Java Multithreading and Parallel Programming Masterclass - [Project] - Simulating a MapReduce Job with Threads - Part 1

This lecture introduces the concept of big data and distributed processing, focusing on the MapReduce programming model. It explains how data is distributed across clusters using HDFS and describes the three main steps of a MapReduce job: map, shuffle, and reduce operations. A word count example is used to illustrate these concepts. The lecture also simulates a MapReduce job using threads to demonstrate the importance of synchronization in parallel processing.

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