07 - Apache Spark for Java Developers - Cluster Mode Overview

@backstreetbrogrammer

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Chapter 01 - Apache Spark for Java Developers - Cluster Mode Overview
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Spark applications run as independent sets of processes on a cluster, coordinated by the SparkContext object in our main program (called the driver program).

Specifically, to run on a cluster, the SparkContext can connect to several types of cluster managers (either Spark’s own standalone cluster manager, Mesos, YARN or Kubernetes), which allocate resources across applications. Once connected, Spark acquires executors on nodes in the cluster, which are processes that run computations and store data for our application. Next, it sends our application code (defined by JAR or Python files passed to SparkContext) to the executors. Finally, SparkContext sends tasks to the executors to run.

Github: https://github.com/backstreetbrogrammer/11_JavaSpark

- Apache Spark for Java Developers Playlist: https://youtube.com/playlist?list=PLQDzPczdXrTgqEc0uomGYDS0SFu7qY3g3
- Java Serialization Playlist: https://youtube.com/playlist?list=PLQDzPczdXrTjGLkI8kd2d0bfNHx0v7dTy
- Dynamic Programming Playlist: https://youtube.com/playlist?list=PLQDzPczdXrTilRgmNUQ632OrD-wfRLUR_

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