Apache Spark in 4 Minutes: MapReduce, RDD, and In-Memory Processing Explained
In 2004, Google introduced MapReduce. Yahoo ran with it. For a while, everyone did too.
Then the cracks showed up, strict paradigms, disk-based exchanges, no good fit for machine learning or interactive queries. UC Berkeley's AMPLab noticed. They built Apache Spark.
In this video, I break down how Spark works under the hood:
→ What MapReduce got right (and where it fell short)
→ What RDD actually is, and why it's immutable by design
→ How lazy evaluation works: transformations vs actions
→ How Spark recovers from failures without writing to disk
No hype. Just the concepts, explained clearly.
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