Databricks Certified Data Engineer - Professional
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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.
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.
Explanation:
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.