The core principle involves the utilization of memory-mapped I/O strategies to manage data streams exceeding available RAM capacity by processing them as disjointed subsets. This methodology operates within the domain of computational resource management and stream processing, adhering to the theoretical constraint that total file size must be partitioned into discrete units to mitigate memory overflow conditions. It functions as a fundamental algorithmic optimization technique situated within the subfield of efficient data handling, ensuring system stability when interacting with large-scale storage media.
Prerequisite chain context: requires File Hashing with hashlib Module in Python.