Linear Array Marshaling for Database Data Transfer

The patent segments the large memory array into multiple smaller row-wise arrays and column-wise arrays. This segmentation allows the system to allocate only the necessary memory portions for each specific data access operation, eliminating the need to allocate and maintain large contiguous memory blocks with unused space. Each segmented array can be independently managed and released, improving overall memory efficiency while maintaining adequate data access capacity.

The patent implements dynamic memory allocation where memory arrays are created and destroyed based on actual access patterns. The row-wise and column-wise arrays are dynamically allocated when needed for specific operations and released when no longer required. This dynamic approach allows the system to adapt memory usage to actual workload demands, improving memory efficiency without sacrificing data access capacity.

The patent uses copying to create row-wise and column-wise views of the underlying data without physically duplicating the entire data set. The copying mechanism creates efficient access patterns by organizing data references in row-major and column-major orders, allowing the system to provide multiple access perspectives while minimizing actual data movement and computational overhead.

The patent adds dimensional organization to the data structure by creating both row-wise and column-wise array views. This dimensional approach allows data to be accessed efficiently in either direction without requiring separate physical storage for each access pattern. The dimensional organization reduces computational cost by enabling direct access to rows or columns through pre-organized array structures rather than requiring complex computation during each access operation.

The patent segments massive data sets into manageable row-wise and column-wise arrays that can be processed in smaller chunks. This segmentation allows the system to handle large volumes of data by processing only the necessary portions in memory at any given time, reducing the peak memory requirements and preventing out-of-memory issues while maintaining high data processing capability.

The patent implements a strategy where memory arrays are discarded (released) after their computational purpose is fulfilled and recovered (reallocated) for subsequent operations. The row-wise and column-wise arrays are created when needed for specific computations and released when no longer required, allowing the system to handle massive data sets with limited memory by continuously recycling memory resources rather than requiring all data to remain in memory simultaneously.