DP-203 Design and implement data storage Practice Question
You are troubleshooting a slow-running query in Azure Synapse Analytics dedicated SQL pool. The query joins a large fact table (hash-distributed on ProductID) with a small dimension table (replicated). Upon reviewing the query plan, you see a 'ShuffleMove' operation. What is the most likely cause of the slow performance?
⚠ Common exam trap
Watch out — candidates often assume a 'ShuffleMove' is always caused by a join key mismatch or poor statistics, but the specific scenario of a dimension table failing to replicate due to size is a common and subtle cause that directly triggers data movement.
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
✓
The dimension table is not actually replicated due to its size exceeding the replication threshold
The 'ShuffleMove' operation in a Synapse dedicated SQL pool query plan indicates that data is being moved between distributions to complete the join. If the small dimension table is supposed to be replicated but exceeds the replication threshold (default 60 GB compressed), it will not be replicated and instead remains hash-distributed. This forces a shuffle of the large fact table's data to align with the dimension table's distribution, causing significant data movement and slow performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The dimension table is not actually replicated due to its size exceeding the replication threshold
Why this is correct
If the dimension table is too large to be replicated, it will be distributed and cause shuffle.
- ✗
The query is running with a low resource class
Why it's wrong here
Resource class affects concurrency, not shuffle.
- ✗
Result set caching is enabled
Why it's wrong here
Caching would improve performance, not cause shuffle.
- ✗
Statistics are outdated on the dimension table
Why it's wrong here
Outdated statistics may cause suboptimal plans but not necessarily shuffle.
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