DP-203 Broadcast join Practice Question
You are building a data processing pipeline in Azure Synapse Analytics that uses a mapping data flow to perform a lookup transformation. The lookup source is a dimension table with 10 million rows. You need to optimize the lookup performance. Which THREE actions 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
✓
Enable the 'Broadcast' option on the lookup source transformation if the dimension table is less than 100 MB.
To optimize lookup performance in a mapping data flow, the recommended actions are: C. Enable the 'Broadcast' option on the lookup source if the dimension table is less than 100 MB. This avoids shuffling the large fact table across nodes. D. Select only the necessary columns in the lookup source transformation to reduce data transfer and memory usage. E. Ensure the dimension table has an index on the columns used for the lookup to speed up the join operation. Options A and B are not optimal: Increasing batch size (A) does not improve lookup performance; it affects sink writes. Partitioning the dimension table on the lookup key before reading (B) can be helpful, but in a data flow, partitioning is typically applied to the source or within the data flow itself, and it is not one of the top three recommended actions for lookup optimization in Synapse mapping data flows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the batch size in the lookup transformation settings.
Why it's wrong here
Batch size is not a setting in lookup transformation.
- ✗
Partition the dimension table on the lookup key before reading.
Why it's wrong here
Partitioning is not done in the data flow; it's a table design consideration.
- ✓
Enable the 'Broadcast' option on the lookup source transformation if the dimension table is less than 100 MB.
Why this is correct
Broadcasting avoids shuffle for small dimension tables.
- ✓
Select only the necessary columns in the lookup source transformation.
Why this is correct
Narrowing columns reduces the amount of data processed.
- ✓
Ensure the dimension table has an index on the columns used for the lookup.
Why this is correct
Indexes speed up lookup queries.
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