Lecture
This lecture covers advanced Spark optimization techniques, focusing on data partitioning, shuffle operations, memory management, and Spark architecture. Topics include RDD manipulation, Spark units of work, memory optimization, and partitioning strategies. The instructor provides insights on minimizing shuffling, optimizing memory usage, and improving data processing efficiency.