Vectorization in Apache Drill refers to the process of representing and processing data as columnar, fixed-length vectors instead of row-based structures. This approach enables efficient CPU cache utilization, SIMD (Single Instruction Multiple Data) operations, and reduces function call overheads.
By leveraging vectorization, Apache Drill improves query performance through:
1. Enhanced memory locality: Columnar storage optimizes cache usage by accessing contiguous memory locations.
2. Batch processing: Operating on large chunks of data at once minimizes branching and loop overheads.
3. SIMD parallelism: Exploiting hardware capabilities for simultaneous execution of multiple data elements with a single instruction.
4. Reduced deserialization costs: Directly operating on encoded data without converting it into intermediate objects.
