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Big Data and Hadoop Online Training
Rated 5/5 based on 179 customer reviews

Big Data And Hadoop Online Training

  • 179 Reviews
  • 6891 students enrolled
  • 6 audio-visual modules that cover all fundamentals of Hadoop 2.0
  • Mobile user friendly content
  • High quality e-learning content developed by industry experts
  • Free downloadable courseware
  • Simulations for easy understanding
  • 100% money back guarantee if dissatisfied within 1 hour of learning access

Description

Companies around the world today find it increasingly difficult to organize and manage large volumes of data. Hadoop has emerged as the most efficient data platform for companies working with big data, and is an integral part of storing, handling and retrieving enormous amounts of data in a variety of applications. Hadoop helps to run deep analytics which cannot be effectively handled by a database engine.

Big enterprises around the world have found Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also growing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.

Our three day course in Hadoop 2.0 Developer training will teach you the technical aspects of Apache Hadoop, and you will obtain a deeper understanding of the power of Hadoop. Our experienced trainers will handhold you through the development of applications and analyses of Big Data, and you will be able to comprehend the key concepts required to create robust big data processing applications. Successful candidates will earn the credential of Hadoop Professional, and will be capable of handling and analysing Terabyte scale of data successfully using MapReduce.

curriculum

Section 1 : Course Overview

About BIG DATA HADOOP (2.0) DEVELOPMENT Course
00:03:06
Hadoop and Hadoop Ecosystem Course Objectives
00:00:33
What is Big Data?
00:00:48
Characteristics of Big Data
00:02:01
Next Logical Questions
00:01:37

Section 2 : Hadoop and Hadoop Ecosystem

What is Hadoop?
00:02:40
How Hadoop works?
00:02:12
How HDFS works
00:02:43
Example Program: Word Count
00:02:47
Shuffle and Start
00:03:29
Hadoop Job Process
00:01:40
Problems with Typical Distributed Systems
00:01:12
How Failures are handled
00:00:44
SQOOP
00:00:44
How Sqoop works
00:01:14
What is Oozie
00:00:45
How Oozie works
00:00:21
Oozie Example
00:01:12
What is Pig
00:01:06
Pig Example
00:00:45
What is Flume
00:00:26
How Flume works
00:00:57
How Flume works - Continued
00:01:46
What is Hive
00:00:58
Hive Example
00:01:00
HDFS Storage Mechanism
00:00:57
HDFS: Important Points
00:00:42
HDFS Closer Look: How files are stored
00:01:13
How files are written to HDFS(Part-1)
00:00:37
How files are written to HDFS(Part-2)
00:00:25
Few Examples
00:01:19
What is Mapper
00:01:01
How MapReduce works
00:01:58
A Note on Daemons
00:01:22

Section 3 : Pig and Hive

Introduction to Pig and Hive
00:01:41
The Hive Data Model
00:02:00
Hive Basics
00:03:50
Pig Basics
00:06:14

Section 4 : Advanced Map Reduce

Advanced Map Reduce Overview
00:01:43
Testing with MR Unit
00:01:54
JUnit Basics - Continued
00:01:26
MRUnit: Example Code
00:02:50
MR Unit Drivers - Continued
00:04:26
The Configure Method
00:00:53
Passing Parameters
00:00:53
Accessing HDFS Programmatically
00:02:53
Using the Distributed Cache
00:03:32

Section 5 : Cluster Planning

Cluster Planning Overview
00:02:19
Planning your Hadoop Cluster
00:03:36
Network Considerations
00:01:25
Important Configurations
00:01:29
Hadoop Configs
00:02:25
Quick Summary of Configs
00:01:39
Hands On Resource Download link
00:00:30

Section 6 : Hands On using Hadoop 2.0

Getting Started
00:17:12
Installing Hadoop in a pseudo distributed mode
00:22:34
Accessing HDFS from command line
00:05:18
Running the Word Count Map Reduce Job
00:23:38
Mini Project: Importing MySQL Data using Sqoop and Querying it using Hive
00:18:55
Setting up FLUME
00:09:29
Setting up Multi-node Cluster
00:08:06

What you get

Perform real-world data analysis using advanced Hadoop API topics.

Implement industry best practices for Hadoop development, debugging techniques and implementation of workflows and common algorithms.

Retrieve information in concise and cost effective manner.

Navigate, set up and run Hadoop command and queries.

Retrieve a gold mine of information from unstructured data.

Process large data sets with the Hadoop ecosystem.

Describe the path to ROI with Hadoop.

Explain the Hadoop frameworks like ApachePigā„¢, ApacheHiveā„¢, Sqoop, Flume, Oozie and other projects from the Apache Hadoop Ecosystem.

Boost their career in the field of high-value analytics.

Certification

Eligibility: There are no prerequisites to take this course but prior basic knowledge of Java and Linux will help.

USD 170

Access Days

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