Friday 18 October 2013

Hadoop training&Big data training with placement assistance

Hadoop Introduction : Magnific training
Hadoop is an open source software.  Hadoop  allows distributed processing of the scattered large sets of data  across batch of computer  servers using simple programming methods. It is outlined to scale up from a single server to thousands of machines, with a very high availability. offers local computation and storage. Rather than depending on hardware, the flexibility of these batches comes from the software’s capability to detect and handle failures at the application layer. This course helps you through address the challenges and take advantage of the core values provided by Hadoop in a vendor neutral way.  
Magnific training Training offers the Hadoop Online Course in a true global setting. 

Hadoop Online Training Concepts :
HADOOP BASICS
1.The Motivation for Hadoop
1.Problems with traditional large-scale systems
1.Data Storage literature survey
2.Data Processing literature Survey
3.Network Constraints
2.Requirements for a new approach
3.Hadoop: Basic Concepts
1.What is Hadoop?
2.The Hadoop Distributed File System
3.Hadoop Map Reduce Works
4.Anatomy of a Hadoop Cluster
4.Hadoop demons
1.Master Daemons
1.Name node
2.Job Tracker
3.Secondary name node
2.Slave Daemons
1.Job tracker
2.Task tracker.
or full course details please visit our website http://www.magnifictraining.com/

Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
* Resume preparation and Interview assistance will be provided.For any further details please 
contact India +91-9052666559
         Usa : +1-678-693-3475.
please mail us all queries to info@magnifictraining.com

Tuesday 1 October 2013

Big data training and Certification | Big data school

Big data Training & Certification Program.

(Magnific training)

Course Contents of Hadoop and Big Data
1. Introduction to Hadoop & Big Data
Introduction to Hadoop
Introduction to Big Data
How Hadoop can solve problem associated with traditional large scale system
Other Open Source Software related to Hadoop
IN depth Knowledge on how Big Data Solutions work on Cloud
How to create your own Hadoop Cluster
2. Hadoop Architecture
Understand the main Hadoop Components
Learn How HDFS Works
List Data Access patterns for which HDFS is Designed
Learn how data is stored in HDFC Cluster
Learn HDFC Commands
3. Querying Data
An overview of Pig, Hive and JAQL
Working with Pig
Working with Hive
Working with JAQL
Working with Pig , Hive and JAQL Transcript
Querying Data with Pig , Hive and JAQL
4. Introduction to MapReduce
Understands the concepts of map and reduce operations
Describes how Hadoop execute a MapReduce Job
List MapReduce Fundamental Data Types
Explain a MapReduce Data flow
List MapReduce fault tolerance and scheduling features
5. Shifting Data into Hadoop
Understand how to transfer data into Hadoop using Flume
Introduction to Flume
Introduction to Flume Transcript
Working with Flume
Flume mode of operation and configuration.

contact India +91-9052666559
         Usa : +1-678-693-3475.

visit www.hadooponlinetraining.net


please mail us all queries to info@magnifictraining.com

Thursday 26 September 2013

Big data school ( Hive,Map reduce,Hdfs) | Training

Big data school ( Hive,Map reduce,Hdfs) | Training
Course Contents
The course covers the following topics:
  • The Motivation For Hadoop

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

  • Hadoop: Basic Concepts

    • What is Hadoop?
    • The Hadoop Distributed File System
    • How MapReduce Works
    • Anatomy of a Hadoop Cluster

  • Writing a MapReduce Program

    • Examining a Sample MapReduce Program
    • Basic API Concepts
    • The Driver Code
    • The Mapper
    • The Reducer
    • Hadoop's Streaming API

  • The Hadoop Ecosystem

    • Hive and Pig
    • HBase
    • Flume
    • Other Ecosystem Projects

  • Integrating Hadoop Into The Workflow

    • Relational Database Management Systems
    • Storage Systems
    • Importing Data from RDBMSs With Sqoop
    • Importing Real-Time Data with Flume

  • Delving Deeper Into The Hadoop API

    • Using Combiners
    • The configure and close Methods
    • SequenceFiles
    • Partitioners
    • Counters
    • Directly Accessing HDFS
    • ToolRunner
    • Using The Distributed Cache

  • Common MapReduce Algorithms

    • Sorting and Searching
    • Indexing
    • Classification/Machine Learning
    • Term Frequency - Inverse Document Frequency
    • Word Co-Occurrence

  • Using Hive and Pig

    • Hive Basics
    • Pig Basics

  • Debugging MapReduce Programs

    • Testing with MRUnit
    • Logging
    • Other Debugging Strategies

  • Advanced MapReduce Programming

    • A Recap of the MapReduce Flow
    • Custom Writables and WritableComparables
    • The Secondary Sort
    • Creating InputFormats and OutputFormats
    • Pipelining Jobs With Oozie.

  • Joining Data Sets in MapReduce Jobs

    • Map-Side Joins
    • Reduce-Side Joins

  • Graph Manipulation in Hadoop

    • Introduction to graph techniques
    • Representing Graphs in Hadoop
    • Implementing a sample algorithm: Single Source Shortest Path.

    • or full course details please visit our website www.hadooponlinetraining.net

    • Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.

    • * Resume preparation and Interview assistance will be provided.
    • For any further details please 

    • contact India +91-9052666559
    •          Usa : +1-678-693-3475.

    • visit www.hadooponlinetraining.net

    • please mail us all queries to info@magnifictraining.com

Sunday 22 September 2013

Big data training and placement | Big data School

Training Agenda:

Introduction to Apache Hadoop 
- Why are we here? What’s changed today? 
- What is Hadoop? 
- Hadoop architecture 

Hadoop Distributed File System (HDFS) 
- Storing and retrieving data from HDFS 
- HDFS operations 

Developing with MapReduce 
- How MapReduce works 
- Writing Mappers 
- Writing Reducers 
- Using Combiners for efficiency 

Modern Development Practices 
- Running with LocalJobRunner 
- Running within an IDE 
- Writing Unit Tests for Hadoop code 

Hadoop Projects: Hive 
- Data warehouses: then and now 
- Hive query language 
- Hive in practice 

Hadoop Projects: Pig 
- Pig: a DSL for MapReduce 
- Pig in practice 

Hadoop Projects: HBASE 
- Column-oriented database, real-time read-write access 
- HBASE in practice 

Wrap-up 
- Further resource 
- What’s new and exciting 
- See more at: 

or full course details please visit our website www.hadooponlinetraining.net

Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.

* Resume preparation and Interview assistance will be provided.
For any further details please 

contact India +91-9052666559
         Usa : +1-678-693-3475.

visit www.hadooponlinetraining.net


please mail us all queries to info@magnifictraining.com

Wednesday 21 August 2013

Big data training school

Magnific training : Big data training school

Introduction
The Case for Apache Hadoop
HDFS
Getting Data into HDFS
MapReduce
Planning Your Hadoop Cluster
Hadoop Installation and Initial Configuration
Installing and Configuring Hive, Impala, and Pig
Hadoop Clients
Cloudera Manager
Advanced Cluster Configuration
Hadoop Security
Managing and Scheduling Jobs
Cluster Maintenance
Cluster Monitoring and Troubleshooting
Conclusion.
You can attend 1st 2 classes or 3 hours for free. once you like the classes then you can go for registration.

or full course details please visit our website www.hadooponlinetraining.net


Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.



* Resume preparation and Interview assistance will be provided. 

For any further details please contact +91-9052666559 or
visit

www.hadooponlinetraining.net

please mail us all queries to info@magnifictraining.com