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Answer: Run OPTIMIZE command with z-ordering on shipment_id, set auto-compaction to true, and use VACUUM with a retention interval of 7 days.
Using the OPTIMIZE command with z-ordering on shipment_id helps in clustering data more efficiently, which is beneficial for read operations. Enabling auto-compaction ensures that small files are periodically merged, improving write performance. Using VACUUM with a reasonable retention interval (7 days) helps in cleaning up unused files without risking data loss.
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You are tasked with optimizing a Delta table for the Databricks SQL service that contains data from a logistics company. The table includes columns like shipment_id, driver_id, delivery_date, and status. Explain how you would use Delta Lake features such as OPTIMIZE, VACUUM, and the configuration of auto-compaction to ensure the table is optimized for both read and write operations.
A
Run OPTIMIZE command with z-ordering on shipment_id, set auto-compaction to true, and use VACUUM with a retention interval of 7 days.
B
Run OPTIMIZE command with z-ordering on driver_id, disable auto-compaction, and use VACUUM with a retention interval of 1 day.
C
Run OPTIMIZE command with z-ordering on delivery_date, set auto-compaction to true, and use VACUUM with a retention interval of 30 days.
D
Run OPTIMIZE command with z-ordering on status, disable auto-compaction, and do not use VACUUM.