2. Introduction
Literature Survey
Working of Hadoop in Big Data Analytics
Advantages and Disadvantages of Hadoop
Application of Big Data Analytics Using Hadoop
Conclusion
References
Outlines
5. What is Big Data?
“A massive volume of both structured and
unstructured data that is so large that it's difficult to
process with traditional database and software
techniques”.
7. Big data analytics is the process of collecting,
organizing and analyzing large sets of data (called big
data) to discover patterns and other useful information.
Big Data Analytics
8.
9. In this illustrated that in olden days through RDBMS tools
,the data was less and easily handled by RDBMS but
recently it is difficult to handle huge data, which is
preferred as “big data”.
Relational database management system
Relational Databases Are Not Designed To Handle Change
Cost
No support for complex object such as documents,video,images etc.
Relational databases have limits on field lengths.
No support for unstructured data.
10. 2006 - Yahoo! created Hadoop based on GFS and MapReduce (with Doug Cutting
and team)
2007 - Yahoo started using Hadoop on a 1000 node cluster
Jan 2008 - Apache took over Hadoop
Jul 2008 - Tested a 4000 node cluster with Hadoop successfully
2009 - Hadoop successfully sorted a petabyte of data in less than 17 hours to
handle billions of searches and indexing millions of web pages.
Dec 2011 - Hadoop releases version 1.0
Aug 2013 - Version 2.0.6 is available
Nov 2014: Release 2.6.0 available
Dec, 2015: Release 2.6.3 available
Oct, 2016: Release 2.6.5 available
Old Version Of Hadoop
11. It limits scalability
Availability Issue
Problem with Resource Utilization
Limitation in running non-MapReduce Application
Disadvantages of old versions of hadoop
12. 25 January, 2017: Release 3.0.0-alpha2
available
This is the second alpha in a series of planned
alphas and betas leading up to a 3.0.0 GA
release. The intention is to "release early,
release often" to quickly iterate on feedback
collected from downstream users.
Latest Version Of Hadoop
13. To overcome the disadvantages of RDBMS, Hadoop is
introduced in market.
Hadoop is an open source, Java-based programming
framework that supports the processing and storage of
extremely large data sets in a distributed computing
environment.
HADOOP
14. There are many old technologies already present used for big
data handling but each one of them has some advantages and
disadvantages. There are number of technologies are there few of
them are mentioned below:
Column-oriented databases
NoSQL databases
MapReduce
Hive
Pig
WibiData
PLATFORA
Apache Zeppelin
Hadoop
Working Of Hadoop In Big Data Analytics
18. NoSQL (originally referring to SQL. or relational.)
database provides a mechanism for storage and
retrieval of data that is modeled in means other than the
tabular relations used in relation databases (RDBMS).
This is backend database of hadoop.
NoSQL
23. Hadoop which is an open source software is a popular
framework tool to handle the big data and used for big
data analytics.
Conclusion
24. [1] Sethy, Rotsnarani, and Mrutyunjaya Panda "Big Data Analysis using Hadoop:
A Survey." International Journal 5.7 (2015).
[2] Bhosale, Harshawardhan S., and Devendra P. Gadekar. "A Review Paper on
BigData and Hadoop." International Journal of Scientic and Research Publications
4.10 (2014): 1.
[3] ]http://research.ijcaonline.org/volume108/number12/pxc3900288.pdf
[4] https://en.wikipedia.org/wiki/Big data
[5] Tom White,.Hadoop, The denitive guide.,OfReilly,3rd Edition
[6] https://www.google.co.in/?gfe rd=cr&ei=ayKnWJWmDe x8AfDyLnQDg&gws
rd=ssl#q= hadoop + tutoria+ppt
[7] https://www.google.co.in/?gfe rd=cr&ei=ayKnWJWmDe x8AfDyLnQDg&gws
rd=ssl#q= hadoop
References
25. [8] Bernice Purcell “The emergence of gbig datah technology and analytics “Journal of Technology
Research 2013.
[9] https://www.google.co.in/search?q=Hadoop%2 C + a + distributed + framework +for + Big + Data
&ie=utf-8&oeutf-8 &client = firefox ab&gfe rd = cr&ei =glXJWJyDMIKM4gL89IPACg
[10] Gupta, Bhawna, and Kiran Jyoti. "Big data analytics with hadoop to analyze targeted attacks
on enterprise data." (IJCSIT) International Journal of Computer Science and Information
Technologies 5.3 (2014): 3867-3870.
[11] Russom, Philip. "Big data analytics." TDWI best practices report, fourth quarter (2011): 1-35.
[12] http://blogs.mindsmapped.com/bigdatahadoop/hadoop-advantages-and-disadvantages/
[13]http://www.tutorialspoint.com/articles/what-is-nosql-and-is-it-the-next-big-trend-in-databases
[14] http://www.tutorialspoint.com/MongoDB/MongoDB-Application.htm
[15]http://www.w3resource.com/mongodb/nosql.php
[16] https://www.dezyre.com/article/5-healthcare-applications-of-hadoop-and-big-data/85
[17] https://www.tutorialspoint.com/hadoop/hadoop_enviornment_setup.htm