DP-203 Develop data processing Practice Question
You are building a data processing solution in Azure Synapse Analytics. The solution requires creating a table that stores sales transactions. The table will be used for both point-of-sale lookups and large aggregation queries. The data is not updated frequently. Which table distribution should you recommend?
⚠ Common exam trap
Watch out — candidates often choose HASH distribution thinking it always improves query performance, but they overlook that without a clear join or grouping column that matches the hash key, HASH can cause data skew and actually degrade mixed workload performance compared to ROUND_ROBIN.
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
✓
ROUND_ROBIN
ROUND_ROBIN is the correct choice because the table is used for both point-of-sale lookups (single-row queries) and large aggregation queries, and the data is not updated frequently. ROUND_ROBIN distributes data evenly across all distributions without a hash key, which provides the best overall performance for mixed workloads where no single distribution key optimizes both lookup and aggregation patterns. It avoids data skew and allows parallel processing for aggregations while still supporting efficient lookups when combined with appropriate indexes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
ROUND_ROBIN
Why this is correct
ROUND_ROBIN evenly distributes data and works well for mixed workloads.
- ✗
HASH on TransactionID
Why it's wrong here
TransactionID may be unique but could cause skew if not evenly distributed.
- ✗
HASH on SalesDate
Why it's wrong here
SalesDate may cause hot spots if many transactions occur on the same date.
- ✗
REPLICATE
Why it's wrong here
REPLICATE is for small tables, not large fact tables.
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