Which Delta Lake feature mentioned in the material enables faster reads for Parquet formats in Fabric Delta Lake?

• A. VACUUM
• B. OptimizeWrite function
• C. Data Skipping Index
• D. V-Order function

Answer: (D)

Reading speed for Parquet in Delta Lake hinges on how data is physically organized on disk. By clustering related rows together across multiple columns, you reduce the amount of data the engine must scan for a given filter. The V-Order function implements this multi-column ordering, arranging data using a space‑filling curve idea so that values that tend to be queried together end up stored near one another. When queries specify predicates on those columns, the reader can prune away large portions of blocks that don’t match, touching far fewer Parquet blocks and speeding up the read.

Other options serve different maintenance or optimization purposes rather than delivering that direct read-time benefit. VACUUM cleans up unused files, which helps storage hygiene but not the fast-path read optimization. The OptimizeWrite function improves writes by consolidating small files, which can indirectly help reads in some scenarios but doesn’t reorder data for fast predicate-based reads. Data Skipping Index adds pruning capabilities, but V-Order provides the actual physical data layout that accelerates reads for Parquet formats by maximizing locality of related data.