DP-203 Develop data processing Practice Question
You are configuring a data pipeline in Azure Data Factory that uses a Mapping Data Flow. The source is a SQL Server table with 50 million rows. The sink is a Delta table in ADLS Gen2. The pipeline runs slowly. You need to improve performance by reducing the number of partitions in the data flow. Which setting should you adjust?
⚠ Common exam trap
Many candidates confuse the 'Optimize' tab settings on the sink with the 'Partition option' in the source or pipeline activity, or mistakenly think that reducing cluster size (Option B) is a valid performance tuning technique for partition reduction.
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
✓
In the sink transformation, set the 'Optimize' tab to 'Single partition'.
Setting the sink transformation's 'Optimize' tab to 'Single partition' forces all data to be written into a single partition, which reduces the number of output files and the associated metadata overhead. This can improve performance when the downstream processing or storage benefits from fewer, larger files, especially for small-to-medium datasets or when the sink is a Delta table that must be compacted later.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
In the source transformation, set the 'Optimize' tab to 'Use current partitioning'.
Why it's wrong here
Source optimization affects read, not sink write partitions.
- ✗
Decrease the cluster size to 4 cores.
Why it's wrong here
Cluster size affects parallelism but not partition count directly.
- ✓
In the sink transformation, set the 'Optimize' tab to 'Single partition'.
Why this is correct
Sink optimization controls how data is written; setting to single partition reduces file count.
- ✗
In the pipeline activity, set the 'Data flow' property 'partitionOption' to 'Single partition'.
Why it's wrong here
The partition option is set within the data flow transformations, not at pipeline level.
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