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Databricks Certified Data Engineer - Professional

Databricks Certified Data Engineer - Professional

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To enhance query performance on a Delta table named 'voters' where columns 58 and 59 are frequently used for highly selective filters, what strategy should a data engineer employ during table creation, considering the need to minimize overhead as new records are added?

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Explanation:

The optimal approach involves repositioning columns 58 and 59 within the first 32 columns to take advantage of the default statistics collection for these columns, thereby improving query performance without significantly increasing overhead as new records are added. Adjusting 'delta.dataSkippingNumIndexedCols' to include more columns would enable statistics collection but at the cost of higher overhead. Statistics are not collected for all columns by default, making the first option incorrect. Focusing statistics collection on just two columns or repositioning them within the first 16 columns does not fully leverage the default settings for optimal performance.

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