Study Guide for the Developer Certification for Apache Spark

Video description

Study Guide for the Developer Certification for Apache Spark

Video description

In this Study Guide for the Developer Certification for Apache Spark training course, expert author Olivier Girardot will teach you everything you need to know to prepare for and pass the Developer Certification for Apache Spark. This course is designed for users that are already familiar with Python, Java, and Scala.

You will start by learning about Apache Spark best practices, including transformations, actions, and joins. From there, Olivier will teach you about closure serialization, shared variables and performance, and Spark SQL. This video tutorial also covers Spark MLLib, Spark GraphX, and Spark streaming. Finally, you will learn about deployment and infrastructure.

Once you have completed this computer based training course, you will have learned the knowledge necessary to prepare for and pass the Spark Certification Exam. Working files are included, allowing you to follow along with the author throughout the lessons.

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Introduction

Introduction and Course Overview 00:04:10

About the Author 00:00:35

Spark’s concepts and approach 00:06:04

Resilient Distributed Databases (RDD) 00:05:03

Creating a Project in IDEA 00:02:54

Spark Core API & Best practices

Base RDD 00:06:46

Transformations 00:05:35

Actions - Part 1 00:01:40

Actions - Part 2 00:02:42

Hadoop Combiners In Spark 00:04:52

Direct Acyclic Graph And Lazy Evaluation 00:07:20

Joins 00:06:15

Closure serialization

How does the magic of Spark works 00:07:30

Serializers and how to change them 00:04:10

Shared variables and performance

Broadcast 00:04:07

Accumulators 00:05:05

Caching & Persistence 00:09:22

Spark SQL

Spark SQL 00:12:32

Inferring A Schema 00:07:38

Applying A Schema 00:06:27

Loading And Writing 00:06:07

SQL Caching And UDF 00:08:48

Spark MLLib

Spark MLLib And Supervised Example - SVM 00:10:02

Unsupervised With Iris Dataset - KMeans 00:08:54

Spark GraphX

Graph Construction 00:07:06

Graph Algorithms 00:06:52

Spark Streaming

Streaming And The Microbatch 00:13:57

Mutable Transformations And Checkpointing 00:09:07

Windows And RDD Transformations 00:08:43

Streaming With Spark SQL, MLLib And Core 00:12:28

Deployment and Infrastructure

Cluster Managers And Submission - Standalone, Mesos And Yarn 00:13:20

Conclusion

Resources And Where To Go From Here 00:04:06

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