While a number of technologies fall under the Big Data label, Hadoop is the Big Data mascot.

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "While a number of technologies fall under the Big Data label, Hadoop is the Big Data mascot."

Transcription

1 While a number of technologies fall under the Big Data label, Hadoop is the Big Data mascot. Remember it stands front and center in the discussion of how to implement a big data strategy. Early adopters are google, facebook, linkedin and yahoo, but it is now becoming mainstream, so what is it? 1

2 2

3 Firstly some context Who here has big data? So, Big Data, what does it mean? Most often big data refers to the size, if it is data and it is big, it must be BIG DATA. However, there are other elements of big data not necessarily associated with size the best way I like to describe big data is big data is any attribute that challenges the constraints of a system capability, for example 20mb powerpoint you cant send it via , so this could be big data 100gb xray image you cant accurately display it on a remote screen in real time for a consultation, this could be big data 1 tb movie you cant render edits within the time constraints of the business, this could be big data With the explosion of data in our environments, the likelihood of you having big data is higher than you think. So, who here now has big data? As you can see, in 2000, we generated 2 exabytes or 2000 PB of new information in the year. 3

4 Fast forward to 2011, the amount of information we generated is 2 exabytes everyday! That is huge, most of this could be a result of big data. 4

5 This unstructured, file-based data comes from many sources such as , audio, video, images, Word documents, machine-generated logs, etc. This type of file-based data is growing at an especially accelerated rate and is expected to grow 50x in the next 10 years. So we have gone from 2 exabytes in a year in 2000, to 2 exabytes a day in 2011, and then 50x that in the next 10 years. That to me means we need to do things differently otherwise we wont be able to store that data let alone extract any type of business value from it. -Unprompted, an airline or a telephone company offers you a spiff? Perhaps just a few days after you ve had an unpleasant experience on one of their flights. How d they do that? - A retailer seems to offer you products closer and closer to the ones you d actually like to buy. And at prices better than you had seen in the store, or on your favorite web site. -Your Physician is increasingly able to predict how you individually will respond to a particular course of treatment? - You re seeing fewer and fewer dropped calls on your mobile? - Your power company is now delivering exact assessments of how energy-efficient your dwelling is? 5

6 We arrive at what many have called the next great productivity revolution. The age in which research and the scientific process becomes automated in the sense that so much data is available for analysis that we no longer need to speculate about what may be taking place the trends, the hypotheses, are already produced by the amount of data available. (see article here: A story to illustrate: The Australian government recently announced funding for a National Mental Health Council. Their job is to collect annually all the metrics on mental health from around Australia (this is currently done on an ad-hoc basis by researchers, but to systematically). So they will gather data from the states on suicide rates, on hospital admissions, on substance abuse, on medically reported rates of depression, and so on all manually collated by ing and asking for spreadsheets a huge undertaking. The old way. Consider now that you can install an iphone app that will use voice pattern recognition to determine your mood ie your mental health can be roughly determined by your smartphone listening to your intonation. So in the age of big data: all this manual assembly of data becomes redundant the process can be autmoated. And not only do we leave behind the manual assembly of data, we can leave behind the process of speculation, hypothesis, and then testing the hypothesis the mental health of all Australians, if they have a smartphone, could be collected (this would need to be voluntary obviously) and then researchers could dig into patterns of mood on a daily basis across demographics and so on. An outbreak of short-term depression across Queensland the day after the maroons got beaten by the blues, for example. The point is, there s a revolution in research productivity here. That s why Wired Magazine call it the end of science. 6

7 7

8 8

9 Big Data is massive new data volumes This is a typical Australian electricity bill. How often do I get one of these? (guess) every 3 months. (Why? Because a person has to physically walk up to the meter and read it.) very manual. Can only be done a few times a year. Now, the electricity company has a data warehouse which captures all their billing data. They use it to analyse usage patterns across parts of the network (and not much else). Their data warehouse might be 3 terabytes. Not huge. This is a smart meter. The smart meter provides readings directly to the utility via wireless or mobile phone networks every 5 minutes. So instead of one reading per customer every three months, we can access a record per customer every 5 minutes. So the data has just grown 3000 times. (That s big data). So suddenly the utility, to retain the same level of customer data, needs 9 petabytes of data warehouse. Most of it becomes exhaust data but there is tremendous value in this data if you can keep it and analyse it. -Network load analysis over time -Better decisions on where to increase network capacity -Real-time alerts when a particular power node is approaching saturation -You can also provide the information back to your customers 9

10 10

11 This is the Silverspring web site, a screenshot taken about 2 weeks ago. Notice the promise here to the consumer See your energy use in real time you only want to promise that if your database can perform, can handle huge numbers of ad-hoc queries from consumers accessing your website 24 x 7. SilverSpring use Greenplum to capture all the readings from their smart meters into a database, and they make this data available to their customers. 11

12 An example of what consumer-facing real-time electricity usage looks like

13 But it s not just for the consumers the real value for the utility is what they can do with the data themselves: -Predictive maintenance -Usage trends over time down to the suburb and street level -Geo-spatial mappings over streets looking weather-related incidents, maintenance cost anomalies and so on. -(I worked with a Utility in Sydney where, using their data warehouse, they were able to identify some motors and pumps that were starting and stopping several times an hour, and others that only cycled once or twice a day or week so instead of blindly sending around a maintenance crew every 3 months, they could maintain some pumps every month and other pumps only twice a year. Savings of several $M) 13 13

14 14

15 15

16 16

17 17

18 And here are some examples of the kind of analytics that can be run against different types of data, and the kind of insights you can expect to gain His point is that traditional data warehousing architectures don t cater for these types of analytics. 18

19 Firstly, lets cover the name. Hadoop was created by Doug Cutting who named his new project after his son s favorite toy, a stuffed elephant, for which the boy had made up the name. His elephant s name was Hadoop! So it is not an acronym, and it doesn t have a special hidden meaning, it is simply the name of a toy elephant. 19

20 I am sure we have all heard the hype.hadoop is increasingly generating the attention of the press and the IT industry as a transformative technology, and can be used to obtain the competitive advantage, if you read some of these quotes you would be saying, where can I get one! 20

21 On the flip side, when you dig a little deeper you can find some hidden facts. Although Hadoop does have real momentum in the market today, as it says on the slide, only a few enterprise vendors have adopted hadoop. Companies may say they have it on their fast track, or are evaluating it..but as we shall soon find out, traditional Hadoop is difficult and does lack some of the features, functionalities, and deployment options needed to be easily adopted by enterprises. 21

22 While a number of technologies fall under the Big Data label, Hadoop is the Big Data mascot. Remember it stands front and center in the discussion of how to implement a big data strategy. Early adopters are google, facebook, linkedin and yahoo, but it is now becoming mainstream, so what is it? 22

23 Trying to understand Hadoop concepts in the context of the wrong architecture design can actually hurt our brains Hadoop was not designed with the typical enterprise environment in mind. Hadoop was designed for a Cluster Architecture built out of commodity x86 hardware with DAS using Open source software based off of papers written by Google. Why base Hadoop on a cluster architecture? Linearly and horizontally scalable Open source software based off of papers written by Google Able to store and query massive amounts of unstructured data Fault tolerant, reliable storage Inexpensive to build and maintain Hide complexity with a common interface These are the elements that were a critical part of the hadoop design. 23

24 Here it is, this is Hadoop is all its glory. Hadoop harnesses the Cluster architecture, by addressing two key points: The layout of the data across the cluster, ensuring that data is evenly distributed; And then present that evenly distributed data back to the applications so they can benefit from Data Locality; And that brings us to Hadoop s two main mechanisms: Hadoop Distributed File System Hadoop MapReduce HDFS is the distributed file system that lets Hadoop scale across commodity servers. That part is easy, we all know what filesystems are and HDFS is no different, it stores data across all nodes that participate in an hadoop cluster. MapReduce is the parallel-processing engine that allows Hadoop to churn through that data, quickly. These are the two must-have components for any Hadoop cluster and together they take care of all complexities for us in leveraging the parallel processing power of a cluster. You now know what Hadoop is at a high level, lets looks at the detail. 24

25 In a traditional Hadoop Architecture, we now can visualise the major components. 1. Map-reduce (Job Tracker and task tracker) 2. Namenode and Secondary namenode (A HDFS NameNode stores Edit logs and File system Image). 3. Datanode (Runs on slaves) In a traditional architecture the compute nodes and the storage nodes can be one in the same. 25

26 So now we are clear on what hadoop is and how it fits within an environment, it does come with some challenges. Namenode failover is not seamless. Poor utilization of storage and CPU resources in Hadoop clusters Inefficient data staging and loading processes Backup and disaster recovery missing Servers with Direct Attached Storage (DAS) islands of storage, remember the 90 s? Data Protection: 3x mirror of all data Data Ingest: Difficult and tool dependent (No common protocol access) Scaling: Add more servers with DAS Single Points of Failure: NameNode Replication: None Data Recovery: Recreate data from other sources 26

27 27

28 28

29 29

30 30

31 31

32 32

33 33

34 34

35 35

36 36

37 37

38 38

39 39

40 40

41 41

42 42

43 43

44 44

45 45

46 46

47 47

48 48

49 49

50 50

51 51

52 52

53 53

54 54

55 55

56 56

57 57

Introduction to Hadoop HDFS and Ecosystems. Slides credits: Cloudera Academic Partners Program & Prof. De Liu, MSBA 6330 Harvesting Big Data

Introduction to Hadoop HDFS and Ecosystems. Slides credits: Cloudera Academic Partners Program & Prof. De Liu, MSBA 6330 Harvesting Big Data Introduction to Hadoop HDFS and Ecosystems ANSHUL MITTAL Slides credits: Cloudera Academic Partners Program & Prof. De Liu, MSBA 6330 Harvesting Big Data Topics The goal of this presentation is to give

More information

Chapter 7. Using Hadoop Cluster and MapReduce

Chapter 7. Using Hadoop Cluster and MapReduce Chapter 7 Using Hadoop Cluster and MapReduce Modeling and Prototyping of RMS for QoS Oriented Grid Page 152 7. Using Hadoop Cluster and MapReduce for Big Data Problems The size of the databases used in

More information

BIG DATA TRENDS AND TECHNOLOGIES

BIG DATA TRENDS AND TECHNOLOGIES BIG DATA TRENDS AND TECHNOLOGIES THE WORLD OF DATA IS CHANGING Cloud WHAT IS BIG DATA? Big data are datasets that grow so large that they become awkward to work with using onhand database management tools.

More information

Large scale processing using Hadoop. Ján Vaňo

Large scale processing using Hadoop. Ján Vaňo Large scale processing using Hadoop Ján Vaňo What is Hadoop? Software platform that lets one easily write and run applications that process vast amounts of data Includes: MapReduce offline computing engine

More information

Open source software framework designed for storage and processing of large scale data on clusters of commodity hardware

Open source software framework designed for storage and processing of large scale data on clusters of commodity hardware Open source software framework designed for storage and processing of large scale data on clusters of commodity hardware Created by Doug Cutting and Mike Carafella in 2005. Cutting named the program after

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

AGENDA. What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story. Our BIG DATA Roadmap. Hadoop PDW

AGENDA. What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story. Our BIG DATA Roadmap. Hadoop PDW AGENDA What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story Hadoop PDW Our BIG DATA Roadmap BIG DATA? Volume 59% growth in annual WW information 1.2M Zetabytes (10 21 bytes) this

More information

Data Refinery with Big Data Aspects

Data Refinery with Big Data Aspects International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 7 (2013), pp. 655-662 International Research Publications House http://www. irphouse.com /ijict.htm Data

More information

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014 White Paper Big Data Executive Overview WP-BD-10312014-01 By Jafar Shunnar & Dan Raver Page 1 Last Updated 11-10-2014 Table of Contents Section 01 Big Data Facts Page 3-4 Section 02 What is Big Data? Page

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics February 11, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics

HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics ESSENTIALS EMC ISILON Use the industry's first and only scale-out NAS solution with native Hadoop

More information

Introduction to Hadoop. New York Oracle User Group Vikas Sawhney

Introduction to Hadoop. New York Oracle User Group Vikas Sawhney Introduction to Hadoop New York Oracle User Group Vikas Sawhney GENERAL AGENDA Driving Factors behind BIG-DATA NOSQL Database 2014 Database Landscape Hadoop Architecture Map/Reduce Hadoop Eco-system Hadoop

More information

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK A COMPREHENSIVE VIEW OF HADOOP ER. AMRINDER KAUR Assistant Professor, Department

More information

INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE

INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE AGENDA Introduction to Big Data Introduction to Hadoop HDFS file system Map/Reduce framework Hadoop utilities Summary BIG DATA FACTS In what timeframe

More information

Big Data Analytics. with EMC Greenplum and Hadoop. Big Data Analytics. Ofir Manor Pre Sales Technical Architect EMC Greenplum

Big Data Analytics. with EMC Greenplum and Hadoop. Big Data Analytics. Ofir Manor Pre Sales Technical Architect EMC Greenplum Big Data Analytics with EMC Greenplum and Hadoop Big Data Analytics with EMC Greenplum and Hadoop Ofir Manor Pre Sales Technical Architect EMC Greenplum 1 Big Data and the Data Warehouse Potential All

More information

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Wayne W. Eckerson Director of Research, TechTarget Founder, BI Leadership Forum Business Analytics

More information

EMC s Enterprise Hadoop Solution. By Julie Lockner, Senior Analyst, and Terri McClure, Senior Analyst

EMC s Enterprise Hadoop Solution. By Julie Lockner, Senior Analyst, and Terri McClure, Senior Analyst White Paper EMC s Enterprise Hadoop Solution Isilon Scale-out NAS and Greenplum HD By Julie Lockner, Senior Analyst, and Terri McClure, Senior Analyst February 2012 This ESG White Paper was commissioned

More information

CSE-E5430 Scalable Cloud Computing Lecture 2

CSE-E5430 Scalable Cloud Computing Lecture 2 CSE-E5430 Scalable Cloud Computing Lecture 2 Keijo Heljanko Department of Computer Science School of Science Aalto University keijo.heljanko@aalto.fi 14.9-2015 1/36 Google MapReduce A scalable batch processing

More information

Data Centric Computing Revisited

Data Centric Computing Revisited Piyush Chaudhary Technical Computing Solutions Data Centric Computing Revisited SPXXL/SCICOMP Summer 2013 Bottom line: It is a time of Powerful Information Data volume is on the rise Dimensions of data

More information

Executive Summary... 2 Introduction... 3. Defining Big Data... 3. The Importance of Big Data... 4 Building a Big Data Platform...

Executive Summary... 2 Introduction... 3. Defining Big Data... 3. The Importance of Big Data... 4 Building a Big Data Platform... Executive Summary... 2 Introduction... 3 Defining Big Data... 3 The Importance of Big Data... 4 Building a Big Data Platform... 5 Infrastructure Requirements... 5 Solution Spectrum... 6 Oracle s Big Data

More information

www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage

www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage If every image made and every word written from the earliest stirring of civilization

More information

Hadoop Distributed File System. Jordan Prosch, Matt Kipps

Hadoop Distributed File System. Jordan Prosch, Matt Kipps Hadoop Distributed File System Jordan Prosch, Matt Kipps Outline - Background - Architecture - Comments & Suggestions Background What is HDFS? Part of Apache Hadoop - distributed storage What is Hadoop?

More information

Building & Optimizing Enterprise-class Hadoop with Open Architectures Prem Jain NetApp

Building & Optimizing Enterprise-class Hadoop with Open Architectures Prem Jain NetApp Building & Optimizing Enterprise-class Hadoop with Open Architectures Prem Jain NetApp Introduction to Hadoop Comes from Internet companies Emerging big data storage and analytics platform HDFS and MapReduce

More information

NextGen Infrastructure for Big DATA Analytics.

NextGen Infrastructure for Big DATA Analytics. NextGen Infrastructure for Big DATA Analytics. So What is Big Data? Data that exceeds the processing capacity of conven4onal database systems. The data is too big, moves too fast, or doesn t fit the structures

More information

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Managing Big Data with Hadoop & Vertica A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Copyright Vertica Systems, Inc. October 2009 Cloudera and Vertica

More information

Prepared By : Manoj Kumar Joshi & Vikas Sawhney

Prepared By : Manoj Kumar Joshi & Vikas Sawhney Prepared By : Manoj Kumar Joshi & Vikas Sawhney General Agenda Introduction to Hadoop Architecture Acknowledgement Thanks to all the authors who left their selfexplanatory images on the internet. Thanks

More information

DEFINITELY. GAME CHANGER? EVOLUTION? Big Data

DEFINITELY. GAME CHANGER? EVOLUTION? Big Data Big Data EVOLUTION? GAME CHANGER? DEFINITELY. EMC s Bill Schmarzo and consultant Ben Woo weigh in on whether Big Data is revolutionary, evolutionary, or both. by Terry Brown EMC+ In a recent survey of

More information

Big Data - Infrastructure Considerations

Big Data - Infrastructure Considerations April 2014, HAPPIEST MINDS TECHNOLOGIES Big Data - Infrastructure Considerations Author Anand Veeramani / Deepak Shivamurthy SHARING. MINDFUL. INTEGRITY. LEARNING. EXCELLENCE. SOCIAL RESPONSIBILITY. Copyright

More information

Hadoop Architecture. Part 1

Hadoop Architecture. Part 1 Hadoop Architecture Part 1 Node, Rack and Cluster: A node is simply a computer, typically non-enterprise, commodity hardware for nodes that contain data. Consider we have Node 1.Then we can add more nodes,

More information

Big Data on Microsoft Platform

Big Data on Microsoft Platform Big Data on Microsoft Platform Prepared by GJ Srinivas Corporate TEG - Microsoft Page 1 Contents 1. What is Big Data?...3 2. Characteristics of Big Data...3 3. Enter Hadoop...3 4. Microsoft Big Data Solutions...4

More information

Big Data Buzzwords From A to Z. By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012

Big Data Buzzwords From A to Z. By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012 Big Data Buzzwords From A to Z By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012 Big Data Buzzwords Big data is one of the, well, biggest trends in IT today, and it has spawned a whole new generation

More information

A Survey on Big Data Concepts and Tools

A Survey on Big Data Concepts and Tools A Survey on Big Data Concepts and Tools D. Rajasekar 1, C. Dhanamani 2, S. K. Sandhya 3 1,3 PG Scholar, 2 Assistant Professor, Department of Computer Science and Engineering, Sri Krishna College of Engineering

More information

Welcome to the unit of Hadoop Fundamentals on Hadoop architecture. I will begin with a terminology review and then cover the major components

Welcome to the unit of Hadoop Fundamentals on Hadoop architecture. I will begin with a terminology review and then cover the major components Welcome to the unit of Hadoop Fundamentals on Hadoop architecture. I will begin with a terminology review and then cover the major components of Hadoop. We will see what types of nodes can exist in a Hadoop

More information

Big Data Big Deal? Salford Systems www.salford-systems.com

Big Data Big Deal? Salford Systems www.salford-systems.com Big Data Big Deal? Salford Systems www.salford-systems.com 2015 Copyright Salford Systems 2010-2015 Big Data Is The New In Thing Google trends as of September 24, 2015 Difficult to read trade press without

More information

Business Analytics In a Big Data World Ted Malone Solutions Architect Data Platform and Cloud Microsoft Federal

Business Analytics In a Big Data World Ted Malone Solutions Architect Data Platform and Cloud Microsoft Federal Business Analytics In a Big Data World Ted Malone Solutions Architect Data Platform and Cloud Microsoft Federal Information has gone from scarce to super-abundant. That brings huge new benefits. The Economist

More information

Networking in the Hadoop Cluster

Networking in the Hadoop Cluster Hadoop and other distributed systems are increasingly the solution of choice for next generation data volumes. A high capacity, any to any, easily manageable networking layer is critical for peak Hadoop

More information

White. Paper. EMC Isilon: A Scalable Storage Platform for Big Data. April 2014

White. Paper. EMC Isilon: A Scalable Storage Platform for Big Data. April 2014 White Paper EMC Isilon: A Scalable Storage Platform for Big Data By Nik Rouda, Senior Analyst and Terri McClure, Senior Analyst April 2014 This ESG White Paper was commissioned by EMC Isilon and is distributed

More information

Beyond Web Application Log Analysis using Apache TM Hadoop. A Whitepaper by Orzota, Inc.

Beyond Web Application Log Analysis using Apache TM Hadoop. A Whitepaper by Orzota, Inc. Beyond Web Application Log Analysis using Apache TM Hadoop A Whitepaper by Orzota, Inc. 1 Web Applications As more and more software moves to a Software as a Service (SaaS) model, the web application has

More information

Overview. Big Data in Apache Hadoop. - HDFS - MapReduce in Hadoop - YARN. https://hadoop.apache.org. Big Data Management and Analytics

Overview. Big Data in Apache Hadoop. - HDFS - MapReduce in Hadoop - YARN. https://hadoop.apache.org. Big Data Management and Analytics Overview Big Data in Apache Hadoop - HDFS - MapReduce in Hadoop - YARN https://hadoop.apache.org 138 Apache Hadoop - Historical Background - 2003: Google publishes its cluster architecture & DFS (GFS)

More information

Virtualizing Apache Hadoop. June, 2012

Virtualizing Apache Hadoop. June, 2012 June, 2012 Table of Contents EXECUTIVE SUMMARY... 3 INTRODUCTION... 3 VIRTUALIZING APACHE HADOOP... 4 INTRODUCTION TO VSPHERE TM... 4 USE CASES AND ADVANTAGES OF VIRTUALIZING HADOOP... 4 MYTHS ABOUT RUNNING

More information

DATA MINING WITH HADOOP AND HIVE Introduction to Architecture

DATA MINING WITH HADOOP AND HIVE Introduction to Architecture DATA MINING WITH HADOOP AND HIVE Introduction to Architecture Dr. Wlodek Zadrozny (Most slides come from Prof. Akella s class in 2014) 2015-2025. Reproduction or usage prohibited without permission of

More information

Building your Big Data Architecture on Amazon Web Services

Building your Big Data Architecture on Amazon Web Services Building your Big Data Architecture on Amazon Web Services Abhishek Sinha @abysinha sinhaar@amazon.com AWS Services Deployment & Administration Application Services Compute Storage Database Networking

More information

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP Pythian White Paper TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP ABSTRACT As companies increasingly rely on big data to steer decisions, they also find themselves looking for ways to simplify

More information

In-Memory Analytics for Big Data

In-Memory Analytics for Big Data In-Memory Analytics for Big Data Game-changing technology for faster, better insights WHITE PAPER SAS White Paper Table of Contents Introduction: A New Breed of Analytics... 1 SAS In-Memory Overview...

More information

Advanced In-Database Analytics

Advanced In-Database Analytics Advanced In-Database Analytics Tallinn, Sept. 25th, 2012 Mikko-Pekka Bertling, BDM Greenplum EMEA 1 That sounds complicated? 2 Who can tell me how best to solve this 3 What are the main mathematical functions??

More information

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM Sneha D.Borkar 1, Prof.Chaitali S.Surtakar 2 Student of B.E., Information Technology, J.D.I.E.T, sborkar95@gmail.com Assistant Professor, Information

More information

Hadoop IST 734 SS CHUNG

Hadoop IST 734 SS CHUNG Hadoop IST 734 SS CHUNG Introduction What is Big Data?? Bulk Amount Unstructured Lots of Applications which need to handle huge amount of data (in terms of 500+ TB per day) If a regular machine need to

More information

Apache Hadoop. Alexandru Costan

Apache Hadoop. Alexandru Costan 1 Apache Hadoop Alexandru Costan Big Data Landscape No one-size-fits-all solution: SQL, NoSQL, MapReduce, No standard, except Hadoop 2 Outline What is Hadoop? Who uses it? Architecture HDFS MapReduce Open

More information

Job Oriented Instructor Led Face2Face True Live Online I.T. Training for Everyone Worldwide

Job Oriented Instructor Led Face2Face True Live Online I.T. Training for Everyone Worldwide H2kInfosys H2K Infosys provides online IT training and placement services worldwide. www.h2kinfosys.com USA- +1-(770)-777-1269, UK (020) 33717615 Training@H2KINFOSYS.com / H2KInfosys@gmail.com DISCLAIMER

More information

Hadoop implementation of MapReduce computational model. Ján Vaňo

Hadoop implementation of MapReduce computational model. Ján Vaňo Hadoop implementation of MapReduce computational model Ján Vaňo What is MapReduce? A computational model published in a paper by Google in 2004 Based on distributed computation Complements Google s distributed

More information

Microsoft Big Data Solutions. Anar Taghiyev P-TSP E-mail: b-anarta@microsoft.com;

Microsoft Big Data Solutions. Anar Taghiyev P-TSP E-mail: b-anarta@microsoft.com; Microsoft Big Data Solutions Anar Taghiyev P-TSP E-mail: b-anarta@microsoft.com; Why/What is Big Data and Why Microsoft? Options of storage and big data processing in Microsoft Azure. Real Impact of Big

More information

BIG DATA USING HADOOP

BIG DATA USING HADOOP + Breakaway Session By Johnson Iyilade, Ph.D. University of Saskatchewan, Canada 23-July, 2015 BIG DATA USING HADOOP + Outline n Framing the Problem Hadoop Solves n Meet Hadoop n Storage with HDFS n Data

More information

Can Storage Fix Hadoop

Can Storage Fix Hadoop Can Storage Fix Hadoop John Webster, Senior Partner 9/18/2013 1 Agenda What is the Internet Data Center and how is it different from Enterprise Data Center? How is the Apache Software Foundation (ASF)

More information

Distributed Computing and Hadoop in Statistics

Distributed Computing and Hadoop in Statistics Distributed Computing and Hadoop in Statistics Xiaoling Lu and Bing Zheng Center For Applied Statistics, Renmin University of China, Beijing, China Corresponding author: Xiaoling Lu, e-mail: xiaolinglu@ruc.edu.cn

More information

HP Vertica OnDemand. Vertica OnDemand. Enterprise-class Big Data analytics in the cloud. Enterprise-class Big Data analytics for any size organization

HP Vertica OnDemand. Vertica OnDemand. Enterprise-class Big Data analytics in the cloud. Enterprise-class Big Data analytics for any size organization Data sheet HP Vertica OnDemand Enterprise-class Big Data analytics in the cloud Enterprise-class Big Data analytics for any size organization Vertica OnDemand Organizations today are experiencing a greater

More information

A Brief Outline on Bigdata Hadoop

A Brief Outline on Bigdata Hadoop A Brief Outline on Bigdata Hadoop Twinkle Gupta 1, Shruti Dixit 2 RGPV, Department of Computer Science and Engineering, Acropolis Institute of Technology and Research, Indore, India Abstract- Bigdata is

More information

Data Warehousing and Analytics Infrastructure at Facebook. Ashish Thusoo & Dhruba Borthakur athusoo,dhruba@facebook.com

Data Warehousing and Analytics Infrastructure at Facebook. Ashish Thusoo & Dhruba Borthakur athusoo,dhruba@facebook.com Data Warehousing and Analytics Infrastructure at Facebook Ashish Thusoo & Dhruba Borthakur athusoo,dhruba@facebook.com Overview Challenges in a Fast Growing & Dynamic Environment Data Flow Architecture,

More information

The 3 questions to ask yourself about BIG DATA

The 3 questions to ask yourself about BIG DATA The 3 questions to ask yourself about BIG DATA Do you have a big data problem? Companies looking to tackle big data problems are embarking on a journey that is full of hype, buzz, confusion, and misinformation.

More information

CDH AND BUSINESS CONTINUITY:

CDH AND BUSINESS CONTINUITY: WHITE PAPER CDH AND BUSINESS CONTINUITY: An overview of the availability, data protection and disaster recovery features in Hadoop Abstract Using the sophisticated built-in capabilities of CDH for tunable

More information

EMC BACKUP MEETS BIG DATA

EMC BACKUP MEETS BIG DATA EMC BACKUP MEETS BIG DATA Strategies To Protect Greenplum, Isilon And Teradata Systems 1 Agenda Big Data: Overview, Backup and Recovery EMC Big Data Backup Strategy EMC Backup and Recovery Solutions for

More information

Hadoop & its Usage at Facebook

Hadoop & its Usage at Facebook Hadoop & its Usage at Facebook Dhruba Borthakur Project Lead, Hadoop Distributed File System dhruba@apache.org Presented at the Storage Developer Conference, Santa Clara September 15, 2009 Outline Introduction

More information

Big Data, Big Traffic. And the WAN

Big Data, Big Traffic. And the WAN Big Data, Big Traffic And the WAN Internet Research Group January, 2012 About The Internet Research Group www.irg-intl.com The Internet Research Group (IRG) provides market research and market strategy

More information

Protecting Big Data Data Protection Solutions for the Business Data Lake

Protecting Big Data Data Protection Solutions for the Business Data Lake White Paper Protecting Big Data Data Protection Solutions for the Business Data Lake Abstract Big Data use cases are maturing and customers are using Big Data to improve top and bottom line revenues. With

More information

Hadoop and its Usage at Facebook. Dhruba Borthakur dhruba@apache.org, June 22 rd, 2009

Hadoop and its Usage at Facebook. Dhruba Borthakur dhruba@apache.org, June 22 rd, 2009 Hadoop and its Usage at Facebook Dhruba Borthakur dhruba@apache.org, June 22 rd, 2009 Who Am I? Hadoop Developer Core contributor since Hadoop s infancy Focussed on Hadoop Distributed File System Facebook

More information

Ubuntu and Hadoop: the perfect match

Ubuntu and Hadoop: the perfect match WHITE PAPER Ubuntu and Hadoop: the perfect match February 2012 Copyright Canonical 2012 www.canonical.com Executive introduction In many fields of IT, there are always stand-out technologies. This is definitely

More information

An Oracle White Paper October 2011. Oracle: Big Data for the Enterprise

An Oracle White Paper October 2011. Oracle: Big Data for the Enterprise An Oracle White Paper October 2011 Oracle: Big Data for the Enterprise Executive Summary... 2 Introduction... 3 Defining Big Data... 3 The Importance of Big Data... 4 Building a Big Data Platform... 5

More information

BIG DATA What it is and how to use?

BIG DATA What it is and how to use? BIG DATA What it is and how to use? Lauri Ilison, PhD Data Scientist 21.11.2014 Big Data definition? There is no clear definition for BIG DATA BIG DATA is more of a concept than precise term 1 21.11.14

More information

Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities

Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities Technology Insight Paper Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities By John Webster February 2015 Enabling you to make the best technology decisions Enabling

More information

Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies

Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies Research Article / Survey Paper / Case Study Available online at: www.ijarcsms.com Image

More information

Better Business Decisions at a Lower Cost with IBM InfoSphere BigInsights Solution Guide

Better Business Decisions at a Lower Cost with IBM InfoSphere BigInsights Solution Guide Better Business Decisions at a Lower Cost with IBM InfoSphere BigInsights Solution Guide Did you know? With the advent of email, smartphones, social media, sensors, and machine-generated data, significantly

More information

HadoopTM Analytics DDN

HadoopTM Analytics DDN DDN Solution Brief Accelerate> HadoopTM Analytics with the SFA Big Data Platform Organizations that need to extract value from all data can leverage the award winning SFA platform to really accelerate

More information

Big + Fast + Safe + Simple = Lowest Technical Risk

Big + Fast + Safe + Simple = Lowest Technical Risk Big + Fast + Safe + Simple = Lowest Technical Risk The Synergy of Greenplum and Isilon Architecture in HP Environments Steffen Thuemmel (Isilon) Andreas Scherbaum (Greenplum) 1 Our problem 2 What is Big

More information

So What s the Big Deal?

So What s the Big Deal? So What s the Big Deal? Presentation Agenda Introduction What is Big Data? So What is the Big Deal? Big Data Technologies Identifying Big Data Opportunities Conducting a Big Data Proof of Concept Big Data

More information

Agenda. Big Data & Hadoop ViPR HDFS Pivotal Big Data Suite & ViPR HDFS ViON Customer Feedback #EMCVIPR

Agenda. Big Data & Hadoop ViPR HDFS Pivotal Big Data Suite & ViPR HDFS ViON Customer Feedback #EMCVIPR 1 Agenda Big Data & Hadoop ViPR HDFS Pivotal Big Data Suite & ViPR HDFS ViON Customer Feedback 2 A World of Connected Devices Need a new data management architecture for Internet of Things 21% the % of

More information

An Industrial Perspective on the Hadoop Ecosystem. Eldar Khalilov Pavel Valov

An Industrial Perspective on the Hadoop Ecosystem. Eldar Khalilov Pavel Valov An Industrial Perspective on the Hadoop Ecosystem Eldar Khalilov Pavel Valov agenda 03.12.2015 2 agenda Introduction 03.12.2015 2 agenda Introduction Research goals 03.12.2015 2 agenda Introduction Research

More information

Real Time Big Data Processing

Real Time Big Data Processing Real Time Big Data Processing Cloud Expo 2014 Ian Meyers Amazon Web Services Global Infrastructure Deployment & Administration App Services Analytics Compute Storage Database Networking AWS Global Infrastructure

More information

Role of Cloud Computing in Big Data Analytics Using MapReduce Component of Hadoop

Role of Cloud Computing in Big Data Analytics Using MapReduce Component of Hadoop Role of Cloud Computing in Big Data Analytics Using MapReduce Component of Hadoop Kanchan A. Khedikar Department of Computer Science & Engineering Walchand Institute of Technoloy, Solapur, Maharashtra,

More information

What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER

What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER A NEW PARADIGM IN INFORMATION TECHNOLOGY There is a revolution happening in information technology, and it s not

More information

Breaking News! Big Data is Solved. What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER

Breaking News! Big Data is Solved. What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER Breaking News! Big Data is Solved. What Is In-Memory Computing and What Does It Mean to U.S. Leaders? EXECUTIVE WHITE PAPER There is a revolution happening in information technology, and it s not just

More information

L1: Introduction to Hadoop

L1: Introduction to Hadoop L1: Introduction to Hadoop Feng Li feng.li@cufe.edu.cn School of Statistics and Mathematics Central University of Finance and Economics Revision: December 1, 2014 Today we are going to learn... 1 General

More information

Hadoop Distributed File System. T-111.5550 Seminar On Multimedia 2009-11-11 Eero Kurkela

Hadoop Distributed File System. T-111.5550 Seminar On Multimedia 2009-11-11 Eero Kurkela Hadoop Distributed File System T-111.5550 Seminar On Multimedia 2009-11-11 Eero Kurkela Agenda Introduction Flesh and bones of HDFS Architecture Accessing data Data replication strategy Fault tolerance

More information

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 It s going mainstream, and it s your next opportunity. by Merv Adrian Enterprises have never had more data, and it s no surprise

More information

Reduction of Data at Namenode in HDFS using harballing Technique

Reduction of Data at Namenode in HDFS using harballing Technique Reduction of Data at Namenode in HDFS using harballing Technique Vaibhav Gopal Korat, Kumar Swamy Pamu vgkorat@gmail.com swamy.uncis@gmail.com Abstract HDFS stands for the Hadoop Distributed File System.

More information

There s no way around it: learning about Big Data means

There s no way around it: learning about Big Data means In This Chapter Chapter 1 Introducing Big Data Beginning with Big Data Meeting MapReduce Saying hello to Hadoop Making connections between Big Data, MapReduce, and Hadoop There s no way around it: learning

More information

Big Data Storage Architecture Design in Cloud Computing

Big Data Storage Architecture Design in Cloud Computing Big Data Storage Architecture Design in Cloud Computing Xuebin Chen 1, Shi Wang 1( ), Yanyan Dong 1, and Xu Wang 2 1 College of Science, North China University of Science and Technology, Tangshan, Hebei,

More information

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ End to End Solution to Accelerate Data Warehouse Optimization Franco Flore Alliance Sales Director - APJ Big Data Is Driving Key Business Initiatives Increase profitability, innovation, customer satisfaction,

More information

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time SCALEOUT SOFTWARE How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time by Dr. William Bain and Dr. Mikhail Sobolev, ScaleOut Software, Inc. 2012 ScaleOut Software, Inc. 12/27/2012 T wenty-first

More information

BIG DATA TECHNOLOGY. Hadoop Ecosystem

BIG DATA TECHNOLOGY. Hadoop Ecosystem BIG DATA TECHNOLOGY Hadoop Ecosystem Agenda Background What is Big Data Solution Objective Introduction to Hadoop Hadoop Ecosystem Hybrid EDW Model Predictive Analysis using Hadoop Conclusion What is Big

More information

Analytics in the Cloud. Peter Sirota, GM Elastic MapReduce

Analytics in the Cloud. Peter Sirota, GM Elastic MapReduce Analytics in the Cloud Peter Sirota, GM Elastic MapReduce Data-Driven Decision Making Data is the new raw material for any business on par with capital, people, and labor. What is Big Data? Terabytes of

More information

Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics

Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics Dharmendra Agawane 1, Rohit Pawar 2, Pavankumar Purohit 3, Gangadhar Agre 4 Guide: Prof. P B Jawade 2

More information

Hadoop Distributed File System. Dhruba Borthakur Apache Hadoop Project Management Committee dhruba@apache.org dhruba@facebook.com

Hadoop Distributed File System. Dhruba Borthakur Apache Hadoop Project Management Committee dhruba@apache.org dhruba@facebook.com Hadoop Distributed File System Dhruba Borthakur Apache Hadoop Project Management Committee dhruba@apache.org dhruba@facebook.com Hadoop, Why? Need to process huge datasets on large clusters of computers

More information

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QlikView Technical Case Study Series Big Data June 2012 qlikview.com Introduction This QlikView technical case study focuses on the QlikView deployment

More information

Modernizing Your Data Warehouse for Hadoop

Modernizing Your Data Warehouse for Hadoop Modernizing Your Data Warehouse for Hadoop Big data. Small data. All data. Audie Wright, DW & Big Data Specialist Audie.Wright@Microsoft.com O 425-538-0044, C 303-324-2860 Unlock Insights on Any Data Taking

More information

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Hadoop MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Understanding Hadoop Understanding Hadoop What's Hadoop about? Apache Hadoop project (started 2008) downloadable open-source software library (current

More information

An Oracle White Paper June 2013. Oracle: Big Data for the Enterprise

An Oracle White Paper June 2013. Oracle: Big Data for the Enterprise An Oracle White Paper June 2013 Oracle: Big Data for the Enterprise Executive Summary... 2 Introduction... 3 Defining Big Data... 3 The Importance of Big Data... 4 Building a Big Data Platform... 5 Infrastructure

More information

Introduction to Cloud Computing

Introduction to Cloud Computing Introduction to Cloud Computing Cloud Computing I (intro) 15 319, spring 2010 2 nd Lecture, Jan 14 th Majd F. Sakr Lecture Motivation General overview on cloud computing What is cloud computing Services

More information

Design and Evolution of the Apache Hadoop File System(HDFS)

Design and Evolution of the Apache Hadoop File System(HDFS) Design and Evolution of the Apache Hadoop File System(HDFS) Dhruba Borthakur Engineer@Facebook Committer@Apache HDFS SDC, Sept 19 2011 Outline Introduction Yet another file-system, why? Goals of Hadoop

More information

Hadoop & its Usage at Facebook

Hadoop & its Usage at Facebook Hadoop & its Usage at Facebook Dhruba Borthakur Project Lead, Hadoop Distributed File System dhruba@apache.org Presented at the The Israeli Association of Grid Technologies July 15, 2009 Outline Architecture

More information