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Answer: Implementing Z-order optimization on frequently queried columns.
Z-order optimization is a powerful technique for physically reorganizing data in a Delta Lake table based on column values, significantly improving query performance by minimizing the data scanned during execution. This method is especially effective for large datasets in Azure Data Lake Storage Gen2, as it clusters related data together, reducing disk reads for common queries. Alternatives like storing data in a single large file (option A) may not enhance performance and could increase data reads. While Azure Redis Cache (option B) can cache results, it doesn't directly address query performance issues. Azure CDN (option D) improves data retrieval for remote users but doesn't directly boost query performance within Databricks. Thus, Z-order optimization stands out as the most effective approach for query performance improvement.
Author: LeetQuiz Editorial Team
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Which Delta Lake optimization technique is most effective for enhancing query performance on large datasets in Azure Data Lake Storage Gen2 within Databricks?
A
Storing data in a single large file to reduce the number of read operations.
B
Using Azure Redis Cache to store intermediate query results.
C
Implementing Z-order optimization on frequently queried columns.
D
Enabling Azure CDN for Delta Lake files to increase data retrieval speed.
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