Would require more resources, not just configuration change.
- ✗
Change the distribution to hash on multiple columns.
Why it's wrong here
Hash distribution supports only one column.
- ✓
Change the distribution to hash on the column that is most frequently used in joins.
Why this is correct
Hash distribution on a join key reduces data shuffling.
- ✗
Rebuild the table as a heap to improve insert performance.
Why it's wrong here
Heaps are not optimized for analytical queries.
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