Big data refers to large amounts of data from various sources that is analyzed to solve problems. It is characterized by volume, velocity, and variety. Hadoop is an open source framework used to store and process big data across clusters of computers. Key components of Hadoop include HDFS for storage, MapReduce for processing, and HIVE for querying. Other tools like Pig and HBase provide additional functionality. Together these tools provide a scalable infrastructure to handle the volume, speed, and complexity of big data.
This presentation Simplify the concepts of Big data and NoSQL databases & Hadoop components.
The Original Source:
http://zohararad.github.io/presentations/big-data-introduction/
A short overview of Bigdata along with its popularity, ups and downs from past to present. We had a look of its needs, challenges and risks too. Architectures involved in it. Vendors associated with it.
Asserting that Big Data is vital to business is an understatement. Organizations have generated more and more data for years, but struggle to use it effectively. Clearly Big Data has more important uses than ensuring compliance with regulatory requirements. In addition, data is being generated with greater velocity, due to the advent of new pervasive devices (e.g., smartphones, tablets, etc.), social Web sites (e.g., Facebook, Twitter, LinkedIn, etc.) and other sources like GPS, Google Maps, heat/pressure sensors, etc.
Introduction to Big Data and Hadoop using Local Standalone Modeinventionjournals
Big Data is a term defined for data sets that are extreme and complex where traditional data processing applications are inadequate to deal with them. The term Big Data often refers simply to the use of predictive investigation on analytic methods that extract value from data. Big data is generalized as a large data which is a collection of big datasets that cannot be processed using traditional computing techniques. Big data is not purely a data, rather than it is a complete subject involves various tools, techniques and frameworks. Big data can be any structured collection which results incapability of conventional data management methods. Hadoop is a distributed example used to change the large amount of data. This manipulation contains not only storage as well as processing on the data. Hadoop is an open- source software framework for dispersed storage and processing of big data sets on computer clusters built from commodity hardware. HDFS was built to support high throughput, streaming reads and writes of extremely large files. Hadoop Map Reduce is a software framework for easily writing applications which process vast amounts of data. Wordcount example reads text files and counts how often words occur. The input is text files and the result is wordcount file, each line of which contains a word and the count of how often it occurred separated by a tab.
This presentation Simplify the concepts of Big data and NoSQL databases & Hadoop components.
The Original Source:
http://zohararad.github.io/presentations/big-data-introduction/
A short overview of Bigdata along with its popularity, ups and downs from past to present. We had a look of its needs, challenges and risks too. Architectures involved in it. Vendors associated with it.
Asserting that Big Data is vital to business is an understatement. Organizations have generated more and more data for years, but struggle to use it effectively. Clearly Big Data has more important uses than ensuring compliance with regulatory requirements. In addition, data is being generated with greater velocity, due to the advent of new pervasive devices (e.g., smartphones, tablets, etc.), social Web sites (e.g., Facebook, Twitter, LinkedIn, etc.) and other sources like GPS, Google Maps, heat/pressure sensors, etc.
Introduction to Big Data and Hadoop using Local Standalone Modeinventionjournals
Big Data is a term defined for data sets that are extreme and complex where traditional data processing applications are inadequate to deal with them. The term Big Data often refers simply to the use of predictive investigation on analytic methods that extract value from data. Big data is generalized as a large data which is a collection of big datasets that cannot be processed using traditional computing techniques. Big data is not purely a data, rather than it is a complete subject involves various tools, techniques and frameworks. Big data can be any structured collection which results incapability of conventional data management methods. Hadoop is a distributed example used to change the large amount of data. This manipulation contains not only storage as well as processing on the data. Hadoop is an open- source software framework for dispersed storage and processing of big data sets on computer clusters built from commodity hardware. HDFS was built to support high throughput, streaming reads and writes of extremely large files. Hadoop Map Reduce is a software framework for easily writing applications which process vast amounts of data. Wordcount example reads text files and counts how often words occur. The input is text files and the result is wordcount file, each line of which contains a word and the count of how often it occurred separated by a tab.
Harnessing Hadoop: Understanding the Big Data Processing Options for Optimizi...Cognizant
A guide to using Apache Hadoop as your open source big data platform of choice, including the vendors that make various Hadoop flavors, related open source tools, Hadoop capabilities and suitable applications.
A short presentation on big data and the technologies available for managing Big Data. and it also contains a brief description of the Apache Hadoop Framework
Big Data raises challenges about how to process such vast pool of raw data and how to aggregate value to our lives. For addressing these demands an ecosystem of tools named Hadoop was conceived.
AN OVERVIEW OF BIGDATA AND HADOOP . THE ARCHITECHTURE IT USES AND THE WAY IT WORKS ON THE DATA SETS. THE SIDES ALSO SHOW THE VARIOUS FIELDS WHERE THEY ARE MOSTLY USED AND IMPLIMENTED
Harnessing Hadoop: Understanding the Big Data Processing Options for Optimizi...Cognizant
A guide to using Apache Hadoop as your open source big data platform of choice, including the vendors that make various Hadoop flavors, related open source tools, Hadoop capabilities and suitable applications.
A short presentation on big data and the technologies available for managing Big Data. and it also contains a brief description of the Apache Hadoop Framework
Big Data raises challenges about how to process such vast pool of raw data and how to aggregate value to our lives. For addressing these demands an ecosystem of tools named Hadoop was conceived.
AN OVERVIEW OF BIGDATA AND HADOOP . THE ARCHITECHTURE IT USES AND THE WAY IT WORKS ON THE DATA SETS. THE SIDES ALSO SHOW THE VARIOUS FIELDS WHERE THEY ARE MOSTLY USED AND IMPLIMENTED
COMPARATIVE STUDY OF INDUCTION MOTOR STARTERS USING MATLAB SIMULINKIJARIIT
This paper presents a comparison between the Direct-On-Line (D.O.L.), and Soft Starter by using MATLAB Simulink .The purpose of this project is to find out the theoretical and actual characteristics of Induction motor. These three basic starting methods which different the irrespective wiring connection are the most applicable and widely-used starting method in the industrial area due to its economic reasons. This project is done by analyzing the characteristics during the motor starting by using the MATLAB Simulation to capture the waveforms of these events. After the Simulation, the three different starting method are being compared to conclude the most suitable and applicable starting method.
"Electronics for Behavioral Health" - Jim Doscher (GM Healthcare, Analog Devi...Hyper Wellbeing
"Electronics for Behavioral Health" - Jim Doscher (GM Healthcare, Analog Devices, Inc.)
Delivered at the inaugural Hyper Wellbeing Summit, 14th November 2016, Mountain View, California.
For more information including details of subsequent events, please visit http://hyperwellbeing.com
The summit was created to foster a community around an emerging industry - Wellness as a Service (WaaS). Consumer technologies, in particular wearables and mobile, are powering a consumer revolution. A revolution to turn health and wellness into platform delivered services. A revolution enabling consumer data-driven disease risk reduction. A revolution extending health care past sick care towards consumer-led lifelong health, wellness and lifestyle optimization.
WaaS newsletter sign-up http://eepurl.com/b71fdr
@hyperwellbeing
Big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware.
this presentation describes the company from where I did my summer training and what is bigdata why we use big data, big data challenges, the issue in big data, the solution of big data issues, hadoop, docker , Ansible etc.
The data management industry has matured over the last three decades, primarily based on relational database management system(RDBMS) technology. Since the amount of data collected, and analyzed in enterprises has increased several folds in volume, variety and velocityof generation and consumption, organisations have started struggling with architectural limitations of traditional RDBMS architecture. As a result a new class of systems had to be designed and implemented, giving rise to the new phenomenon of “Big Data”. In this paper we will trace the origin of new class of system called Hadoop to handle Big data.
One of the challenges in storing and processing the data and using the latest internet technologies has resulted in large volumes of data. The technique to manage this massive amount of data and to pull out the value, out of this volume is collectively called Big data. Over the recent years, there has been a rising interest in big data for social media analysis. Online social media have become the important platform across the world to share information. Facebook, one of the largest social media site receives posts in millions every day. One of the efficient technologies that deal with the Big Data is Hadoop. Hadoop, for processing large data volume jobs uses MapReduce programming model. This paper provides a survey on Hadoop and its role in facebook and a brief introduction to HIVE.
this is a presentation on hadoop basics. Hadoop is an Apache open source framework written in java that allows distributed processing of large datasets across clusters of computers using simple programming models.
Learn About Big Data and Hadoop The Most Significant ResourceAssignment Help
Data is now one of the most significant resources for businesses all around the world because of the digital revolution. However, the ability to gather, organize, process, and evaluate huge volumes of data has altered the way businesses function and arrive at educated decisions. Managing and gleaning information from the ever-expanding marine environments of information is impossible without Big Data and Hadoop. Both of which are at the vanguard of this data revolution.
If you have selected a programming language, and have difficulties writing the best assignment, get the assistance of assessment help experts to learn more about it. In this blog, we will look at the basics of Big Data and Hadoop and how they work. However, we will also explore the nature of Big Data. Also, its defining features, and the difficulties it provides. We'll also take a look at how Hadoop, an open-source platform, has become a frontrunner in the race to solve the challenges posed by Big Data. These fully appreciate the potential for change of Big Data and Hadoop for businesses across a wide range of sectors. It is necessary first to grasp the central position that they play in current data-driven decision-making.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2. What is Big Data?
Big data refers to huge amount of digital information collected from multiple
and different sources.
Big Data is one of those things that is completely transforming the way we
are doing the everyday things which leaves a digital trace which can be
used and analyzed. Big Data refers to our ability to make use of the ever
increasing volumes of data .An aim to solve new problems or old problems
in a better way.
3. Data generated by us :
Mobile Devices
Conversation data
Photo and video Image data
Social Networks data
Satellites
The Internet Of Things data
4. Big Data are characterized by 3v’s:
Volume – Data Quantity
Velocity - Data Speed
Variety – Types of data
Storing Big Data
Analyzing data characteristics
Selecting data sources for analysis
Eliminating redundant data
5. Processing Big Data
Mapping data to programming frame work
Connecting and extracting data from storage
Transforming data for processing
Subdividing data for Hadoop MapReduce
Creating the components of Hadoop MapReduce jobs
Executing Hadoop MapReduce Jobs
Monitoring the progress of the job flows
6. The Structure of Big Data
Structured – Traditional data sources , the data stored in
fields in a database
Semi-structured – a form of structured data that doesn’t
conform with the formal structure of the data models of relat
ional databases and also has tags or other markers to sepa
rate semantic elements within the data
Unstructured – video data , audio data , the data that do
esn’t reside in a traditional row-column database .
7. How is Big Data actually used?
Some examples…
Better understand and target customers
Understand and optimize business processes
Improving health
Improving security
Improving sports performance
Improving and optimizing cities and countries
There are endless applications of Big Data. Any business t
hat doesn’t seriously consider the implications of big data
runs in the risk of being left behind!
8. Infrastructure of Big Data
To handle different dimensions of big data in terms of volume , ve
locity, variety an effective and efficient design has to used proces
s large amount of data arriving at high speed from different sourc
es .Multiple faces are present here
Multi-source Big data generation
Big data Storage
Big data Processing
Cloud Computing and Big Data
Big Data needs massive amounts of memory or storage space fo
r all the data to be stored in .This is where Cloud Computing com
es into the picture which is cost saving ,scalable , provides variet
y of services like - huge processing power, high storage capabilit
y.
9. Survey paper on Big Data(IEEE)
Ms.Vibhavari Chavan, Prof.Rajesh.N.Phursule(IJCSIT paper)
Big Data usually includes data set with sizes beyond the ability of
commonly used software tools to capture, manage and process dat
a within a tolerable elapsed time .
Size of big data is constantly a moving target.
Big Data is a set of techniques and technologies that require new
form of integration to uncover large hidden values from large data s
ets.
Big data environment is used to organize and analyze various typ
es of data.
Map Reduce framework generates a lot of intermediate data.
10. Hadoop
Hadoop is open source framework
Hadoop framework is written in java
Response time varies depending on the complexity of the process
Massive scalability is the key advantage
Currently used for index web searches , email spam detection, pred
iction in financial services etc.
By storing data hadoop consists of 2components:
HDFS , Map Reduce
11. HDFS
HDFS is the file system component of Hadoop framework designed a
nd optimized to store large amounts of data on low cost hardware. Arch
itecture of HDFS has :
Name Node - kind of master node having the information abo
ut metadata. All data node address, free space, active passive type dat
a node, stored data, job tracker.
Data Node – Data node is a type of slave node in the hadoop,
which is used to save the data and there is task tracker in data node w
hich is use to track on the ongoing job on the data node and the jobs w
hich coming from name node.
14. PIG
Initially developed by Yahoo! Is a programming language used to handle any k
ind of data.
Pig had two components:
first being the language itself called “PigLatin”
second is the runtime environment where the PigLatin programs are
executed .
Look at the programming language itself so that easier than having to write
mapper and reducer programs:
• The first step in this language is to LOAD the data to be manipulate
d into HDFS
• Then run the data through a set of TRANSFORMations (in turn conve
rted into mapper and reducer tasks )
• DUMP the data to the screen or STORE the results elsewhere.
15. HIVE
Initially developed by Facebook now Apache HIVE is a data warehouse infrast
ructure built on top of hadoop for query, data summarization and analysis.
Supports analysis of datasets stored in Hadoop’s HDFS and other compatible
file systems
Different storage types – plain text, HBase and other
Metadata storage in RDBMS ,reduces time for semantic checks
Operating on compressed data stored in Hadoop
Built-in User-defined Functions(UDF’s)
SQL like queries “HiveQL” that are implicitly converted into MapReduce jobs
It provides indexes including bit map indexes to fasten the queries.
16. HBase
HBase is a column-oriented Database where as HDFS is file system
HBase has a table format with rows and columns and each table sho
uld have a Primary Key defined in it that is used for all accesses in this
HBase table. Allows many attributes to be grouped into Column familie
s .
Table schema should be predefined along with the column families ,b
ut is flexible enough to add new columns to the families at any time ,ma
king the schema flexible .
Just as HDFS’s NameNode and slave nodes MapReduce also has Jo
bTracker and TaskTracker slave nodes .
Availability of NameNode in this case is also a concern jus as in HDF
S , and is also sensitive to loss of information of the master node
17. Conclusion
Hadoop MapReduce is an open source framework used for data-sensiti
ve ,reliable, fault tolerant, scalable data, has many implementation opti
ons and allows rewriting algorithms into MapReduce.
The framework breaks up large data into smaller chunks and handles it
.
We can present the design and evaluation of a data aware cache fram
ework that requires minimum change to the original MapReduce progra
mming model for provisioning incremental processing for Big data appli
cations using the MapReduce model.