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This course includes:

  • 3 hours on-demand video
  • 10 articles
  • 13 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Database Design & Development Hadoop

Java Parallel Computation on Hadoop

Learn to write real, working data-driven Java programs that can run in parallel on multiple machines by using Hadoop.
Rating: 4.6 out of 54.6 (110 ratings)
14,894 students
Created by Ivan Ng, Frahaan Hussain
Last updated 8/2014
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Know the essential concepts about Hadoop
  • Know how to setup a Hadoop cluster in pseudo-distributed mode
  • Know how to setup a Hadoop cluster in distributed mode (3 physical nodes)
  • Know how to develop Java programs to parallelize computations on Hadoop

Course content

12 sections • 43 lectures • 3h 2m total length

  • Preview01:01

  • Preview05:53
  • Requirements for the new approach
    03:17
  • Hadoop solving the limitations
    06:00

  • Overview of HDFS
    06:28
  • Overview of MapReduce
    08:12
  • Overview of Hadoop clusters
    03:58

  • Cloudera VM
    01:22
  • Demonstration: Using the VM
    01:02
  • Preview03:31
  • Tips about Shared Folders
    00:32
  • Accessing HDFS
    01:33
  • Running MapReduce
    02:44
  • Demonstration: Accessing HDFS
    04:35
  • Demonstration: Running MapReduce
    02:52
  • Demonstration: Web Console for HDFS
    02:58
  • Demonstration: Web Console for MapReduce
    01:33

  • About the Environment
    02:19
  • Setup the Master node - Exercise Manual
    6 pages
  • Setup the Slave node - Exercise Manual
    6 pages
  • Start the Master node - Exercise Manual
    2 pages
  • Start the Slave node - Exercise Manual
    2 pages

  • The Problem and Design
    04:39
  • Demonstration: Develop and Run the program
    13:31
  • Word Counting - Source Code
    00:05

  • The Problem and Design
    04:48
  • Demonstration: Develop and Run the program
    12:59
  • Data Sorting - Source Code
    00:05

  • The Problem and Design
    05:04
  • Demonstration: Develop and Run the program
    11:52
  • Pattern Searching - Source Code
    00:05

  • The Problem and Design
    04:37
  • Demonstration: Develop and Run the program
    10:54
  • Item Co-occurrence - Source Code
    00:05

  • The Problem and Design
    04:22
  • Demonstration: Develop and Run the program
    15:25
  • Inverted Index - Source Code
    00:05

Requirements

  • An understanding of the Java programming language

Description

Build your essential knowledge with this hands-on, introductory course on the Java parallel computation using the popular Hadoop framework:

- Getting Started with Hadoop

- HDFS working mechanism

- MapReduce working mecahnism

- An anatomy of the Hadoop cluster

- Hadoop VM in pseudo-distributed mode

- Hadoop VM in distributed mode

- Elaborated examples in using MapReduce

Learn the Widely-Used Hadoop Framework

Apache Hadoop is an open-source software framework for storage and large-scale processing of data-sets on clusters of commodity hardware. Hadoop is an Apache top-level project being built and used by a global community of contributors and users. It is licensed under the Apache License 2.0.

All the modules in Hadoop are designed with a fundamental assumption that hardware failures (of individual machines, or racks of machines) are common and thus should be automatically handled in software by the framework. Apache Hadoop's MapReduce and HDFS components originally derived respectively from Google's MapReduce and Google File System (GFS) papers.

Who are using Hadoop for data-driven applications?

You will be surprised to know that many companies have adopted to use Hadoop already. Companies like Alibaba, Ebay, Facebook, LinkedIn, Yahoo! is using this proven technology to harvest its data, discover insights and empower their different applications!

Contents and Overview

As a software developer, you might have encountered the situation that your program takes too much time to run against large amount of data. If you are looking for a way to scale out your data processing, this is the course designed for you. This course is designed to build your knowledge and use of Hadoop framework through modules covering the following:

- Background about parallel computation

- Limitations of parallel computation before Hadoop

- Problems solved by Hadoop

- Core projects under Hadoop - HDFS and MapReduce

- How HDFS works

- How MapReduce works

- How a cluster works

- How to leverage the VM for Hadoop learning and testing

- How the starter program works

- How the data sorting works

- How the pattern searching

- How the word co-occurrence

- How the inverted index works

- How the data aggregation works

- All the examples are blended with full source code and elaborations

Come and join us! With this structured course, you can learn this prevalent technology in handling Big Data.

Who this course is for:

  • IT Practitioners
  • Software Developers
  • Software Architects
  • Programmers
  • Data Analysts
  • Data Scientists

Instructors

Ivan Ng
Instructor on Emerging Technologies
Ivan Ng
  • 4.6 Instructor Rating
  • 110 Reviews
  • 14,894 Students
  • 1 Course

Along my path working as a software architect in the last 15 years for different products like Learning Management System, Online Game, RFID-based warehousing systems and high-frequency advertising systems for companies like Prudential, AXA, Bank of China, I also delivered numerous training on a wide range of IT related topics for more than 10 years - topics include Big Data, Mobility, Front-end Engineering, Cloud Computing, Server Architecture and Data Analytic - for different institutes like HP Education, Oracle Education, Hong Kong Open University of Hong Kong, Chinese University of Hong Kong.

I enjoy the time interacting with the participants and understand the practical requirements encountered under different needs.

I have my first master degree in Information Technology and the 2nd master degree in Quantitative Finance.

Frahaan Hussain
CEO and Lead Developer at Sonar Systems
Frahaan Hussain
  • 3.9 Instructor Rating
  • 14,167 Reviews
  • 534,462 Students
  • 100 Courses

I am CEO of Sonar Systems which is the world leader in educational material for the game engine Cocos2d-x, one of the best and most popular game engines in the world. With years of experience programming and running an online education platform (Sonar Learning) I can help and support new programming like you.

I am also a University Lecturer teaching a variety of topics in Games Programming from Games Design to OpenGL Shader Programming.

I am also a published author of games design and soon to be released Responsive Web Design. I have all the facets required to educate and inspire.

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