When designing a Spark job in Databricks for a multi-dimensional analysis project that involves complex joins across multiple large datasets, which strategies would you implement to optimize join operations for high performance?

Real Exam

Applying a filter on datasets prior to joining to reduce the size of data being processed and joined.

8.2%

Converting datasets to Delta format and using Z-ordering to colocate related information on the disk for faster access during joins.

15.3%

Pre-partitioning datasets based on join keys before executing the join operations to minimize data shuffling.

54.1%

Utilizing broadcast joins for smaller datasets to avoid shuffling the larger dataset across the cluster.

22.4%

Databricks Certified Data Engineer - Professional