Скачать или смотреть Getting Started with Scala and Apache Spark | Ch 3b - MapReduce in Big Data Ecosystem | PySpark

This video is continuation of chapter 3a where we show the same implementation in Python using PySpark.

In Chapter 3 of our Scala and Spark Big Data series, we explore the powerful reduce operation—a core concept in functional programming and distributed computing frameworks like Spark. This tutorial covers how to aggregate and summarize data using the reduce operation and introduces the role of caching in Spark to optimize performance.

In this video, you'll learn:

What the reduce operation is and how it works in Spark
How to use reduce for common operations like summing and finding the maximum
The MapReduce model and its role in distributed data processing
Practical examples of reduce in Spark with Scala
How caching in Spark can improve performance by storing intermediate results in memory
Make sure to watch the entire video for hands-on examples, and don’t forget to like, comment, and subscribe for more Spark tutorials in this series!

Github Repo: https://github.com/sedhha/scala_spark...