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Big Data Hadoop Duration: 32 Hours Start Date: Weekend Batch 10.a.m - 6 p.m (Date to be updated s

 

 

Big Data Hadoop

 

The internet users have increased from 2.937 Billion to 3.174 from the last year. Hence managing data has been bottleneck situation to store and manage huge data.

 

To solve the above problem Hadoop an open source framework has evolved to store and process huge amount of data

 

To bridge the gap between the trending market needs and increasing job opportunities for this technology you have reached the right place to get equipped with your skill set with us.

 

Highlights

 

 

* 32 Hours of Intense Training

 

 

* Highly Qualified Trainers

 

 

* Hands on experience

 


Course Details

 

 

Objective – To Master the Big Data Hadoop Technology to promote your career oppportunities.

 

Course Fees – 15000 + Service Tax (14.5%)

Contents/Topics covered during the course:

 

1. Introduction to Big Data and Hadoop

- What is Big Data?

- The Rise of Bytes

- Data Explosion and its Sources

- Types of Data

-  Structured, Semi-structured, Unstructured data

- Characteristics of Big Data

-  Limitations of Traditional Large-Scale Systems

-  Use Cases for BigData

- Challenges of BigData

-  Hadoop Introduction - What is Hadoop? Why Hadoop?

- Supported Operating Systems

- Organizations using Hadoop

- Hadoop Job Trends

- History of Hadoop

- Hadoop Core Components – MapReduce & HDFS

2.Hadoop Setup

- Deployment Modes – Standalone Mode, Pseudo-Distributed Mode, Fully Distributed Mode -

- Pseudo-Distributed Mode Virtual Machine Setup on Windows

- VMWare Player - Introduction

- Install VMWare

-  Create a VM in VMWare

- Download and Install Hadoop Packages

- Configuration parameters and values

-  HDFS parameters

-  MapReduce parameters

- YARN parameters

-  Hadoop environment setup

- Environment variables

-  Hadoop Configuration

- HDFS, MapReduce and YARN parameters

- Hadoop Core Services – Daemon Process Status using JPS

- Hadoop WebUI

-  Eclipse development environment setup

3. HDFS Architecture

- Introduction to Hadoop Distributed File System

- Regular File System v/s HDFS

- HDFS Architecture

- Components of HDFS - NameNode, DataNode, SecondayNameNode

-  HDFS Features - Fault Tolerance, Horizontal Scaling, Data Replication, Rack Awareness

- Anatomy of a file write on HDFS

- Anatomy of a file read on HDFS

-  Hands on with Hadoop HDFS, WebUI and Linux Terminal Commands

- HDFS File System Operations

- Name Node Metadata, File System Namespace, NameNode Operation,

- Data Block Split

- Benefits of Data Block Approach

- HDFS - Block Replication Architecture, Block placement, Replication Method, Data Replication Topology, Network Topology, Data Replication Representation

- HDFS Programming Basics – Java API

- Java API Introduction

-  Hadoop Configuration API

-  HDFS API Overview

- When Hadoop is not suitable

4. MapReduce

-  What is MapReduce and Why it is popular

-  MapReduce Framework– Introduction, Driver, Mapper, Reducer, Combiner, Split, Shuffle & Sort 

-  Use cases of MapReduce

- Real-time uses of MapReduce

- Input Splits in MapReduce

- Hands on with MapReduce Programming

-  Map Reduce Architecture

- Responsibility of JobTracker, TaskTracker in classic MapReduce v1

- Running on LocalJobRunner v/s Cluster

Packaging MapReduce Jobs in a JAR

-  Responsibility of JobTracker, TaskTracker in classic MapReduce v1 

- Anatomy of MapReduce Jobs Execution in classic MRv1(JT, TT)

- Understanding Input/Output Format, Sequence Input/Output format

- Joins in MapReduce

5. YARN Architecture

- Hadoop 1.0 Limitations

- MapReduce Limitations

- YARN Architecture

- Classic vs. YARN

- Speculative Execution

- Understanding Data Types of Keys and Values

-  MapReduce and YARN command line tools

-  Anatomy of MapReduce Jobs Execution MRv2 - YARN(RM, AM, NM)

- Distributed Cache

6. Hive

- Limitations of MapReduce

- Need for High Level Languages

-  Analytical OLAP - Data warehousing with Apache Hive

- What is Hive?

- Hive Query Language

- Background of Hive.

- Hive Installation and Configuration

-  Hive Architecture

-  Hive Data Types

-  Hive Data Model

- Hive Examples

- Create/Show Database

- Create/Show/Drop Tables

- SELECT, INSERT, OVERWRITE, EXPLAIN

- CREATE, ALTER, DROP, TRUNCATE

- Create / Show Database.

- Create / Show / Drop Tables

- Hive UDF

- SerDe (Serialization / Deserialization)

- Partitions and Buckets

-  Joins

- Limitations of Hive

- SQL vs. Hive

7. Sqoop and Flume – Data Ingestion

- Setup MySQL RDBMS

- Sqoop - Import/Export Structured Data to/from HDFS from/to RDBMS

-  Introduction to Sqoop

- Sqoop Installation

- Importing Data – to HDFS, Hive, HBase

- Sqoop Connectors

- Sqoop Commands

- Flume – Import Semi-Structured Data to HDFS

- Why Flume

-  Flume - Introduction 

- Flume Model

8. NoSQL and HBase

- Introduction to NoSQL

- CAP Theorem and Eventual consistency

- Row Oriented v/s Column Oriented Storage

-  Landscape of NoSQL

-  HBase Architecture Overview

-  HBase v/s HDFS

-  Batch vs. Real Time Data Processing

- Use-cases for Real Time Data Read/Write

- HBase components - HMaster, HRegionServer

- ZooKeeper

-  Replication

- Apache Phoenix

-  Bulk Loading HBase

9. Other components on Hadoop Ecosystem

- Introduction to Oozie

-Oozie Installation

- Creating Oozie Workflows

10. Commercial Distributions of Hadoop

- Introduction to Cloudera, Hortonworks, MapR


 FAQ

 

1. How do I Enroll for this class?

 

There is a Register Link below, please click on it enter details and submit the form.

Once we get your details we will send an email with the Bank details to which 50% of the payment should be made.


 

2. What is mode of Payment?

 

Online Transfer and Cash.

50 % of the Total fees amount to be paid for confirmation and remaining 50 % on or by  the first day of the class.

Note - Details of Bank account for Online Transfer will be sent to your email address on Registration.


 

3. When will I get a confirmation of admission?

 

On receipt of your payment we will send out the confirmation email with Course details.


 

4. What if i make a payment and dont attend the class?

 

No Refund will be provided, You can refer any substitue or we can try to fit in to another batch based on availability (but no gurantee on this).


 

5. What if i attend one class and unable to continue?

 

 

No Refund will be provided.  A seat for missed sessions in a future course would be at the discretion of TestBuds, on an availability basis.          

 


 

6. Can I Cancel the admission after payment?

 

 

If Cancellation is done by atleast 10 working days (mon-fri) before the date of training start date a full refund is provided, post which no refund is provided.

 


 

7. What if the training gets cancelled by TestBuds?

 

 

In case of insufficient batch enrolments, or Trainer non-availability (or any other instances) TestBuds reserves the right to cancel the training, with a full refund of advance received towards enrolment.

 


 

8. What are the batch timings?

 

Weekend batch - 10.a.m - 6.p.m 

However Timings would be sent in the confirmation email.


Venue : TestBuds (Registered office):
1/A, 3rd Floor, 24th A Main, 5th A Cross,
Manjunath Colony, Marenahalli, JP Nagar 2nd Phase,
Bangalore – 560078
(opp R.V. Dental college)


 

Business Lines : Phone : +91 – 080 – 4217 4500 
                              Contact person : Sindhu
                              
training@testbuds.in


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Small overview
Whether cloud, mobile, social, or analytics, businesses today are struggling to deal the massive amounts of data created by both traditional and the new era workloads. Businesses that have the storage infrastructure to better gain insights from this data will have competitive advantage.Virtualization, in computing, refers to the act of creating a virtual (rather than actual) version of something, including but not limited to a virtual computer hardware platform, operating system (OS), storage device, or computer network resources. Training on these areas can fetch jobs in product based companies.

Curriculum Overview
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Detail about Trainer
Trainer has 10 years of experience in the companies like NetApp, VMware and HP

Duration
30 hours including lab sessions

Certification Course 
No


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