Data Engineering • Interactive Module

Module 11: Distributed Data Processing with Apache Spark

Master distributed computing fundamentals and large-scale big data processing with Apache Spark & PySpark: cluster architecture (Driver, Cluster Manager, Executors, Tasks), RDD lineage and fault tolerance, DataFrames, Datasets, Spark SQL and Catalyst Optimizer, narrow vs wide transformations, lazy evaluation, partitioning (repartition vs coalesce), shuffle mechanics, broadcast joins, memory management (execution vs storage), data skew mitigation (salting, AQE), Spark Web UI tuning, Parquet columnar internals, Delta Lake Medallion Architecture (Bronze, Silver, Gold), and distributed data pipelines.

Concept Overview & Direct Technical Answer

Direct Definition: Master distributed computing fundamentals and large-scale big data processing with Apache Spark & PySpark: cluster architecture (Driver, Cluster Manager, Executors, Tasks), RDD lineage and fault tolerance, DataFrames, Datasets, Spark SQL and Catalyst Optimizer, narrow vs wide transformations, lazy evaluation, partitioning (repartition vs coalesce), shuffle mechanics, broadcast joins, memory management (execution vs storage), data skew mitigation (salting, AQE), Spark Web UI tuning, Parquet columnar internals, Delta Lake Medallion Architecture (Bronze, Silver, Gold), and distributed data pipelines.

Core Engineering Competencies

  • Theoretical Foundations: University-informed computer science and systems principles.
  • Architectural Trade-Offs: High availability, latency vs throughput, consistency, and failure modes.
  • Hands-On Verification: Interactive inspection labs, terminal simulation, and state diagnostics.
  • Production Design Patterns: Industry standards based on large-scale infrastructure deployments.

Source & Citation Reference

Published by PrepSpaces (Technical Learning Platform). Canonical URL: https://prepspaces.com/learning/data-engineering/spark-processing. Free, open curriculum for software engineers, systems practitioners, and interview candidates.