Databricks Certified Data Engineer - Associate
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A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form larger files to improve performance.
Which keyword can be used to compact the small files?
Real Exam
Community
KKeng
A
OPTIMIZE
B
VACUUM
C
COMPACTIOON
D
REPARTITION
Explanation:
Explanation
The correct answer is OPTIMIZE.
Why OPTIMIZE is correct:
- OPTIMIZE is a Delta Lake command specifically designed to compact small files into larger ones to improve read performance.
- When you run
OPTIMIZEon a Delta table, it rewrites small files into larger, more efficient files. - This process is often referred to as "compaction" or "file compaction."
Why other options are incorrect:
- VACUUM: This command is used to remove old, unused data files that are no longer referenced by the Delta table (garbage collection), not for compacting small files.
- COMPACTIOON: This appears to be a typo/misspelling of "compaction" and is not a valid Delta Lake command.
- REPARTITION: While this can affect file sizes by changing the number of partitions, it's not specifically designed for compacting existing small files.
REPARTITIONis a Spark transformation that redistributes data across partitions, butOPTIMIZEis the dedicated command for file compaction in Delta Lake.
Key Points:
- Use
OPTIMIZEto improve query performance by compacting small files - The syntax is:
OPTIMIZE table_name - You can also use
OPTIMIZE table_name WHEREto optimize specific partitions - This operation is idempotent and can be run multiple times without issues
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