Monday 9 November 2015

Bigdata Hadoop Training in UK,Canada, Singapore

Hadoop Content:
 Hadoop is an open source framework for distributed storage and processing of large sets of data on commodity hardware .Open-source software is created and maintained by a network of developers from around the globe It's free to download, use and contribute to, though more and more commercial versions of Hadoop are becoming available.   
 Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. 
Hadoop often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set .
Commercial function of Hadoop training in Hyderabad contains image processing, Web Crawling, Text processing and Information Analytics.
Data sets grow in size in part because they are increasingly being gathered by cheap and numerous information-sensing mobile devices,aerial , software logs, cameras, microphones, Radio Frequency identification Network and Delivering big data
Now a day’s Hadoop is the Biggest Hot cake for freshers as well as expierenced .Everyone have to    grasp the oppurtunity .
Hyderabad  is   becoming  the  best  place for learning Hadoop .Hadoop training in Hyderabad provides all the Data  with Real time expierenced faculty. Online   courses, Class room courses  are  also providing by R S Trainings through out the week at USA,UK.

RStrainings institute in Hyderabad focus on the needs of the Hadoop community. RStrainings listed one of the top Big Data training institutes in Hyderabad. We offer Hadoop education for working proffessionals. We offer all Big Data training courses as students option. RStrainings Provides free demo Classes.
If you have any reference for the above furnished courses, just intimate them.

Thanks!
Reach us on:
contact@rstrainings.com
Phone: 9052699906

Friday 22 August 2014

Hadoop Online & ClassRoom Training in Hyderabad


RS TRAININGS 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 Hadoop Online training to the learners in all parts of the world with the implementation of modern technologies like Gotomeeting and WebEx.

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 TRAININGS 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 TRAININGS is elite and provides accomplished training services to cater the client needs.



Course Name: Hadoop Administation and Development            24*7 technical support

Faculty : Realtime Experience 

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

Highlights in our training service:

Every faculty has Real Time experience .Trained Resources placed in countries like India,Australia, USA, UK, JAPAN, SWEDEN Itely,Newzeland,singapor etc.Any critical issues faced by resource resolved using Teamviewer, webex.Supporting the resource with Top 100 Interview questions.Resume built in best corporate standards according to the job description.We will market the resume for top technolgy countries.After each week a status exam is conducted.offline online trainings are conducted everyday.Weekend trainings for job goers.flexible timings in accordance with the resource comfortability.If version related to any Tool is upgraded. We will send the upgraded information via email.we will develop the Aquintance with Production,development and testing environments.Real time scenarios covered accross Software Development Life Cycle.for every 10 hours One hour catered to resolve the doubts.Explaining bugs and critical issues and development activities 24*7 technical supports sevices.

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