Apache Hadoop Architecture Development and Administration

This course equips you with the knowledge and skills to become an
Apache Hadoop Developer.

Course Duration: 4 days (full-time) 

Daytime Classes | Evening Classes | Virtual & Online Classes                                                        

   

You will learn to…

Understand the concept of HDFS and MapReduce framework

Develop robust data processing applications

Write Hadoop codes

Learn best practice in a Hadoop development environment

About this course

This course equips you with the knowledge and skills to become an Apache Hadoop Developer. You will be exposed to different industry use case scenarios, the core concepts (HDFS and MapReduce) and implementation of Hadoop, how to develop robust data processing applications, MapReduce and how to write MapReduce codes, and Hadoop Distributed Files System (HDFS). You will also learn best practice Hadoop Development, debugging and implementation of workflows.

4 Benefits of booking this course with us

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HOW DO YOU LIKE TO ATTEND?
With a strong presence in all the main sites across of UK, Pairview dedicate all the efforts to deliver the most full superior learning experience. Our Education Centre classrooms are designed to provide a unique, inspiring and secure learning environment . Our experienced trainers take our delegates to the next level, supporting all their needs, giving them the skills-set to be ahead of the most in-demand tools of this field.

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IN-Class

Enjoy a broad choice of courses/ classes and dates – choose from all available of dates and course events anywhere in the UK. Choose one of the Pairview’s site classrooms across of UK to have your training classes. Our classrooms are designed to leverage sophisticated training technology with LIVE virtual classes in order to give you the most live and superior learning experience.

With our virtual classes you can attend to all training sessions in any Pairview’s site classrooms. You will be LIVE in the session and you will be able to communicate easily in real time with your course instructor and classmates – ask questions, get clarification and contribute your insights – everything with live voice and image.


Online – via AnyWhere

Attend all the training sessions Online – via AnyWhere. Control an LIVE in-class computer using our own Pairview’s interface. You will be able to communicate easily in real time with your course instructor and classmates – ask questions, get clarification and contribute your insights – everything with live voice and image. Your instructor will be able to see exactly how you’re doing and can interactively support you at the moment just like in a classroom.

You Can be in your home or in the other part of the world. With this solution you can attend all the Training Courses online – via AnyWhere.

Avoid long journeys to attend your training sessions in some particular site, save your time and your money with this singular option.

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Testimonials

“The facilitator is very knowledgeable with years of experience, the course delivery was exceptional.”
Anonymous, Course Feedback Form

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Course Content

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  1. Introduction

2. The Motivation for Hadoop

  • Problems with Traditional Large-Scale Systems
  • Introducing Hadoop
  • Hadoopable Problems
  1. Hadoop: Basic Concepts and HDFS
  • The Hadoop Project and Hadoop Components
  • The Hadoop Distributed File System
  1. Introduction to MapReduce
  • MapReduce Overview
  • Example: WordCount
  • Mappers
  • Reducers
  1. Hadoop Clusters and the Hadoop Ecosystem
  • Hadoop Cluster Overview
  • Hadoop Jobs and Tasks
  • Other Hadoop Ecosystem Components
  1. Writing a MapReduce Program in Java
  • Basic MapReduce API Concepts
  • Writing MapReduce Drivers, Mappers, and Reducers in Java
  • Speeding Up Hadoop Development by Using Eclipse
  • Differences between the Old and New MapReduce APIs
  1. Writing a MapReduce Program using Streaming
  • Writing Mappers and Reducers with the Streaming API
  • Unit Testing MapReduce Programs
  • Unit Testing
  • The JUnit and MRUnit Testing Frameworks
  • Writing Unit Tests with MRUnit
  • Running Unit Tests
  1. Delving Deeper into the Hadoop API
  • Using the ToolRunner Class
  • Setting Up and Tearing Down Mappers and Reducers
  • Decreasing the Amount of Intermediate Data with Combiners
  • Accessing HDFS Programmatically
  • Using the Distributed Cache
  • Using the Hadoop API’s Library of Mappers, Reducers, and Partitioners
  1. Practical Development Tips and Techniques
  • Strategies for Debugging MapReduce Code
  • Testing MapReduce Code Locally by Using LocalJobRunner
  • Writing and Viewing Log Files
  • Retrieving Job Information with Counters
  • Reusing Objects
  • Creating Map-Only MapReduce Jobs
  1. Partitioners and Reducers
  • How Partitioners and Reducers Work Together
  • Determining the Optimal Number of Reducers for a Job
  • Writing Customer Partitioners
  1. Data Input and Output
  • Creating Custom Writable and WritableComparable Implementations
  • Saving Binary Data Using SequenceFile and Avro Data Files
  • Issues to Consider When Using File Compression
  • Implementing Custom InputFormats and OutputFormats
  1. Common MapReduce Algorithms
  • Sorting and Searching Large Data Sets
  • Indexing Data
  • Computing Term Frequency — Inverse Document Frequency
  • Calculating Word Co-Occurrence
  • Performing Secondary Sort
  1. Joining Data Sets in MapReduce Jobs
  • Writing a Map-Side Join
  • Writing a Reduce-Side Join
  1. Integrating Hadoop into the Enterprise Workflow
  • Integrating Hadoop into an Existing Enterprise
  • Loading Data from an RDBMS into HDFS by Using Sqoop
  • Managing Real-Time Data Using Flume
  • Accessing HDFS from Legacy Systems with FuseDFS and HttpFS
  1. An Introduction to Hive, Imapala and Pig
  • The Motivation for Hive, Impala, and Pig
  • Hive Overview
  • Impala Overview
  • Pig Overview
  • Choosing Between Hive, Impala, and Pig
  1. An Introduction to Oozie
  • Introduction to Oozie
  • Creating Oozie Workflows
Developers who need to write and maintain Apache Hadoop applications.

£1,980 per person, ex VAT

£1,683 per person, ex VAT