HADOOP TRAINING

Hadoop Online Training

Duration of       Hours 

HRS

Duration time may vary depends on course progress

Training Objectives of Hadoop:

Hadoop Course will provide the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action. This course will further examine related technologies such as Hive, Pig, and Apache Accumulo.


Target Students / Prerequisites:

Students must be belonging to IT Background and familiar with Concepts in Java and Linux.

Course Content

Introduction, The Motivation for Hadoop:


  • Problems with traditional large-scale systems


  • Requirements for a new approach



Hadoop Basic Concepts:


  • An Overview of Hadoop


  • The Hadoop Distributed File System


  • Hands-on Exercise


  • How MapReduce Works


  • Hands-on Exercise


  • Anatomy of a Hadoop Cluster


  • Other Hadoop Ecosystem Components



Writing a MapReduce Program:


  • Examining a Sample MapReduce Program


  • With several examples


  • Basic API Concepts


  • The Driver Code


  • The Mapper


  • The Reducer


  • Hadoop’s Streaming API



Delving Deeper Into The Hadoop API:


  • More About ToolRunner


  • Testing with MRUnit


  • Reducing Intermediate Data With Combiners


  • The configure and close methods for Map/Reduce Setup and Teardown


  • Writing Partitioners for Better Load Balancing


  • Hands-On Exercise


  • Directly Accessing HDFS


  • Using the Distributed Cache


  • Hands-On Exercise



Performing several Hadoop jobs:


  • The configure and close Methods


  • Sequence Files


  • Record Reader


  • Record Writer


  • Role of Reporter


  • Output Collector


  • Processing video files and audio files


  • Processing image files


  • Processing XML files


  • Counters


  • Directly Accessing HDFS


  • ToolRunner


  • Using The Distributed Cache



Common MapReduce Algorithms:


  • Sorting and Searching


  • Indexing


  • Classification/Machine Learning


  • Term Frequency-Inverse Document Frequency


  • Word Co-Occurrence


  • Hands-On Exercise: Creating an Inverted Index


  • Identity Mapper


  • Identity Reducer


  • Exploring well known problems using MapReduce applications



Using HBase:


  • What is HBase?


  • HBase API


  • Managing large data sets with HBase


  • Using HBase in Hadoop applications


  • Hands-on Exercise


Using Hive and Pig:


  • Hive Basics


  • Pig Basics


  • Hands-on Exercise


  • Practical Development Tips and Techniques


  • Debugging MapReduce Code


  • Using LocalJobRunner Mode for Easier Debugging


  • Retrieving Job Information with Countries


  • Logging


  • Splittable File Formats


  • Determining the Optimal Number of Reducers


  • Map-Only MapReduce Jobs


  • Hands-on Exercise



Debugging MapReduce Programs:


  • Testing with MRUnit


  • Logging


  • Classification/Machine Learning


  • Advanced MapReduce Programming


  • A Recap of the MapReduce Flow


  • The Secondary Sort


  • CustomizedInputFormats and OutputFormats


  • Pipelining Jobs With Oozie


  • Map-Side Joins


  • Reduce-Side Joins



Joining Data Sets in MapReduce:


  • Map-Side Joins


  • The Secondary Sort


  • Reduce-Side Joins



Monitoring and debugging on a Production Cluster:


  • Counters


  • Skipping Bad Records


  • Rerunning failed tasks with Isolation Runner



Tuning for Performance in MapReduce:


  • Reducing network traffic with combiner


  • Partitioners


  • Reducing the amount of input data


  • Using Compression


  • Reusing the JVM


  • Running with speculative execution


  • Refactoring code and rewriting algorithms Parameters affecting Performance


  • Other Performance Aspects

Have some Questions?

Call us at our care or drop quick contact box

Why with us?
  • Live Quality Training 

  • Live demonstration of of features and practicals.

  • 100% Assurance Placement Assistance

  • Effective Resume building

  • Internship Program for real exposure

  • Interview preparation with mock interview drills

  • Process of applying jobs at right places

  • Guidance of getting flexible, part time jobs

Our chanel partners : AlightPro | Career ITS

© Copyright © 2008 ProCareer Inc. All rights reserved.