Hadoop Developer


Apache Hadoop is the open source data management software that helps organizations analyze huge volumes of structured and unstructured data, is a very hot topic across the tech industry. It can be quickly learn to take advantage of the MapReduce framework through technical sessions and hands on labs.
by mithun-reddy
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Hadoop

KEY FEATURES

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Experienced and certified trainers with real time project experience.

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35-40 Interactive online training sessions.

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In-house course content and with consistent course structure and design

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Exclusive Student Portal

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Weekly Assessments

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Learn Anytime and Anywhere

Overview

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.

Pre-Requisites

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

Introduction to Big data and Hadoop

  • Understanding Big Data
  • Challenges in processing Big Data
  • 3V Characteristics (Volume, Variety and Velocity)
  • Brief history of Hadoop
  • How Hadoop addresses Big Data?
  • HDFS and MR
  • Hadoop echo system

5 Daemons processes Map Reduce

  • Map Reduce Basics
  • Map Reduce Data Flow
  • Word count Example solving
  • Algorithms for simple and complex problems
  • Hadoop Streaming

HDFS (Hadoop Distributed File System)

  •  HDFS Overview and Architecture
  • HDFS Keywords like Name Node, Data
  • Node, Heart Beat etc
  • Configuring HDFS
  • Data Flows (Read and Write)
  • HDFS Permissions and Security
  • HDFS commands
  • Rack Awareness

Developing a Map Reduce Application

  • Setting up working environment
  • Custom Data types (Writable and Custom Key types)
  • Input and Output file formats
  • Driver, Mapper and Reducer Code Wal thru
  • Configuring IDE Eclipse
  • Writing Unit test and running locally
  • Map Reduce Web UI
  • Hands -on

How Map Reduce works?

  • Classic Map Reduce (Map Reduce I)
  • YARN (Map Reduce II)
  • Job Scheduling
  • Shuffle and Sort
  • Failures
  • Oozie Workflows
  • Hands-on Excercises

How Map Reduce works?

  • Map Reduce Types
  • Input formats – Input splits & records, text input, binary input, multiple inputs and database input.
  • Output formats – text output, binary output, multiple outputs, Lazy output and database output.
  • Hands-on

Hadoop Echo Systems PIG

  • Overview of PIG
  • Installation and running PIG
  • PIG Latin
  • Loading and storing data
  • Hands-on

HIVE

  • Overview of HIVE
  • Installation and running HIVE
  • HiveQL
  • Tables
  • Hands-on

HBASE

  • Overview of HBASE Installation  CLinets (avro, REST, Thrift)
  • Hands-on

Overview of SQOOP

  • Solving Case studies
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Front-End JavaScript Frameworks: AngularJs

About this course: This course concentrates mainly on Javascript based front-end frame-works, And in particular, AngularJs is, The most popular among them. We will review the model view controller(MVC) design-pattern in the context of AngularJs

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