Hadoop Developer training in usa | Administration training

Hadoop Developer Course Content:

Course Content:

• How MapReduce and the Hadoop Distributed File System work
• How to write MapReduce code in Java or other programming languages
• What issues to consider when developing MapReduce jobs
• How to implement common algorithms in Hadoop
• Best practices for Hadoop development and debugging
• How to leverage other project such as Apache Hive, Apache Pig, Sqoop and Oozie
• Advanced Hadoop API topics required for real-world data analysis

Outline

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

• The MapReduce Flow
• Examining a Sample MapReduce Program
• Basic MapReduce API Concepts
• The Driver Code
• The Mapper
• The Reducer
• Hadoop’s Streaming API
• Using Eclipse for Rapid Development
• Hands-on exercise
• The New MapReduce API

Integrating Hadoop into the Workflow

• Relational Database Management Systems
• Storage Systems
• Importing Data from RDBMSs With Sqoop
• Hands-on exercise
• Importing Real-Time Data with Flume
• Accessing HDFS Using FuseDFS and Hoop

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

Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• 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 Counters
• Logging
• Splittable File Formats
• Determining the Optimal Number of Reducers
• Map-Only MapReduce Jobs
• Hands-On Exercise

Joining Data Sets in MapReduce

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• You can attend 1st 2 classes or 3 hours for free. once you like the classes then you can go for registration.
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• or full course details please visit our website www.hadooponlinetraining.net
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• Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
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• * Resume preparation and Interview assistance will be provided. 
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• For any further details please contact 
• INDIA: +91-9052666559 
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• USA: +1-6786933475
 or 
• visit www.hadooponlinetraining.net
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• please mail us all queries to info@magnifictraining.com