DP-203 Design and implement data storage Practice Question
Which THREE statements are true about partitioning in Azure Synapse Analytics dedicated SQL pool?
⚠ Common exam trap
Watch out — candidates often confuse partitions with distributions, thinking they are automatically aligned, or assume partitioning is only for rowstore indexes, when in fact columnstore indexes are the recommended and most common storage type for partitioning in dedicated SQL pool.
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
✓
Partition switching can be used to quickly load data into a table.
Partition switching in Azure Synapse Analytics dedicated SQL pool allows you to quickly load data into a table by switching a partition from a staging table into the target table. This operation is metadata-only and does not require data movement, making it highly efficient for incremental data loads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Partition switching can be used to quickly load data into a table.
Why this is correct
Switching partitions is a metadata-only operation.
- ✗
Partitions are automatically aligned with distributions.
Why it's wrong here
Partitions and distributions are separate concepts.
- ✓
Each partition is stored as a separate set of rowgroups in a columnstore index.
Why this is correct
Partitions are physically separate in columnstore.
- ✗
Partitioning is only supported on tables with clustered rowstore indexes.
Why it's wrong here
Partitioning works with both columnstore and rowstore.
- ✓
Excessive partitioning can lead to fragmentation and poor query performance.
Why this is correct
Too many partitions increase metadata overhead and can hurt performance.
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