Apache Spark for Engineers: 5 Real-World Use Cases

Explain why Apache Spark exists, how its execution model actually works, and recognize the concrete production problems it solves — from personalized recommendations to real-time fraud scoring.

4 sections · 9 lessons

Course outline

Why Spark Exists

  1. The Problem with Disk-Based MapReduce
  2. In-Memory Computing and the DAG

The Engine Underneath

  1. RDDs, DataFrames, and the Catalyst Optimizer
  2. Partitioning and Shuffles — Where Performance Breaks

One Engine, Many Workloads

  1. Batch Processing and Structured Streaming
  2. MLlib and Iterative Algorithms

Spark in the Real World

  1. Personalization at Scale: Spotify's Discover Weekly
  2. Real-Time Fraud Scoring and Surge Pricing
  3. Common Gotchas: collect(), Caching, and When Spark Loses

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