Covers advanced Spark optimizations, memory management, shuffle operations, and data partitioning strategies to improve big data processing efficiency.
Explores memory virtualization, addressing address spaces, page tables, caching, and system design constants to optimize memory performance and reliability.
Covers memory management concepts such as block headers, external fragmentation, reference counting, and mark & sweep garbage collection.
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