Answer-first summary for fast verification
Answer: Implement Z-order optimization on columns that are often queried together.
Implementing Z-order optimization on columns that are frequently queried together reorganizes the data to group related data physically closer on disk. This method significantly boosts query performance without a notable increase in storage costs, as it avoids data duplication or reshuffling. Other options like repartitioning or converting formats either increase storage costs or do not effectively optimize for specific query patterns.
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When encountering performance issues while querying a large dataset in Delta Lake, which technique would you apply to enhance query performance without substantially increasing storage costs?
A
Convert the dataset to a different format, such as CSV, for faster read performance.
B
Increase the file size of your Delta Lake table‘s underlying Parquet files.
C
Implement Z-order optimization on columns that are often queried together.
D
Repartition the data by the most frequently queried column.
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