BigData and Hadoop Training Content

Big Data and Hadoop 
1.	What is Big Data?
2.	5 Vs of Big Data
3.	Big Data Architecture, Technologies, Challenge and Big Data Requirements
4.	Big Data Distributed Computing and Complexity
5.	Hadoop
6.	Map Reduce Framework
7.	Hadoop Ecosystem
Big Data and Hadoop Introduction
1.	What is Big Data and Hadoop?
2.	Challenges of Big Data
3.	Traditional approach Vs Hadoop
4.	Hadoop Architecture
5.	Distributed Model
6.	Block structure File System
7.	Technologies supporting Big Data
8.	Replication
9.	Fault Tolerance
10.	Why Hadoop?
11.	Hadoop Eco-System
12.	Use cases of Hadoop
13.	Fundamental Design Principles of Hadoop
14.	Comparison of Hadoop Vs RDBMS
Understand Hadoop Cluster Architecture
1.	Hadoop Cluster and Architecture
2.	5 Daemons
3.	Hands-On Exercise
4.	Typical Workflow
5.	Hands-On Exercise
6.	Writing Files to HDFS
7.	Hands-On Exercise
8.	Reading Files from HDFS
9.	Hands-On Exercise
10.	Rack Awareness
11.	Before Map Reduce
Map Reduce Concepts
1.	Map Reduce Concepts
2.	What is Map Reduce?
3.	Why Map Reduce?
4.	Map Reduce in real world  and Map Reduce Flow
5.	What is Mapper,  Reducer, and Shuffling?
6.	Word Count Problem
7.	Hands-On Exercise
8.	Distributed Word Count Flow and Solution
9.	Log Processing and Map Reduce
10.	Hands-On Exercise
Advanced Map Reduce Concepts
1.	What is Combiner?
2.	What is Partitioner?
3.	What is Counter?
4.	InputFormats/Output Formats
5.	Map Join using MR
6.	Reduce Join using MR
7.	MR Distributed Cache
8.	Using sequence files & images with MR
9.	Planning for Cluster & Hadoop 2.0 Yarn
10.	Configuration of Hadoop
11.	Choosing Right Hadoop Hardware and Software?
12.	Hadoop Log Files?
Hadoop 2.0 and YARN
1.	Hadoop 1.0 Challenges
2.	NN Scalability, SPOF, and HA
3.	Job Tracker Challenges
4.	Hadoop 2.0 New Features
5.	Hadoop 2.0 Cluster Architecture & Federation
6.	Hadoop 2.0 HA
7.	Yarn & Hadoop Ecosystem
8.	Yarn MR Application Flow
PIG
1.	Introduction to Pig
2.	What Is Pig?
3.	Pigâ??s Features & Pig Use Cases
4.	Interacting with Pig
5.	Basic Data Analysis with Pig
6.	Pig Latin Syntax
7.	Loading Data
8.	Simple Data Types
9.	Field Definitions
10.	Data Output
11.	Viewing the Schema
12.	Filtering and Sorting Data
13.	Commonly-Used Functions
14.	Pig for ETL Processing
15.	Processing Complex Data with Pig
16.	Storage Formats
17.	Complex/Nested Data Types
18.	Hands-On Exercise
19.	Grouping
20.	Built-in Functions for Complex Data
21.	Iterating Grouped Data
22.	Multi-Dataset Operations with Pig
23.	Techniques for Combining Data Sets
24.	Joining Data Sets in Pig
25.	Splitting Data Sets
HIVE
1.	Hive Fundamentals and Architecture
2.	Loading and Querying Data in Hive
3.	Hive Architecture and Installation
4.	Comparison with Traditional Database
5.	HiveQL: Data Types, Operators and Functions
6.	Hive Tables, Managed Tables and External Tables
Hadoop Developer Training Outline
 Introduction to Hadoop 

o	Hadoop Distributed File System 
o	Hadoop Architecture 
o	MapReduce & HDFS Hadoop Eco Systems 
o	Introduction to Pig
o	Introduction to Hive 
o	Introduction to HBase
o	Other eco system Map Hadoop Developer
o	Moving the Data into Hadoop 
o	Moving The Data out from Hadoop 
o	Reading and Writing the files in HDFS using java program
o	The Hadoop Java API for MapReduce o Mapper Class o Reducer Class o Driver Class
o	Writing Basic MapReduce Program In java
o	Understanding the MapReduce Internal Components
o	Hbase MapReduce Program 
o	Hive Overview
o	Working with Hive
o	Pig Overview 
o	Working with Pig
o	Sqoop Overview
o	Moving the Data from RDBMS to Hadoop 
o	Moving the Data from RDBMS to Hbase
o	Moving the Data from RDBMS to Hive 
o	Flume Overview 
o	Moving The Data from Web server Into Hadoop
o	Real Time Example in Hadoop
o	Apache Log viewer Analysis
 Hadoop Admin Training Outline 
o	Big Data Overview
o	Introduction In Hadoop and Hadoop Related Eco System.
o	Choosing Hardware For Hadoop Cluster nodes 
o	Apache Hadoop Installation o Standalone Mode o Pseudo Distributed Mode o Fully Distributed Mode
o	Installing Hadoop Eco System and Integrate With Hadoop
o	Zookeeper Installation o Hbase Installation o Hive Installation o Pig Installation o Sqoop Installation o Installing Mahout 
o	Horton Works Installation 
o	Cloudera Installation
o	Hadoop Commands usage 
o	Import the data in HDFS
o	Sample Hadoop Examples (Word count program and Population problem)
o	Monitoring The Hadoop Cluster o Monitoring Hadoop Cluster with Ganglia o Monitoring Hadoop Cluster with Nagios o Monitoring Hadoop Cluster with JMX
o	Hadoop Configuration management Tool
o	Hadoop Benchmarking

Key Features

60 Hours of Learning

online | Classroom | Corporate
Learning.

Job Placement Assistance

Based on performance of candidate in training batch, will be placed in our company projects.

2+ Practical Hands-On Projects

After course completion sample projects will be shared by trainers.

Flexible Schedules

Weekdays, Weekend, Classroom batches only in hyderabad location are available.

Support

Job support will be provided until student will work independently. Can be added in technical what sapp groups.

Modes of Training

CLASS ROOM TRAINING
  • Links / Blog link will be shared
  • Real time scenarios/ use cases will be covered in training
ONLINE TRAINING
  • Daily assignment will be given
  • Daily session recording videos access will be given for 90 days
CORPORATE TRAINING
  • Experienced corporate faculty is available
  • Interview questions, material will be provided in training