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BIGDATA AND HADOOP By Ram and Raghavendra

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Page 1: Big data&hadoop

BIGDATA AND HADOOP

By Ram and Raghavendra

Page 2: Big data&hadoop
Page 3: Big data&hadoop

BIGDATAWhat is bigdata…..?

Bigdata is the type of data which contains large volume of files in the form of vedios, audios,Pictures, documents etc……….

Page 4: Big data&hadoop

SOURCES OF BIGDATA

Page 5: Big data&hadoop

BIG DATA

Face book TWITTER

Google

ONEDRIVEYahoo

Media ,Government,Flipkart etc……………

Page 6: Big data&hadoop

Types of bigdata

1.Structured data

2.Un structured data

Page 7: Big data&hadoop

Structured data:

It is the similar type of data which contains same category of files. ex: 1.text files

Text file1 Text file2 ………..

picture1 picture22.pictures ……..

Page 8: Big data&hadoop

Unstructured data:

It is the combination of different types of data.

vedios audios pictures documents

Page 9: Big data&hadoop

Three Characteristics of Big Data V3s

Volume• Data

quantity

Velocity• Data Speed

Variety• Data Types

Page 10: Big data&hadoop

ABOUT BIGDATA• Everyday we are creating 2.5 quintillion bytes of data

• 90% of data in the world has been created in the last two years

• Facebook generates 500+ terabytes of data per a day

Page 11: Big data&hadoop

Difficults with bigdataIt is too difficult to manage this bigdata for 1. analysis 2. capture 3.curation 4.search5.sharing 6.storage7.transfer 8.visualization and information privacy , with standard database management systems like DBMS and RDBMS.

Page 12: Big data&hadoop
Page 13: Big data&hadoop

WHAT IS HADOOP....?

Hadoop Framework Of ToolsIs

Open source(APACHE)

Page 14: Big data&hadoop

Objective :

Hadoop Running applications on Bigdata

SUPPORTS

Page 15: Big data&hadoop

Challenging points to Hadoop

velocity varietyvolume

Page 16: Big data&hadoop

Traditional Approach• Enterprise Approach:

Big Data Processed By Powerful computer

Page 17: Big data&hadoop

Traditional Approach:• Enterprise Approach:

Big Data Processing limit Powerful computer

Only so much data could be

processed

Page 18: Big data&hadoop

Breaking the Data

Big Data Is broken into pieces

Page 19: Big data&hadoop

move computation to the data

Big DataCombined result

COM

PUTA

TIO

N

Page 20: Big data&hadoop

ARCHITECTURE

MAP REDUCE

FILE SYSTEM(HDFS)

PROJECTS

Page 21: Big data&hadoop

DISTRIBUTED MODEL

• 1.THESE ARE LOW COST COMPURTERS• 2. WORKS ON LINUX BASED MACHINES

LINUX LINUX LINUX LINUX

Page 22: Big data&hadoop

TASK TRACKER AND DATA NODES

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

Page 23: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

MASTER JOB TRACKER

Page 24: Big data&hadoop

COMPONENTS

MAP REDUCE

FILE SYSTEM(HDFS)

Page 25: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

Map Reduce

JOB TRACKER

MASTER M

ap

Redu

ce

Page 26: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

HDFS

JOB TRACKER

MASTER HD

FS

Page 27: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

Batch processing

JOB TRACKER

MASTER

Application Queue

Batch

processi

ng

Page 28: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

Job Tracker

JOB TRACKER

MASTER

Page 29: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

FAULT TOLERANCE FOR DATA NODE

JOB TRACKER

MASTER HD

FS

Page 30: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

FAULT TOLERANCE FOR PROCESSING

JOB TRACKER

MASTER M

AP

REDU

CE

Page 31: Big data&hadoop

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

TASK TRACKER

DATANODE

TASK TRACKER

DATA NODE

SLAVES

TASK TRACKER

NAME DATA

NODE NODE

M

Master Backup

JOB TRACKER

MASTER

Tables a

re

backe

d up

Page 32: Big data&hadoop

Easy programming

Do not worryabout

1.Where the file is located

2.How to manage failures

3.How to break competitions into pieces

programmers

4.Scalability

Page 33: Big data&hadoop

Name•Name was given by Doug cutting•Created by Doug cutting Mike cafarella(yahoo) in 2005•Yahoo donated HADOOP to Apache in 2006

Page 34: Big data&hadoop

Usage Areas •Social media •Retail•Financial services•Searching tools•Government • Intelligence

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Companies• Yahoo• Facebook• Amazon• eBay• American airlines• The NEW YORK Times• Chevron• IBM• Federal Reserve Board

Page 36: Big data&hadoop

Future outlook

yahoo

By 2015 50% of enterprise data will be processed by Hadoop

Page 37: Big data&hadoop

Thank you