DP-203 Design and implement data storage Practice Question
A company uses Azure Synapse Analytics dedicated SQL pool. They need to load data from Azure Data Lake Storage Gen2 (ADLS Gen2) incrementally. Which PolyBase external table configuration supports incremental loading without reprocessing historical data?
⚠ Common exam trap
Candidates often confuse indexing or distribution strategies (which apply to internal tables) with external table capabilities, overlooking that only partition elimination on external tables enables incremental file-level filtering in PolyBase.
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
✓
Create an external table partitioned by date column with a partition location pattern.
Partitioning an external table by a date column with a partition location pattern allows PolyBase to perform partition elimination during queries. This means only the partitions containing new or modified data are read from ADLS Gen2, enabling incremental loading without scanning historical data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create an external table with a clustered index on the date column.
Why it's wrong here
External tables do not support indexes.
- ✓
Create an external table partitioned by date column with a partition location pattern.
Why this is correct
Partitioned external tables allow PolyBase to eliminate partitions, loading only new data.
- ✗
Create an external table on ORC files with a clustered columnstore index.
Why it's wrong here
ORC is a file format, not a partitioning strategy; indexes cannot be created on external tables.
- ✗
Create an external table with round-robin distribution on the date column.
Why it's wrong here
Round-robin distribution distributes rows randomly; it does not support partition pruning.
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