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BIG DATA MAPREDUCE TRAINING

Learners: 89   |   Duration: 30 Hrs   |   Reviews 21 ( 4.0 )

MapReduce produces huge information on a group of PCs utilizing a parallel, appropriated calculation and accommodating adaptation to non-critical failure. In the event that Hadoop is the sensory system associating a wide range of servers together, then MapReduce is the mind creating and handling data into significant information


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MapReduce produces and procedures huge information on a group of PCs utilizing a parallel, appropriated calculation and accommodating adaptation to non-critical failure. In the event that Hadoop is the sensory system associating a wide range of servers together, then MapReduce is the mind creating and handling data into significant information

What you will learn in BIG DATA MapReduce Training?

The primary target of MapReduce internet preparing system is to show members how to compose MapReduce programs, moving from easy to complex projects by degrees and with a lot of illustrations. It starts with the MapReduce establishment and design process and proceeds onward to hypothesis and practice. Portraying the information stream of the Mapper info and Reducer yield preparing, it gives the 10,000-foot view with respect to the ideas required in MapReduce. It discusses how the program oversees servers and how to connect with the MapReduce API. It demonstrates to oversee employment with the Hadoop CLI and screen them with MCS. It talks about how to function with various information sources on MapReduce and the conveyed store. It likewise incorporates the methods required in running numerous employments and tying.

Who should take BIG DATA MapReduce course?

  • Analytics experts
  • Research experts
  • IT engineers and analyzers
  • Project Managers
  • Information Scientists

Why should you go for BIG DATA MapReduce course?

As the number of associations attempting to tackle the energy of huge information preparing duplicates, the IT divisions are discovering that their centralized servers, intended for organized information, are not ready to deal with the surge of unstructured information. This reality is inciting a move to exceptional stages that can deal with big business workloads, which is the place MapReduce and Hadoop come in. MapReduce and Hadoop offer IT offices the capacity to deal with boundless simultaneous errands and gigantic preparing power with effectiveness and dependability. These are the instruments that are vital for crunching high volumes of unstructured information. In this way, engineers, information designers, database managers, and information examiners, specifically have much to pick up by acing MapReduce.

The normal pay of Hadoop designers working in the huge information industry has been accounted as $135,000. Exploit this worldwide move to huge information and enlist in MapReduce web-based preparing program today.


Salary as per Market

A Data analyst earns around $135,000

Big Data Introduction

Hadoop Introduction
What is Hadoop? Why Hadoop?
Hadoop History?
Different types of Components in Hadoop?
HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
What is the scope of Hadoop?

Deep Drive in HDFS

Introduction of HDFS
HDFS Design
HDFS role in Hadoop
Features of HDFS
Daemons of Hadoop and its functionality
Name Node
Secondary Name Node
Job Tracker
Data Node
Task Tracker
Anatomy of File Wright
Anatomy of File Read
Network Topology
Nodes
Racks
Data Center
Parallel Copying using DistCp
Basic Configuration for HDFS
Data Organization
Blocks and
Replication
Rack Awareness
Heartbeat Signal
How to Store the Data into HDFS
How to Read the Data from HDFS
Accessing HDFS (Introduction of Basic UNIX commands)
CLI commands

MapReduce using Java

The introduction of MapReduce.
MapReduce Architecture
Data flow in MapReduce
Splits
Mapper
Portioning
Sort and shuffle
Combiner
Reducer
Understand Difference Between Block and InputSplit
Role of RecordReader
Basic Configuration of MapReduce
MapReduce life cycle
Driver Code
Mapper
and Reducer
How MapReduce Works
Writing and Executing the Basic MapReduce Program using Java
Submission & Initialization of MapReduce Job.
File Input/Output Formats in MapReduce Jobs
Text Input Format
Key Value Input Format
Sequence File Input Format
NLine Input Format
Joins
Map-side Joins
Reducer-side Joins
Word Count Example
Partition MapReduce Program
Side Data Distribution
Distributed Cache (with Program)
Counters (with Program)
Types of Counters
Task Counters
Job Counters
User Defined Counters
Propagation of Counters
Job Scheduling

Introduction to Apache PIG

Introduction to PIG Data Flow Engine
MapReduce vs. PIG in detail
When should PIG use?
Data Types in PIG
Basic PIG programming
Modes of Execution in PIG
Local Mode and
MapReduce Mode
Execution Mechanisms
Grunt Shell
Script
Embedded
Operators/Transformations in PIG
PIG UDF’s with Program
Word Count Example in PIG
The difference between the MapReduce and PIG

Introduction to SQOOP

Use of SQOOP
Connect to mySql database
SQOOP commands
Import
Export
Eval
Codegen etc…
Joins in SQOOP
Export to MySQL
Export to HBase

Introduction to HIVE

HIVE Meta Store
HIVE Architecture
Tables in HIVE
Managed Tables
External Tables
Hive Data Types
Primitive Types
Complex Types
Partition
Joins in HIVE
HIVE UDF’s and UADF’s with Programs
Word Count Example

Introduction to HBASE

Basic Configurations of HBASE
Fundamentals of HBase
What is NoSQL?
HBase Data Model
Table and Row
Column Family and Column Qualifier
Cell and its Versioning
Categories of NoSQL Data Bases
Key-Value Database
Document Database
Column Family Database
HBASE Architecture
HMaster
Region Servers
Regions
MemStore
Store
SQL vs. NOSQL
How HBASE differs from RDBMS
HDFS vs. HBase
Client-side buffering or bulk uploads
HBase Designing Tables
HBase Operations
Get
Scan
Put
Delete

MongoDB</h3

Where to Use?
Configuration On Windows
Inserting the data into MongoDB?
Reading the MongoDB data.

Downloading and installing the Ubuntu12.x
Installing Java
Installing Hadoop
Creating Cluster
Increasing Decreasing the Cluster size
Monitoring the Cluster Health
Starting and Stopping the Nodes
Zookeeper
Introduction Zookeeper
Data Modal
Operations
OZIE
Introduction to OOZIE
Use of OOZIE
Where to use?
Flume
Introduction to Flume
Uses of Flume
Flume Architecture
Flume Master
Flume Collectors
Flume Agents

Our trainers are Highly experienced in implementing real-time solutions on different Scenarios and Expert in their professionals.

We record each LIVE class session you undergo through this training and we will share the recordings of each session/class.

Trainer will Provide Detailed installation of required software through LMS to the students we support by providing Training and practical in real time experience with all utilities required for completely understanding of this Training.

Yes, there are some group discount are available only if group contain more than 2 Or more participates.

Yes. All the training sessions will be a LIVE Online Streaming using either through GoToMeeting or WebEx You will be shared with live meeting access while Session Starts

We provide Training in a Real Time Projects Oriented

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Yes we will Schedule a Demo Session as per the student convenient by sharing LIVE Online Streaming access either through GoToMeeting or WebEx.

If you are enrolled in classes and you have paid fees, but want to cancel the registration for certain reason, it can be done within 48 hours of initial registration. Please make a note that refunds will be processed within 15 days of prior request

As we are one of the Best Online Training Provider we have customer throughout the world wide specially from UK, USA, UAE, Australia, Qatar, Singapore, New Zealand, India, Malaysia, Dubai, Doha, Melbourne, Brisbane, Perth, Wellington, Auckland Middle East Countries and other parts of the world

We are also located in USA Offering Online Training in Cities like New York, New jersey, Dallas, Seattle, Baltimore, Tempe, Chandler, Scottsdale, Peoria, Honolulu, Columbus, Raleigh, Nashville, Plano, Toronto, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Houston, Minneapolis, Los Angeles, San Francisco, San Jose, San Diego, Washington DC, Chicago, Philadelphia, St. Louis, Edison, Jacksonville, Towson, Salt Lake City, Davidson, Murfreesboro, Atlanta, Alexandria, Sunnyvale, Santa Clara, Carlsbad, San Marcos, Franklin, Tacoma, California, Bellevue, Austin, Charlotte, Garland, Raleigh-Cary, Boston, Orlando, Fort Lauderdale, Miami, Gilbert.

In Indian we have customer from Bangalore, Mysore, Hyderabad (Ameerpet), Visage, Chennai, Kolkata, Pune, Mumbai, Delhi, Jaipur, Ahmadabad, Kerala etc…

You can clarify your queries by dialing +91 - 82 9696 0414, +1 (646) 586 - 2969 Or you can send a mail to info@gologica.com. We are ready to clear your enquiries at any time

At the end of this course, you will receive a course completion certificate which certifies that you have successfully completed GoLogica training in MapReduce technology.

You will get certified in MapReduce by clearing the online examination with a minimum score of 70%.

To help you prepare for a certification exam, we shall provide you a simulation exam and a practice exam. 

 

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Reviews


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Upcoming Demo’s

22
Friday
March, 2019
23
Saturday
March, 2019
24
Sunday
March, 2019
25
Monday
March, 2019

Course Duration - 30 hrs

Hours - 1hr/day

Training Mode - Online

Course Duration - 8 Weekends

Hours - 2hr/Day

Training Mode - Online

Course Duration - 15 Days

Hours - 2hr/Day

Training Mode - Online