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Big Data Insights using MapReduce
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Session Objectives
ᗍ Introduction to Big Data and Hadoop
ᗍ Understanding HDFS
ᗍ Introduction to MapReduce – MapReduce Fundamentals
ᗍ MapReduce Programming Tutorial
ᗍ BIG Data Analytics via MapReduce
ᗍ BIG Data & Hadoop Course Details
ᗍ Webinar by Skillspeed
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Big Data and its Challenges
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Big Data and its Challenges
Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications
Systems / Enterprises generate huge amount of data from Terabytes to and even Petabytes of information
It’s very difficult to manage such huge data……
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Who Generates Big Data?
Have you ever wondered how Google, Facebook or LinkedIn manages to store and utilize the huge data?
Today, it is becoming a problem for all of us to manage such BIG DATA…. Get Started with BIG Data & Hadoop
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Hadoop can be used for easy processing of such huge Data…..
We will answer how?
Before that let’s understand what is Hadoop?Get Started with BIG Data & Hadoop
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Hadoop and its Characteristics
Apache Hadoop is a framework that allows the distributed processing of large data sets across clusters of commodity computers using a simple programming model
It is an Open-source Data Management technology with scale-out storage and distributed processing
Hadoop Characteristics
Flexible
Reliable
Economical
Scalable Get Started with BIG Data & Hadoop
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Why Hadoop?
How does Hadoop solve the Big Data challenges?
Hadoop Platform is designed to address the big data problems
Size of Data
Variety of Data
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Hadoop Ecosystem
Flume Sqoop
Import Or Export
Unstructured or Semi-Structured data Structured Data
Apache Oozie (Workflow)
HDFS(Hadoop Distributed File System)
Pig LatinData Analysis
HiveDW System
MapReduce Framework HBase
OtherYARN
Frameworks (MPI,GIRAPH)
YARNCluster Resource Management
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Map Reduce
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Map Reduce – Scenario
Let us consider a real life scenario to understand the importance of “Map Reduce” in Hadoop
Suppose, you are the handling a project which has x tasks and takes 100 hours
for one resource to complete
1 x 100 = 100 hours
100/10(resources) = 10 hours
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Similarly,
= 100 hours 100/10 = 10 hours
Map Reduce – Scenario
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More Scenarios on Map-Reduce
Problem Statement:
Find maximum stock market levels recorded in a span of 5 years
Problem Statement:
De-identify personal identifier information
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Traditional Solution
matchesSplit Data
VeryBig
Data
Allmatches
grep
grep
grep
cat
grep
:
matches
matches
matches
Split Data
Split Data
Split Data
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MapReduce Solution
VeryBig
Input
Split Data
Allmatches
:
Split Data
Split Data
Split Data
MAP
REDUCE
MapReduce Framework
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MapReduce Advantages
Two biggest advantages:
ᗍ Takes processing to the dataᗍ Allows processing data in parallel
a b
c
Map Task
HDFS BlockData Center
Rack
Node
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MapReduce Flow
1. Input data is present in data nodes
2. Map tasks = Input Splits
3. Mappers produce intermediate data
4. Data exchanged among nodes in “shuffling”
5. All data of same key goes to same reducer
6. Reducer output stored at output location
Node 1
INPUT DATA
Map
Node 2
Map
Node 1
Reduce
Node 1
Reduce
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What is Expected?
In this section, we will discuss the questions on HDFS and MapReduce that is asked during the interview
This will help you analyze the importance of the topics under study!
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Job Trends – Hadoop
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Why SkillSpeed?
Course Curriculum
from Industry Experts
Instructor Led Live Virtual
Sessions
Lifetime access to Course
Content via LMS
100% Placement Assistance
24x7 Support
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Course Topics
Module 1
Introduction to Big Data and Hadoop
Module 2
HDFS Internals, Hadoop Configurations and
Data Loading
Module 3
Introduction to Map Reduce
Module 4
Advanced Map Reduce Concepts
Module 5
Introduction to Pig
Module 6
Advanced Pig and Introduction to Hive
Module 7
Advanced Hive Concepts
Module 8
Extending Hive and HBase Introduction
Module 9
Advanced HBase and Oozie Introduction
Module 10
Project Set-up Discussion
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Corporate Partners
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Lines open 24/7
To know more about the course, Please contact:
IND +91-90660-20904 USA 1866-607-6547 (Toll Free)
Or reach us at
Contact Us
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Image References
Google images – credit for google, Facebook and LinkedIn LOGO and Snapshots
http://findicons.com/icon/66444/user_group
http://www.virtualizor.com/tour
https://accounts.it.et.byu.edu/
http://www.clipartsfree.net/tag/server.html
http://www.gopixpic.com/16/time-clock-icon-png-download
http://blog.smartbear.com/requirements/how-to-interview-users-to-find-out-what-they-really-want/
http://www.lincs.fr/research/areas/big-data/
http://www.counsellingpages.co.uk/
http://langfordsconsultancy.com/langfords-training-support-package/
http://cbsepathshala.blogspot.in/2012/05/physics-class-x-chapter-electricity.html
http://mmatycoon.com/tycoontimes/tycoontimesstory.php?SID=1010
http://imgarcade.com/1/big-data-cartoon/