DP-203 Develop data processing Practice Question
You need to process a large dataset stored as CSV files in Azure Data Lake Storage Gen2 using Azure Databricks. The processing involves several transformations and aggregations. You want to minimize shuffle operations. Which approach should you use?
⚠ Common exam trap
Watch out — candidates often confuse partitioning (which can increase shuffle) with Z-ordering (which reduces shuffle by improving data locality without creating new partitions), leading them to choose bucketing or high-cardinality partitioning as a solution for shuffle minimization.
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
✓
Use Delta Lake and apply Z-ordering on the columns used in filters and aggregations
Z-ordering in Delta Lake co-locates related data within files based on specified columns, which significantly reduces the amount of data scanned during filter and aggregation operations. By minimizing the data that needs to be read, Z-ordering inherently reduces shuffle operations because fewer partitions need to be exchanged across the cluster during transformations. This approach is specifically designed to optimize query performance on large datasets in Azure Databricks without increasing the number of shuffle stages.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Delta Lake and apply Z-ordering on the columns used in filters and aggregations
Why this is correct
Z-ordering co-locates related data, reducing data shuffling.
- ✗
Cache the data in memory after reading
Why it's wrong here
Caching does not reduce shuffle; it speeds up subsequent actions.
- ✗
Use bucketing with a fixed number of buckets
Why it's wrong here
Bucketing helps with join optimization but not general shuffle reduction.
- ✗
Partition the data by a high-cardinality column
Why it's wrong here
High-cardinality partitions can lead to small file issues and many shuffle stages.
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