This document provides an overview of big data analysis for page ranking using MapReduce. It discusses key concepts like what big data is, the four V's of big data, Hadoop and MapReduce frameworks, and applications of big data analysis including homeland security, finance, healthcare, manufacturing, and more. The document concludes that real-time big data analysis enables better decision making and timely actions based on large datasets.

1. BBigig DData Analysis for Pageata Analysis for Page
Ranking using Map/ReduceRanking using Map/Reduce
R.Renuka,
R.Vidhya
Priya,
IIIB.Sc., IT,
S.F.R.College for

2. Overview
Introduction
What isBig Data!
Why Big Data?
4 V’sOf Big Data
Big DataAnalyticsTechnologies
Map/Reduce
Applications
CaseStudy
Conclusion

3. Introduction
Datahaveoutgrown thestorageand processing capabilitiesof
asinglehost.
Two fundamental challenges:
– how to storeand
– how to work with voluminousdatasizes, and,
– how to understand dataand turn it into acompetitive
advantage.

4. What isBig Data!
‘Big-data’ issimilar to ‘Small-data’, but bigger
But having databigger requiresdifferent approaches:
techniques, tools& architectures
To solve:
New problemsand old problemsin abetter way.

5. TheBlind men and theElephant

6. Why Big Data?
Key enablersfor thegrowth of “Big Data” are:
Increaseof Processing Power
Increaseof StorageCapacities
Availability of Data

7. 4 V’sof Big Data

8. Big DataAnalyticsTechnologies
Hadoop
PLATFORA
WibiData
PIG
Hive
MapReduce
NoSQL databases
Column-oriented databases

9. Hadoop
Hadoop isadistributed filesystem and data
processing engine
Hadoop hastwo components:
– TheHadoop distributed filesystem (HDFS)
– TheMapReduceprograming.

10. Map / Reduce
A High level abstracted framework for distributed processing of large
datasets
Fault Tolerant , Parallelization
Computation consistsof two phases
Map
Reduce
A Master-Slavearchitecture
Computationsoccursin multipleslavenodes
And it triesto providedatalocality asmuch aspossible.

11. MR model
Map
– Processakey/valuepair to generateintermediatekey/value
pairs
Reduce
– Mergeall intermediatevaluesassociated with thesamekey
Usersimplement interfaceof two primary methods:
1. Map: (key1, val1) → (key2, val2)
2. Reduce: (key2, [val2]) → [val3]

12. Applications

13. Homeland Security
FinanceSmarter Healthcare
Multi-channel
sales
Telecom
Manufacturing
Traffic Control
Trading Analytics Fraud and Risk
Log Analysis
Search Quality
Retails

14. CaseStudy

16. Conclusion
Real-time big data isn’t just a process for storing
petabytesor exabytesof datain adatawarehouse, It’s
about the ability to make better decisions and take
meaningful actionsat theright time.

17. Queries ??