Covers the principles and mechanisms of virtual memory in computer systems, focusing on isolation, efficiency, and the role of the Memory Management Unit.
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.
Explores storage management challenges in transitioning to data lakes, addressing software and hardware heterogeneity, unified storage design, and performance optimization.
