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Hadoop Online Training

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hadoop online training

The Demand for Hadoop skill-sets has been increasing along with the rise in usage of Big Data.

Hadoop skillsets can brings a range of chances to strengthen your career to a remarkable level.

Learn from the Hadoop industry experts with more than 8 yrs of practical contact with facts.

Hadoop Training - Online / Offline 

Our Hadoop online training and offline classes will make you an expert in Hadoop components.  Our Hadoop students work on real time assignments and project with industry standards . Get an full exposure to Big Data industry based real-time projects in various verticals. Online Training's Guru is the best institute to learn Hadoop on both online and offline modes.

Hadoop Online / Offline Learning Is Made Easy

Offline Classroom Training

  • Classroom training by certified industry experts
  • Hadoop Training material designed by Experts
  • Fast-track / Regular / Weekend Batches
  • Hadoop Training  in Hyderabad, India
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Hadoop LED Live Online Training

  • LED  Hadoop online training by the experts in Industry
  • Hadoop Training material designed specially for you.
  • Hadoop Experts One to One sessions.
  • Fast-track / Regular / Weekend Batches
  • 24 x 7 Support 
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Hadoop Corporate Training

  • Offline / Online Hadoop training by certified experts options.
  • Hadoop Training material designed by Experts
  • 24x 7 Teaching assistance and support.
  • Advanced reporting for individuals and teams.
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Hadoop training course content and Syllabus - Online / Offline

Hadoop Course Content

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    Hadoop Overview, Architecture Considerations, Infrastructure, Platforms and Automation

Use case walkthrough

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    ETL
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    Log Analytics
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    Real Time Analytics

Hbase for Developers :

NoSQL Introduction

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    Traditional RDBMS approach
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    NoSQL introduction
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    Hadoop & Hbase positioning

Hbase Introduction

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    What it is, what it is not, its history and common use-cases
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    Hbase Client – Shell, exercise

Hbase Architecture

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    Building Components
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    Storage, B+ tree, Log Structured Merge Trees
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    Region Lifecycle
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    Read/Write Path

Hbase Schema Design

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    Introduction to hbase schema
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    Column Family, Rows, Cells, Cell timestamp
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    Deletes
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    Exercise - build a schema, load data, query data

Hbase Java API – Exercises

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    Connection
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    CRUD API
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    Scan API
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    Filters
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    Counters
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    Hbase MapReduce
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    Hbase Bulk load

Hbase Operations, cluster management

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    Performance Tuning
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    Advanced Features
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    Exercise
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    Recap and Q&A

MapReduce for Developers

Introduction

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    Traditional Systems / Why Big Data / Why Hadoop
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    Hadoop Basic Concepts/Fundamentals

Hadoop in the Enterprise

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    Where Hadoop Fits in the Enterprise
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    Review Use Cases

Architecture

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    Hadoop Architecture & Building Blocks
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    HDFS and MapReduce

Hadoop CLI

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    Walkthrough
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    Exercise

MapReduce Programming

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    Fundamentals
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    Anatomy of MapReduce Job Run
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    Job Monitoring, Scheduling
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    Sample Code Walk Through
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    Hadoop API Walk Through
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    Exercise

MapReduce Formats

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    Input Formats, Exercise
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    Output Formats, Exercise

Hadoop File Formats

MapReduce Design Considerations

Hadoop File Formats

MapReduce Algorithms

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    Walkthrough of 2-3 Algorithms

MapReduce Features

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    Counters, Exercise
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    Map Side Join, Exercise
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    Reduce Side Join, Exercise
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    Sorting, Exercise

Use Case A (Long Exercise)

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    Input Formats, Exercise
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    Output Formats, Exercise

MapReduce Testing

Hadoop Ecosystem

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    Oozie
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    Flume
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    Sqoop
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    Exercise 1 (Sqoop)
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    Streaming API
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    Exercise 2 (Streaming API)
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    Hcatalog
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    Zookeeper

HBase Introduction

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    Introduction
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    HBase Architecture

VIEW Types

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    Default Views
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    Overriden Views
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    Normal Views

MapReduce Performance Tuning

Development Best Practice and Debugging

Apache Hadoop for Administrators

Hadoop Fundamentals and Architecture

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    Why Hadoop, Hadoop Basics and Hadoop Architecture
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    HDFS and Map Reduce

Hadoop Ecosystems Overview

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    Hive
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    Hbase
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    ZooKeeper
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    Pig
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    Mahout
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    Flume
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    Sqoop
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    Oozie

Hardware and Software requirements

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    Hardware, Operating System and Other Software
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    Management Console

Deploy Hadoop ecosystem services

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    Hive
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    ZooKeeper
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    HBase
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    Administration
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    Pig
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    Mahout
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    Mysql
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    Setup Security

Enable Security – Configure Users, Groups, Secure HDFS, MapReduce, HBase and Hive

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    Configuring User and Groups
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    Configuring Secure HDFS
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    Configuring Secure MapReduce
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    Configuring Secure HBase and Hive

Manage and Monitor your cluster

Command Line Interface

Troubleshooting your cluster

Introduction to Big Data and Hadoop

Hadoop Overview

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    Why Hadoop
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    Hadoop Basic Concepts
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    Hadoop Ecosystem – MapReduce, Hadoop Streaming, Hive, Pig, Flume, Sqoop, Hbase, Oozie, Mahout
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    Where Hadoop fits in the Enterprise
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    Review use cases

Apache Hive & Pig for Developers

Overview of Hadoop

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    Big Data and the Distributed File System
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    MapReduce

Hive Introduction

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    Why Hive?
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    Compare vs SQL
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    Use Cases

Hive Architecture – Building Blocks

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    Hive CLI and Language (Exercise)
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    HDFS Shell
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    Hive CLI
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    Data Types
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    Hive Cheat-Sheet
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    Data Definition Statements
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    Data Manipulation Statements
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    Select, Views, GroupBy, SortBy/DistributeBy/ClusterBy/OrderBy, Joins
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    Built-in Functions
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    Union, Sub Queries, Sampling, Explain

Hive Use case implementation -(Exercise)

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    Use Case 1
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    Use Case 2
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    Best Practices

Advance Features

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    Transform and Map-Reduce Scripts
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    Custom UDF
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    UDTF
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    SerDe
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    Recap and Q&A

Pig Introduction

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    Position Pig in Hadoop ecosystem
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    Why Pig and not MapReduce
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    Simple example (slides) comparing Pig and MapReduce
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    Who is using Pig now and what are the main use caseserDe
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    Pig Architecture
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    Discuss high level components of Pig
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    Pig Grunt - How to Start and Use

Pig Latin Programming

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    Data Types
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    Cheat sheet
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    Schema
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    Expressions
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    Commands and Exercise
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    Load, Store, Dump, Relational Operations,Foreach, Filter, Group, Order By, Distinct, Join, Cogroup,Union, Cross, Limit, Sample, Parallel

Use Cases (working exercise)

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    Use Case 1
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    Use Case 2
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    Use Case 3 (compare pig and hive)

Advanced Features, UDFs

Best Practices and common pitfalls

Mahout & Machine Learning

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    Mahout Overview
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    Mahout Installation
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    Introduction to the Math Library
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    Vector implementation and Operations (Hands-on exercise)
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    Matrix Implementation and Operations (Hands-on exercise)
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    Anatomy of a Machine Learning Application

Classification

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    Introduction to Classification
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    Classification Workflow
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    Feature Extraction
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    Classification Techniques (Hands-on exercise)

Evaluation (Hands-on exercise)

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    Clustering
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    Use Cases
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    Clustering algorithms in Mahout
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    K-means clustering (Hands-on exercise)
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    Canopy clustering (Hands-on exercise)

Clustering

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    Mixture Models
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    Probabilistic Clustering – Dirichlet (Hands-on exercise)
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    Latent Dirichlet Model (Hands-on exercise)
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    Evaluating and Improving Clustering quality (Hands-on exercise)
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    Distance Measures (Hands-on exercise)

Recommendation Systems

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    Overview of Recommendation Systems
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    Use cases
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    Types of Recommendation Systems
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    Collaborative Filtering (Hands-on exercise)
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    Recommendation System Evaluation (Hands-on exercise)
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    Similarity Measures
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    Architecture of Recommendation Systems
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    Wrap Up

Why to choose "Online Training Guru" Hadoop Training in Hyderabad?

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    Our Experts in Hadoop training in Hyderabad designed the course according to the existing IT industry.
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    You can expect the best Hadoop training in Hyderabad guaranteeing the entire course modules in the Hadoop classes.
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    Hadoop training in Hyderabad are scheduled on all the weekdays. Also students can opt for customized online training schedule in accordance with the needs.
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    Our Hadoop trainers team are current industry experts proudly owning greater than ten years experience in Hadoop training.
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    Our Hadoop training in Hyderabad not only helps the students in engaging in live projects, but also we offer session on interview presentation skills together with Hadoop placement assistance.
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    Our lab doors are open 365 days a year. Individuals, in accordance with their comfort can make use of the lab for accomplishing projects and exercise the Hadoop technical assignments.
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    Our Hadoop trainers spend one-to-one attention.
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    We accept payments via Paytm, Net Banking and PayPal 
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