Hadoop online training in hyderabad

                       Hadoop is an open source software project that enables the distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software’s ability to detect and handle failures at the application layer.

      Hadoop is supplemented by an ecosystem of Apache projects, such as Pig, Hive and Zookeeper, that extend the value of Hadoop and improves its usability.

Hadoop enables a computing solution that is:

Scalable– New nodes can be added as needed, and added without needing to change data formats, how data is loaded, how jobs are written, or the applications on top.

.Cost effective– Hadoop brings massively parallel computing to commodity servers. The result is a sizeable decrease in the cost per terabyte of storage, which in turn makes it affordable to model all your data

Flexible– Hadoop is schema-less, and can absorb any type of data, structured or not, from any number of sources. Data from multiple sources can be joined and aggregated in arbitrary ways enabling deeper analyses than any one system can provide

Fault tolerant– When you lose a node, the system redirects work to another location of the data and continues processing without missing a fright beat.

Rs Training's : is a brand and providing quality online and offline training's for students in world wide. Rs Training's providing Best Hadoop online training in Hyderabad.

RS TRAINING'S: Interactive training from Technological mavens to groom learners into technological aces.

RS TRAINING'S is an outstanding ONLINE IT TRAINING and CLASSROOM IT TRAINING institute with State of Art infrastructure led by the finest trainers in the market. We offer Online training to the learners in all parts of the world with the implementation of modern technologies like Gotomeeting and Web Ex.

    Our trainers are Domain experts with a proven experience of at least a decade in the real time environment. We believe in the policy that “Learning is the virtue of success in life”.The flexible course curriculum designed at RS TRAINING'S will be up to date in the technological race and be able to cater the requirement of both fresher’s and Professionals. Be it Corporate training or Online Training or Classroom Training for Hadoop ,RS TRAINING'S is elite and provides accomplished training services to cater the client needs.

Course Content:

Course Objective Summary

During this course, you will learn:

• Introduction to Big Data and Analytics
• Introduction to Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
• Pig concepts
• Hive concepts
• Sqoop concepts
• Flume Concepts
• Oozie workflow concepts
• Impala Concepts
• Hue Concepts
• HBASE Concepts
• ZooKeeper Concepts
• Real Life Use Cases

Reporting Tool

• Tableau 

1. Virtualbox/VM Ware

• Basics
• Installations
• Backups
• Snapshots

2. Linux

• Basics
• Installations
• Commands

3. Hadoop 

• Why Hadoop?
• Scaling
• Distributed Framework
• Hadoop v/s RDBMS
• Brief history of hadoop

4. Setup hadoop 

• Pseudo mode
• Cluster mode
• Ipv6
• Ssh
• Installation of java, hadoop
• Configurations of hadoop
• Hadoop Processes ( NN, SNN, JT, DN, TT)
• Temporary directory
• UI
• Common errors when running hadoop cluster, solutions

5. HDFS- Hadoop distributed File System

• HDFS Design and Architecture
• HDFS Concepts
• Interacting HDFS using command line
• Interacting HDFS using Java APIs
• Dataflow
• Blocks
• Replica

6. Hadoop Processes

• Name node
• Secondary name node
• Job tracker
• Task tracker
• Data node

7. Map Reduce

• Developing Map Reduce Application
• Phases in Map Reduce Framework
• Map Reduce Input and Output Formats
• Advanced Concepts
• Sample Applications
• Combiner

8. Joining datasets in Mapreduce jobs

• Map-side join
• Reduce-Side join

9. Map reduce – customization

• Custom Input format class
• Hash Partitioner
• Custom Partitioner
• Sorting techniques
• Custom Output format class

10. Hadoop Programming Languages :-

I.HIVE

• Introduction
• Installation and Configuration
• Interacting HDFS using HIVE
• Map Reduce Programs through HIVE
• HIVE Commands
• Loading, Filtering, Grouping….
• Data types, Operators…..
• Joins, Groups….
• Sample programs in HIVE

II. PIG 

• Basics
• Installation and Configurations
• Commands….

OVERVIEW HADOOP DEVELOPER

11. Introduction

12. The Motivation for Hadoop

• Problems with traditional large-scale systems
• Requirements for a new approach

13. 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

14. 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

15. Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise.

16.PIG Concepts..

• Data loading in PIG.
• Data Extraction in PIG.
• Data Transformation in PIG.
• Hands on exercise on PIG.

17. Hive Concepts.

• Hive Query Language.
• Alter and Delete in Hive.
• Partition in Hive.
• Indexing.
• Joins in Hive.Unions in hive.
• Industry specific configuration of hive parameters.
• Authentication & Authorization.
• Statistics with Hive.
• Archiving in Hive.
• Hands-on exercise

18. Working with Sqoop

• Introduction.
• Import Data.
• Export Data.
• Sqoop Syntaxs.
• Databases connection.
• Hands-on exercise

19. Working with Flume

• Introduction.
• Configuration and Setup.
• Flume Sink with example.
• Channel.
• Flume Source with example.
• Complex flume architecture.

20. OOZIE Concepts
21. IMPALA Concepts
22. HUE Concepts
23. HBASE Concepts
24. ZooKeeper concepts

Reporting Tool..

Tableau

This course is designed for the beginner to intermediate-level Tableau user. It is for anyone who works with data – regardless of technical or analytical background. This course is designed to help you understand the important concepts and techniques used in Tableau to move from simple to complex visualizations and learn how to combine them in interactive dashboards.

Course Topics

Overview

• What is visual analysis?
• Strengths/weakness of the visual system.

Laying the Groundwork for Visual Analysis

• Analytical Process
• Preparing for analysis

Getting, Cleaning and Classifying Your Data

• Cleaning, formatting and reshaping.
• Using additional data to support your analysis.
• Data classification

Visual Mapping Techniques

• Visual Variables : Basic Units of Data Visualization
• Working with Color
• Marks in action: Common chart types

Solving Real-World Problems with Visual Analysis

• Getting a Feel for the Data- Exploratory Analysis.
• Making comparisons
• Looking at (co-)Relationships.
• Checking progress.
• Spatial Relationships.
• Try, try again.

Communicating Your Findings

• Fine-tuning for more effective visualization
• Storytelling and guided analytics
• Dashboards