In the context of Delta Lake tables experiencing high-frequency updates to existing records, which approach is most effective in reducing the performance impact on both query and ingestion operations?

Real Exam

Split the table into frequently updated and static partitions, applying updates in bulk to the dynamic partition.

3.7%

Implement an event sourcing model, storing updates as events and materializing the final state in a separate table for queries.

7.3%

Leverage Delta Lake‘s MERGE operation, optimizing merge conditions and clustering the table by update keys.

74.4%

Regularly compact the Delta Lake table to merge small files and optimize the layout for faster updates and queries.

14.6%

Databricks Certified Data Engineer - Professional