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Hadoop & Spark

Posted By: Sigha
Hadoop & Spark

Hadoop & Spark
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 8.4 GB
Genre: eLearning Video | Duration: 29 lectures (26 hour, 50 mins) | Language: English

Master the Hadoop ecosystem and Spark tutorial


What you'll learn

Hadoop & Spark

Requirements

N/A

Description

The world of Hadoop and "Big Data" can be intimidating - hundreds of different technologies with cryptic names form the Hadoop ecosystem. With this Hadoop tutorial, you'll not only understand what those systems are and how they fit together - but you'll go hands-on and learn how to use them to solve real business problems! “Big data" analysis is a hot and highly valuable skill – and this course will teach you two technologies fundamental to big data quickly: MapReduce and Hadoop

Understanding Hadoop is a highly valuable skill for anyone working at companies with large amounts of data.

Almost every large company you might want to work at uses Hadoop in some way, including Amazon, Ebay, Facebook, Google, LinkedIn, IBM, Spotify, Twitter, and Yahoo! And it's not just technology companies that need Hadoop; even the New York Times uses Hadoop for processing images.

Also, you will learn about how Spark works best when using the Scala programming language, and this course also includes Scala to get you up to speed quickly.

The course is aimed at Software Engineers, Database Administrators, and System Administrators that want to learn about Big Data. Other IT professionals can also take this course, but might have to do some extra research to understand some of the concepts. Once you complete the it, you'll walk away from this course with a real, deep understanding of Hadoop and its associated distributed systems, and you can apply Hadoop to real-world problems.

Below are the topics discussed:-

Part 1 :- Introduction

Part 2 :- Hadoop Architecture

Part 3 :- MapReduce

Part 4 :- Spark

Part 5 :- Spark Programming

Part 6 :- Scala

Who this course is for:

Hadoop & Spark

Hadoop & Spark


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