Which approach is used to optimize the read and write performance of a Delta Lake table?

The approach of applying Z-Ordering for frequently queried columns is effective in optimizing the read and write performance of a Delta Lake table. Z-Ordering is a technique that reorganizes the data within the table based on the values of specified columns. When you Z-Order the data, it co-locates related information within the same file, which significantly improves the performance for queries that filter on those columns. As a result, read operations become more efficient, as there is less data to scan when executing filters or joins involving the Z-Ordered columns.

Additionally, Z-Ordering reduces latency for queries and enhances the overall performance, especially in analytics workloads. This optimization is particularly beneficial when dealing with large datasets where data retrieval operations need to be as fast as possible.

Other optimization techniques like those mentioned in the other options may contribute to performance but do not specifically target improving query efficiency in the same way that Z-Ordering does for frequently accessed columns. For example, traditional Parquet optimizations focus on the file format, and while they provide benefits, they are not tailored specifically for Delta Lake's features. Running the VACUUM command is essential for managing data files and reclaiming storage, but it does not enhance read performance directly. Partitioning data based on