Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Hadoop Adminstration with Latest Release (2.0)Edureka!
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
Hadoop Interview Questions and Answers | Big Data Interview Questions | Hadoo...Edureka!
This Hadoop Tutorial on Hadoop Interview Questions and Answers ( Hadoop Interview Blog series: https://goo.gl/ndqlss ) will help you to prepare yourself for Big Data and Hadoop interviews. Learn about the most important Hadoop interview questions and answers and know what will set you apart in the interview process. Below are the topics covered in this Hadoop Interview Questions and Answers Tutorial:
Hadoop Interview Questions on:
1) Big Data & Hadoop
2) HDFS
3) MapReduce
4) Apache Hive
5) Apache Pig
6) Apache HBase and Sqoop
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
#HadoopInterviewQuestions #BigDataInterviewQuestions #HadoopInterview
Hadoop simplifies your job as a Data Warehousing professional. With Hadoop, you can manage any volume, variety and velocity of data, flawlessly and comparably in less time. As a Data Warehousing professional, you will undoubtedly have troubleshooting and data processing skills. These skills are sufficient for you to be a proficient Hadoop-er.
Key Questions Answered
What is Big Data and Hadoop?
What are the limitations of current Data Warehouse solutions?
How Hadoop solves these problems?
Real World Hadoop Use-Case in Data Warehouse Solutions?
Hadoop Adminstration with Latest Release (2.0)Edureka!
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
Hadoop Interview Questions and Answers | Big Data Interview Questions | Hadoo...Edureka!
This Hadoop Tutorial on Hadoop Interview Questions and Answers ( Hadoop Interview Blog series: https://goo.gl/ndqlss ) will help you to prepare yourself for Big Data and Hadoop interviews. Learn about the most important Hadoop interview questions and answers and know what will set you apart in the interview process. Below are the topics covered in this Hadoop Interview Questions and Answers Tutorial:
Hadoop Interview Questions on:
1) Big Data & Hadoop
2) HDFS
3) MapReduce
4) Apache Hive
5) Apache Pig
6) Apache HBase and Sqoop
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
#HadoopInterviewQuestions #BigDataInterviewQuestions #HadoopInterview
Hadoop simplifies your job as a Data Warehousing professional. With Hadoop, you can manage any volume, variety and velocity of data, flawlessly and comparably in less time. As a Data Warehousing professional, you will undoubtedly have troubleshooting and data processing skills. These skills are sufficient for you to be a proficient Hadoop-er.
Key Questions Answered
What is Big Data and Hadoop?
What are the limitations of current Data Warehouse solutions?
How Hadoop solves these problems?
Real World Hadoop Use-Case in Data Warehouse Solutions?
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
What is Hadoop | Introduction to Hadoop | Hadoop Tutorial | Hadoop Training |...Edureka!
This Edureka "What is Hadoop" Tutorial (check our hadoop blog series here: https://goo.gl/lQKjL8) will help you understand all the basics of Hadoop. Learn about the differences in traditional and hadoop way of storing and processing data in detail. Below are the topics covered in this tutorial:
1) Traditional Way of Processing - SEARS
2) Big Data Growth Drivers
3) Problem Associated with Big Data
4) Hadoop: Solution to Big Data Problem
5) What is Hadoop?
6) HDFS
7) MapReduce
8) Hadoop Ecosystem
9) Demo: Hadoop Case Study - Orbitz
Subscribe to our channel to get updates.
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Apache Hadoop Tutorial | Hadoop Tutorial For Beginners | Big Data Hadoop | Ha...Edureka!
This Edureka "Hadoop tutorial For Beginners" ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand the problem with traditional system while processing Big Data and how Hadoop solves it. This tutorial will provide you a comprehensive idea about HDFS and YARN along with their architecture that has been explained in a very simple manner using examples and practical demonstration. At the end, you will get to know how to analyze Olympic data set using Hadoop and gain useful insights.
Below are the topics covered in this tutorial:
1. Big Data Growth Drivers
2. What is Big Data?
3. Hadoop Introduction
4. Hadoop Master/Slave Architecture
5. Hadoop Core Components
6. HDFS Data Blocks
7. HDFS Read/Write Mechanism
8. What is MapReduce
9. MapReduce Program
10. MapReduce Job Workflow
11. Hadoop Ecosystem
12. Hadoop Use Case: Analyzing Olympic Dataset
Hadoop Administration Training | Hadoop Administration Tutorial | Hadoop Admi...Edureka!
This Edureka Hadoop Administration Training tutorial will help you understand the functions of all the Hadoop daemons and what are the configuration parameters involved with them. It will also take you through a step by step Multi-Node Hadoop Installation and will discuss all the configuration files in detail. Below are the topics covered in this tutorial:
1) What is Big Data?
2) Hadoop Ecosystem
3) Hadoop Core Components: HDFS & YARN
4) Hadoop Core Configuration Files
5) Multi Node Hadoop Installation
6) Tuning Hadoop using Configuration Files
7) Commissioning and Decommissioning the DataNode
8) Hadoop Web UI Components
9) Hadoop Job Responsibilities
Big Data with Hadoop and HDInsight. This is an intro to the technology. If you are new to BigData or just heard of it. This presentation help you to know just little bit more about the technology.
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
With the surge in Big Data, organizations have began to implement Big Data related technologies as a part of their system. This has lead to a huge need to update existing skillsets with Hadoop. Java professionals are one such people who have to update themselves with Hadoop skills.
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
What is Hadoop | Introduction to Hadoop | Hadoop Tutorial | Hadoop Training |...Edureka!
This Edureka "What is Hadoop" Tutorial (check our hadoop blog series here: https://goo.gl/lQKjL8) will help you understand all the basics of Hadoop. Learn about the differences in traditional and hadoop way of storing and processing data in detail. Below are the topics covered in this tutorial:
1) Traditional Way of Processing - SEARS
2) Big Data Growth Drivers
3) Problem Associated with Big Data
4) Hadoop: Solution to Big Data Problem
5) What is Hadoop?
6) HDFS
7) MapReduce
8) Hadoop Ecosystem
9) Demo: Hadoop Case Study - Orbitz
Subscribe to our channel to get updates.
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Apache Hadoop Tutorial | Hadoop Tutorial For Beginners | Big Data Hadoop | Ha...Edureka!
This Edureka "Hadoop tutorial For Beginners" ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand the problem with traditional system while processing Big Data and how Hadoop solves it. This tutorial will provide you a comprehensive idea about HDFS and YARN along with their architecture that has been explained in a very simple manner using examples and practical demonstration. At the end, you will get to know how to analyze Olympic data set using Hadoop and gain useful insights.
Below are the topics covered in this tutorial:
1. Big Data Growth Drivers
2. What is Big Data?
3. Hadoop Introduction
4. Hadoop Master/Slave Architecture
5. Hadoop Core Components
6. HDFS Data Blocks
7. HDFS Read/Write Mechanism
8. What is MapReduce
9. MapReduce Program
10. MapReduce Job Workflow
11. Hadoop Ecosystem
12. Hadoop Use Case: Analyzing Olympic Dataset
Hadoop Administration Training | Hadoop Administration Tutorial | Hadoop Admi...Edureka!
This Edureka Hadoop Administration Training tutorial will help you understand the functions of all the Hadoop daemons and what are the configuration parameters involved with them. It will also take you through a step by step Multi-Node Hadoop Installation and will discuss all the configuration files in detail. Below are the topics covered in this tutorial:
1) What is Big Data?
2) Hadoop Ecosystem
3) Hadoop Core Components: HDFS & YARN
4) Hadoop Core Configuration Files
5) Multi Node Hadoop Installation
6) Tuning Hadoop using Configuration Files
7) Commissioning and Decommissioning the DataNode
8) Hadoop Web UI Components
9) Hadoop Job Responsibilities
Big Data with Hadoop and HDInsight. This is an intro to the technology. If you are new to BigData or just heard of it. This presentation help you to know just little bit more about the technology.
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
With the surge in Big Data, organizations have began to implement Big Data related technologies as a part of their system. This has lead to a huge need to update existing skillsets with Hadoop. Java professionals are one such people who have to update themselves with Hadoop skills.
John Sing's Edge 2013 presentation, detailing when/where/how external storage products and/or system software (i.e. GPFS) can be effectively used in a Hadoop storage environment. Many Hadoop situations absolutely required direct attached storage. However, there are many intelligent situations where shared external storage may make sense in a Hadoop environment. This presentation details how/why/where, and promotes taking an intelligent, Hadoop-aware approach to deciding between internal storage and external shared storage. Having full awareness of Hadoop considerations is essential to selecting either internal or external shared storage in Hadoop environment.
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
Enough taking about Big data and Hadoop and let’s see how Hadoop works in action.
We will locate a real dataset, ingest it to our cluster, connect it to a database, apply some queries and data transformations on it , save our result and show it via BI tool.
Top Hadoop Big Data Interview Questions and Answers for FresherJanBask Training
Top Hadoop Big Data Interview Questions and Answers for Fresher , Hadoop, Hadoop Big Data, Hadoop Training, Hadoop Interview Question, Hadoop Interview Answers, Hadoop Big Data Interview Question
HDFS is a Java-based file system that provides scalable and reliable data storage, and it was designed to span large clusters of commodity servers. HDFS has demonstrated production scalability of up to 200 PB of storage and a single cluster of 4500 servers, supporting close to a billion files and blocks.
Big-Data Hadoop Tutorials - MindScripts Technologies, Pune amrutupre
MindScripts Technologies, is the leading Big-Data Hadoop Training institutes in Pune, providing a complete Big-Data Hadoop Course with Cloud-Era certification.
50 must read hadoop interview questions & answers - whizlabsWhizlabs
At present, the Big Data Hadoop jobs are on the rise. So, here we present top 50 Hadoop Interview Questions and Answers to help you crack job interview..!!
5 Scenarios: When To Use & When Not to Use HadoopEdureka!
Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in 2015. Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals.
Overview of Big data, Hadoop and Microsoft BI - version1Thanh Nguyen
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Overview of big data & hadoop version 1 - Tony NguyenThanh Nguyen
Overview of Big data, Hadoop and Microsoft BI - version1
Big Data and Hadoop are emerging topics in data warehousing for many executives, BI practices and technologists today. However, many people still aren't sure how Big Data and existing Data warehouse can be married and turn that promise into value. This presentation provides an overview of Big Data technology and how Big Data can fit to the current BI/data warehousing context.
http://www.quantumit.com.au
http://www.evisional.com
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.
What to learn during the 21 days Lockdown | EdurekaEdureka!
Register Here: https://resources.edureka.co/21-days-learning-plan-webinar/
In light of the complete national lockdown for 21 days, we invite you to join a FREE webinar by renowned Mentor and Advisor, Nitin Gupta as he helps you create a 21-day learning gameplan to maximize returns for your career.
The webinar will help freshers and experienced professionals to capitalize on these 21 days and figure out the best technologies to learn while confined to home.
You will also get all your questions and doubts resolved in real-time.
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Top 10 Dying Programming Languages in 2020 | EdurekaEdureka!
YouTube Link: https://youtu.be/LSM7hD6GM4M
Get Edureka Certified in Trending Programming Languages: https://www.edureka.co
In this highly competitive IT industry, everyone wants to learn programming languages that will keep them ahead of the game. But knowing what to learn so you gain the most out of your knowledge is a whole other ball game. So, we at Edureka have prepared a list of Top 10 Dying Programming Languages 2020 that will help you to make the right choice for your career. Meanwhile, if you ever wondered about which languages are slated for continuing uptake and possible greatness, we have a list for that, too.
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Top 5 Trending Business Intelligence Tools | EdurekaEdureka!
YouTube Link: https://youtu.be/eEwq_mPd1iI
Edureka BI Certification Training Courses: https://www.edureka.co/bi-and-visualization-certification-courses
Receiving insights and finding trends is absolutely critical for businesses to scale and adapt as the years go on. This is exactly what business intelligence does and the best thing about these software solutions is that their potential uses are practically unlimited.
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Tableau Tutorial for Data Science | EdurekaEdureka!
YouTube Link:https://youtu.be/ZHNdSKMluI0
Edureka Tableau Certification Training: https://www.edureka.co/tableau-certification-training
This Edureka's PPT on "Tableau for Data Science" will help you to utilize Tableau as a tool for Data Science, not only for engagement but also comprehension efficiency. Through this PPT, you will learn to gain the maximum amount of insight with the least amount of effort.
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YouTube Link:https://youtu.be/CVv8zhYEjUE
Edureka Python Certification Training: https://www.edureka.co/data-science-python-certification-course
This Edureka PPT on 'Python Programming' will help you learn Python programming basics with the help of interesting hands-on implementations.
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YouTube Link:https://youtu.be/LvgqSMlIXFs
Get Edureka Certified in Trending Project Management Certifications: https://www.edureka.co/project-management-and-methodologies-certification-courses
Whether you want to scale up your career or are trying to switch your career path, Project Management Certifications seems to be a perfect choice in either case. So, we at Edureka have prepared a list of Top 5 Project Management Certifications that you must check out in 2020 for a major career boost.
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Top Maven Interview Questions in 2020 | EdurekaEdureka!
YouTube Link: https://youtu.be/5iTcAR4fScM
**DevOps Certification Courses - https://www.edureka.co/devops-certification-training***
This video on 'Maven Interview Questions' discusses the most frequently asked Maven Interview Questions. This PPT will help give you a detailed explanation of the topics which will help you in acing the interviews.
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YouTube Link: https://youtu.be/xHUiYEIcY_I
** Linux Administration Certification Training - https://www.edureka.co/linux-admin **
Linux Mint is the first operating system that people from Windows or Mac are drawn towards when they have to switch to Linux in their work environment. Linux Mint has been around since the year 2006 and has grown and matured into a very user-friendly OS. Do watch the PPT till the very end to see all the demonstrations.
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How to Deploy Java Web App in AWS| EdurekaEdureka!
YouTube Link:https://youtu.be/Ozc5Yu_IcaI
** Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training**
This Edureka PPT shows how to deploy a java web application in AWS using AWS Elastic Beanstalk. It also describes the advantages of using AWS for this purpose.
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*** Edureka Digital Marketing Course: https://www.edureka.co/post-graduate/digital-marketing-certification***
This Edureka PPT on "Top 10 Reasons to Learn Digital Marketing" will help you understand why you should take up Digital Marketing
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** RPA Training: https://www.edureka.co/robotic-process-automation-training**
This PPT on RPA in 2020 will provide a glimpse of the accomplishments and benefits provided by RPA. Also, it will list out the new changes and technologies that will collaborate with RPA in 2020.
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**DevOps Certification Courses - https://www.edureka.co/devops-certification-training **
This PPT shows how to configure Jenkins to receive email notifications. It also includes a demo that shows how to do it in 6 simple steps in the Windows machine.
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EA Algorithm in Machine Learning | EdurekaEdureka!
YouTube Link: https://youtu.be/DIADjJXrgps
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training **
This Edureka PPT on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model.
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PGP in AI and Machine Learning (9 Months Online Program): https://www.edureka.co/post-graduate/machine-learning-and-ai
This Edureka PPT on "Cognitive AI" explains cognitive computing and how it helps in making better human decisions at work. Also, it explains the differences between cognitive computing and artificial intelligence.
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Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training
This Edureka PPT on AWS Cloud Practitioner will provide a complete guide to your AWS Cloud Practitioner Certification exam. It will explain the exam details, objectives, why you should get certified and also how AWS certification will help your career.
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Blue Prism Top Interview Questions | EdurekaEdureka!
YouTube Link: https://youtu.be/ykbRdUNIbyQ
** RPA Training: https://www.edureka.co/robotic-process-automation-certification-courses**
This PPT on Blue Prism Interview Questions will cover the Top 50 Blue Prism related questions asked in your interviews.
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AWS Architect Certification Training: https://www.edureka.co/aws-certification-training
This PPT will help you in understanding how AWS deals smartly with Big Data. It also shows how AWS can solve Big Data challenges with ease.
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A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaEdureka!
YouTube Link: https://youtu.be/amlkE0g-YFU
** Artificial Intelligence and Deep Learning: https://www.edureka.co/ai-deep-learni... **
This Edureka PPT on 'A Star Algorithm' teaches you all about the A star Algorithm, the uses, advantages and disadvantages and much more. It also shows you how the algorithm can be implemented practically and has a comparison between the Dijkstra and itself.
Check out our playlist for more videos: http://bit.ly/2taym8X
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Kubernetes Installation on Ubuntu | EdurekaEdureka!
YouTube Link: https://youtu.be/UWg3ORRRF60
Kubernetes Certification: https://www.edureka.co/kubernetes-certification
This Edureka PPT will help you set up a Kubernetes cluster having 1 master and 1 node. The detailed step by step instructions is demonstrated in this PPT.
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DevOps Training: https://www.edureka.co/devops-certification-training
This Edureka DevOps Tutorial for Beginners talks about What is DevOps and how it works. You will learn about several DevOps tools (Git, Jenkins, Docker, Puppet, Ansible, Nagios) involved at different DevOps stages such as version control, continuous integration, continuous delivery, continuous deployment, continuous monitoring.
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Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
2. How It Works…
LIVE On-Line classes
Class recordings in Learning Management System (LMS)
Module wise Quizzes, Coding Assignments
24x7 on-demand technical support
Project work on large Datasets
Online certification exam
Lifetime access to the LMS
Complimentary Java Classes
Slide 2
www.edureka.in/hadoop
3. Course Topics
Module 1
Module 2
Slide 3
Advance MapReduce
MRUnit testing framework
Module 5
Analytics using Pig
Understanding Pig Latin
Module 6
Advance HBASE
Zookeeper Service
Module 9
Advance Hive
NoSQL Databases and HBASE
Module 8
Analytics using Hive
Understanding HIVE QL
Module 7
Hadoop MapReduce framework
Programming in Map Reduce
Module 4
Hadoop Cluster Configuration
Data loading Techniques
Hadoop Project Environment
Module 3
Understanding Big Data
Hadoop Architecture
Hadoop 2.0 – New Features
Programming in MRv2
Module 10
Apache Oozie
Real world Datasets and Analysis
Project Discussion
www.edureka.in/hadoop
4. Topics for Today
What is Big Data?
Limitations of the existing solutions
Solving the problem with Hadoop
Introduction to Hadoop
Hadoop Eco-System
Hadoop Core Components
HDFS Architecture
MapReduce Job execution
Anatomy of a File Write and Read
Hadoop 2.0 (YARN or MRv2) Architecture
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5. What Is Big Data?
Lots of Data (Terabytes or Petabytes)
Big data is the term for a collection of data sets so large and complex that it becomes difficult to
process using on-hand database management tools or traditional data processing applications. The
challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization.
Systems / Enterprises generate huge amount of data from Terabytes to and even Petabytes of
information.
NYSE generates about one terabyte of new trade data
per day to Perform stock trading analytics to determine
trends for optimal trades.
Slide 5
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8. Annie’s Introduction
Hello There!!
My name is Annie.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
Slide 8
www.edureka.in/hadoop
9. Annie’s Question
Map the following to corresponding data type:
-
XML Files
-
Word Docs, PDF files, Text files
-
E-Mail body
-
Slide 9
Hello There!!
My name is Annie.
Data from Enterprise systems (ERP, CRM etc.)
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
www.edureka.in/hadoop
10. Annie’s Answer
XML Files -> Semi-structured data
Word Docs, PDF files, Text files -> Unstructured Data
E-Mail body -> Unstructured Data
Data from Enterprise systems (ERP, CRM etc.) -> Structured Data
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11. Further Reading
More on Big Data
http://www.edureka.in/blog/the-hype-behind-big-data/
Hadoop Cluster Configuration Files
http://www.edureka.in/blog/hadoop-cluster-configuration-files/
Opportunities in Hadoop
http://www.edureka.in/blog/jobs-in-hadoop/
Big Data
http://en.wikipedia.org/wiki/Big_Data
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www.edureka.in/hadoop
12. Common Big Data Customer Scenarios
Web and e-tailing
Recommendation Engines
Ad Targeting
Search Quality
Abuse and Click Fraud Detection
Telecommunications
Customer Churn Prevention
Network Performance
Optimization
Calling Data Record (CDR)
Analysis
Analyzing Network to Predict
Failure
http://wiki.apache.org/hadoop/PoweredBy
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13. Common Big Data Customer Scenarios (Contd.)
Government
Fraud Detection And Cyber Security
Welfare schemes
Justice
Healthcare & Life Sciences
Health information exchange
Gene sequencing
Serialization
Healthcare service quality
improvements
Drug Safety
http://wiki.apache.org/hadoop/PoweredBy
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14. Common Big Data Customer Scenarios (Contd.)
Banks and Financial services
Modeling True Risk
Threat Analysis
Fraud Detection
Trade Surveillance
Credit Scoring And Analysis
Retail
Point of sales Transaction
Analysis
Customer Churn Analysis
Sentiment Analysis
http://wiki.apache.org/hadoop/PoweredBy
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15. Hidden Treasure
Case Study: Sears Holding Corporation
Insight into data can provide Business
Advantage.
Some key early indicators can mean Fortunes
to Business.
X
More Precise Analysis with more data.
*Sears was using traditional systems such as Oracle
Exadata, Teradata and SAS etc. to store and process the
customer activity and sales data.
Slide 15
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16. Limitations of Existing Data Analytics Architecture
BI Reports + Interactive Apps
A meagre
10% of the
~2PB Data is
available for
BI
RDBMS (Aggregated Data)
1. Can‟t explore original
high fidelity raw data
ETL Compute Grid
2. Moving data to compute
doesn‟t scale
Storage only Grid (original Raw Data)
Storage
Processing
90% of
the ~2PB
Archived
3. Premature data
death
Mostly Append
Collection
Instrumentation
http://www.informationweek.com/it-leadership/why-sears-is-going-all-in-on-hadoop/d/d-id/1107038?
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www.edureka.in/hadoop
17. Solution: A Combined Storage Computer Layer
BI Reports + Interactive Apps
1. Data Exploration &
Advanced analytics
RDBMS (Aggregated Data)
No Data
Archiving
Entire ~2PB
Data is
available for
processing
Both
Storage
And
Processing
2. Scalable throughput for ETL &
aggregation
Hadoop : Storage + Compute Grid
3. Keep data alive
forever
Mostly Append
Collection
Instrumentation
*Sears moved to a 300-Node Hadoop cluster to keep 100% of its data available for processing rather
than a meagre 10% as was the case with existing Non-Hadoop solutions.
Slide 17
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19. Hadoop – It’s about Scale And Structure
RDBMS
EDW
MPP
RDBMS
HADOOP
NoSQL
Structured
Data Types
Multi and Unstructured
Limited, No Data Processing
Processing
Processing coupled with Data
Standards & Structured
Governance
Loosely Structured
Required On write
Schema
Required On Read
Reads are Fast
Speed
Writes are Fast
Software License
Cost
Support Only
Known Entity
Resources
Growing, Complexities, Wide
Interactive OLAP Analytics
Complex ACID Transactions
Operational Data Store
Best Fit Use
Data Discovery
Processing Unstructured Data
Massive Storage/Processing
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20. Why DFS?
Read 1 TB Data
1 Machine
4 I/O Channels
Each Channel – 100 MB/s
Slide 20
10 Machines
4 I/O Channels
Each Channel – 100 MB/s
www.edureka.in/hadoop
23. What Is Hadoop?
Apache Hadoop is a framework that allows for the distributed processing of large data sets
across clusters of commodity computers using a simple programming model.
It is an Open-source Data Management with scale-out storage & distributed processing.
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25. Annie’s Question
Hadoop is a framework that allows for the distributed processing of:
-
Slide 25
Small Data Sets
Large Data Sets
Hello There!!
My name is Annie.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
www.edureka.in/hadoop
26. Annie’s Answer
Large Data Sets. It is also capable to process small data-sets
however to experience the true power of Hadoop one needs to have
data in Tb‟s because this where RDBMS takes hours and fails
whereas Hadoop does the same in couple of minutes.
Slide 26
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27. Hadoop Eco-System
Apache Oozie (Workflow)
Hive
Pig Latin
DW System
Data Analysis
Mahout
Machine Learning
MapReduce Framework
HBase
HDFS (Hadoop Distributed File System)
Flume
Sqoop
Import Or Export
Slide 27
Unstructured or
Semi-Structured data
Structured Data
www.edureka.in/hadoop
28. Machine Learning with Mahout
Write intelligent applications using Apache Mahout
LinkedIn Recommendations
Hadoop and
MapReduce magic in
action
https://cwiki.apache.org/confluence/display/MAHOUT/Powered+By+Mahout
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29. Hadoop Core Components
Hadoop is a system for large scale data processing.
It has two main components:
HDFS – Hadoop Distributed File System (Storage)
Distributed across “nodes”
Natively redundant
NameNode tracks locations.
MapReduce (Processing)
Splits a task across processors
“near” the data & assembles results
Self-Healing, High Bandwidth
Clustered storage
JobTracker manages the TaskTrackers
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30. Hadoop Core Components (Contd.)
MapReduce
Engine
Task
Tracker
Task
Tracker
Task
Tracker
Task
Tracker
HDFS
Cluster
Slide 30
Job Tracker
Admin Node
Name node
Data Node
Data Node
Data Node
Data Node
www.edureka.in/hadoop
32. Main Components Of HDFS
NameNode:
master of the system
maintains and manages the blocks which are present on the
DataNodes
DataNodes:
slaves which are deployed on each machine and provide the
actual storage
responsible for serving read and write requests for the clients
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33. NameNode Metadata
Meta-data in Memory
The entire metadata is in main memory
No demand paging of FS meta-data
Types of Metadata
List of files
List of Blocks for each file
List of DataNode for each block
File attributes, e.g. access time, replication factor
A Transaction Log
Records file creations, file deletions. etc
Slide 33
Name Node
(Stores metadata only)
METADATA:
/user/doug/hinfo -> 1 3 5
/user/doug/pdetail -> 4 2
Name Node:
Keeps track of overall file directory
structure and the placement of Data
Block
www.edureka.in/hadoop
34. Secondary Name Node
metadata
NameNode
Secondary NameNode:
Single Point
Failure
Not a hot standby for the NameNode
You give me
metadata every
hour, I will make
it secure
Connects to NameNode every hour*
Housekeeping, backup of NemeNode metadata
Saved metadata can build a failed NameNode
Secondary
NameNode
metadata
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35. Annie’s Question
NameNode?
a)
is the “Single Point of Failure” in a cluster
b) runs on „Enterprise-class‟ hardware
c)
d) All of the above
Slide 35
Hello There!!
My name is Annie.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
stores meta-data
www.edureka.in/hadoop
36. Annie’s Answer
All of the above. NameNode Stores meta-data and runs on reliable
high quality hardware because it‟s a Single Point of failure in a
hadoop Cluster.
Slide 36
www.edureka.in/hadoop
37. Annie’s Question
When the NameNode fails, Secondary NameNode takes over
instantly and prevents Cluster Failure:
a)
TRUE
b) FALSE
Slide 37
Hello There!!
My name is Annie.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
www.edureka.in/hadoop
38. Annie’s Answer
False. Secondary NameNode is used for creating NameNode
Checkpoints. NameNode can Hello There!!
be manually recovered using „edits‟
My name is Annie.
and „FSImage‟ stored in Secondary NameNode.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
Slide 38
www.edureka.in/hadoop
39. JobTracker
1. Copy Input Files
DFS
Job.xml.
Job.jar.
3. Get Input Files‟ Info
Client
2. Submit Job
4. Create Splits
Input Files
5. Upload Job
Information
User
6. Submit Job
Slide 39
Job Tracker
www.edureka.in/hadoop
40. JobTracker (Contd.)
DFS
Input Spilts
Client
8. Read Job Files
Job.xml.
Job.jar.
Maps
6. Submit Job
Job Tracker
Reduces
9. Create
maps and
reduces
7. Initialize Job
Slide 40
As many maps
as splits
Job Queue
www.edureka.in/hadoop
42. Annie’s Question
Hadoop framework picks which of the following daemon
for scheduling a task ?
a) namenode
b) datanode
c) task tracker
d) job tracker
Slide 42
www.edureka.in/hadoop
43. Annie’s Answer
JobTracker takes care of all theHello There!!
job scheduling and
My name is Annie.
I love quizzes and
puzzles and I am here to
make you guys think and
answer my questions.
assign tasks to TaskTrackers.
Slide 43
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44. Anatomy of A File Write
HDFS
Client
2. Create
1. Create
3. Write
Distributed
File System
NameNode
NameNode
7. Complete
6. Close
4. Write Packet
5. ack Packet
4
Pipeline of
Data nodes
DataNode
DataNode
Slide 44
4
DataNode
5
DataNode
DataNode
5
DataNode
www.edureka.in/hadoop
45. Anatomy of A File Read
HDFS
Client
2. Get Block locations
1. Create
3. Write
NameNode
Distributed
File System
NameNode
4. Read
5. Read
DataNode
DataNode
DataNode
Slide 45
DataNode
DataNode
DataNode
www.edureka.in/hadoop
47. Annie’s Question
In HDFS, blocks of a file are written in parallel, however
the replication of the blocks are done sequentially:
a)
TRUE
b) FALSE
Slide 47
www.edureka.in/hadoop
48. Annie’s Answer
True. A files is divided into Blocks, these blocks are
written in parallel but the block replication happen in
sequence.
Slide 48
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49. Annie’s Question
A file of 400MB is being copied to HDFS. The system
has finished copying 250MB. What happens if a client
tries to access that file:
a)
b)
c)
d)
Slide 49
can read up to block that's successfully written.
can read up to last bit successfully written.
Will throw an throw an exception.
Cannot see that file until its finished copying.
www.edureka.in/hadoop
50. Annie’s Answer
Client can read up to the successfully written data block,
Answer is (a)
Slide 50
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51. Hadoop 2.x (YARN or MRv2)
HDFS
All name space edits
logged to shared NFS
storage; single writer
(fencing)
Secondary
Name Node
Active
NameNode
Data Node
Client
YARN
Shared
edit logs
Read edit logs and applies
to its own namespace
Resource
Manager
Standby
NameNode
Data Node
Data Manager
Node Node
Container
Node Manager
Container
Slide 51
App
Master
Node Manager
Container
App
Master
Data Node
Node Manager
Container
App
Master
Data Node
App
Master
www.edureka.in/hadoop
52. Further Reading
Apache Hadoop and HDFS
http://www.edureka.in/blog/introduction-to-apache-hadoop-hdfs/
Apache Hadoop HDFS Architecture
http://www.edureka.in/blog/apache-hadoop-hdfs-architecture/
Hadoop 2.0 and YARN
http://www.edureka.in/blog/apache-hadoop-2-0-and-yarn/
Slide 52
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53. Module-2 Pre-work
Setup the Hadoop development environment using the documents present in the LMS.
Hadoop Installation – Setup Cloudera CDH3 Demo VM
Hadoop Installation – Setup Cloudera CDH4 QuickStart VM
Execute Linux Basic Commands
Execute HDFS Hands On commands
Attempt the Module-1 Assignments present in the LMS.
Slide 53
www.edureka.in/hadoop
Web and e-tailing- eBay is using Hadoop technology and the Hbase database, which supports real-time analysis of Hadoop data, to build a new search engine for its auction site. eBay has more than 97 million active buyers and sellers and over 200 million items for sale in 50,000 categories. The site handles close to 2 billion page views, 250 million search queries and tens of billions of database calls daily. The company has 9 petabytes of data stored on Hadoop and Teradata clusters, and the amount is growing quickly.TelecommunicationsChina Mobile; Data Mining platform for Telecom Industry, 5-8 TB/day CDR , Network Signaling DataCurrent Solutions such as Oracle DB, SAS (Data Mining), Unix Servers and SAN aren’t sufficient to store and process such a vast amount of dataNeed faster data processing to Precision marketing, Network Optimization, Service Optimization and Log Processing
Government-AADHAR by Govt. Of India; 5 MB Data per resident, maps to about 10-15 PB of raw data. The Hadoop stack: HDFS (Hadoop distributed file system) is used to provide high data read/write throughput in the order of many terabytes per day. Distributed architecture enables scale out as needed. Hive is used for building the UIDAI data warehouse, HBase for indexed lookup of records across millions of rows, Zookeeper as a distributed coordination service for server instances, and Pig as an ETL (extract, transform and load) solution for loading data into Hive.Healthcare and Life Sciences- Life sciences research firm NextBio uses Hadoop and HBase to help big pharmaceutical companies conduct genomic research. The company embraced Hadoop in 2009 to make the sheer scale of genomic data-analysis more affordable. The company's core 100-node Hadoop cluster, which has processed as much as 100 terabytes of data, is used to compare data from drug studies to publically available genomics data. Given that there are tens of thousands of such studies and 3.2 billion base pairs behind each of the hundreds of genomes that NextBio studies, it's clearly a big-data challenge.
Banks and Financial services:3 of the top 5 Banks run Cloudera HadoopJPMorgan Chase uses Hadoop technology for a growing number of purposes, including fraud detection, IT risk management and self service. With over 150 petabytes of data stored online, 30,000 databases and 3.5 billion log-ins to user accounts, data is the lifeblood of JPMorgan Chase.Retail:Sears is an American multinational mid-range department store chain headquartered in Hoffman Estates, Illinois). It Moved to Hadoop from Hadoop from Teradata and SAS to avoid archiving and deleting its meaningful sales and other customer activity data. 300-Node Hadoop cluster helps Sears to keep its 100% data (~2PB) available to BI rather than a meager 10% as was the case with Non-Hadoop solutions. Walmart; migrated data from its existing Oracle, Neteeza, Oracle and Greenplum gear to its 250-Node Hadoop Cluster.
Why Oracle, HP, IBM and other Enterprise Technology giants are in Red on growth. Sears:Sears wanted to personalize marketing campaigns, coupons, and offers down to the individual customer, but the existing legacy systems were incapable of supporting that.Sears' process for analyzing marketing campaigns for loyalty club members used to take six weeks on mainframe, Teradata, and SAS servers. The new process running on Hadoop can be completed weekly. For certain online and mobile commerce scenarios, Sears can now perform daily analyses. What's more, targeting is more granular, in some cases down to the individual customer. Moving up the stack, Sears is consolidating its databases to MySQL, InfoBright, and Teradata--EMC Greenplum, Microsoft SQL Server, and Oracle (including four Exadata boxes) are on their way out.Sears routinely replaces legacy Unix systems with Linux rather than upgrade them, and it has retired most of its Sun and HP-UX servers. Microsoft server and development technologies are also on the way out.
- 2 PB of data--mostly structured and unstructured data such as customer transaction, point of sale, and supply chain.- Because of Archiving Need 90% of the ~2PB of Data is not available for BI
300-Node Hadoop cluster helps Sears to keep its 100% data (~2PB) available to BI rather than a meager 10% as was the case with Non-Hadoop solutions. Sears now keeps all of its data down to individual transactions (rather than aggregates) and years of history (rather than imposing quarterly windows on certain data, as it did previously). That's raw data, which Sears can refactor and combine as needed quickly and efficiently within Hadoop.To give a sense of how early Sears was to Hadoop development, Wal-Mart divulged early this year that it was scaling out an experimental 10-node Hadoop cluster for e-commerce analysis. Sears passed that size in 2010.Has its own Hadoop solutions subsidiary MetaScale, to provide hadoop services to other retail companies on the line of AWS.
Accessible: Hadoop runs on large clusters of commodity machines or cloud computing services such as Amazon EC2Robust: Since Hadoop can run on commodity cluster, its designed with the assumption of frequent hardware failure, it can gracefully handle such failure and computation don’t stop because of few failed devices / systemsScalable:Hadoop scales linearly to handle large data by adding more slave nodes to the clusterSimple : Its easy to write efficient parallel programming with Hadoop
We will cover other Hadoop Components in detail in future sessions of this course.
Data transferred from DataNode to MapTask process. DBlk is the file data block; CBlk is the file checksum block. File data are transferred to the client through Java niotransferTo (aka UNIX sendfilesyscall). Checksum data are first fetched to DataNode JVM buffer, and then pushed to the client (details are not shown). Both file data and checksum data are bundled in an HDFS packet (typically 64KB) in the format of: {packet header | checksum bytes | data bytes}.2. Data received from the socket are buffered in a BufferedInputStream, presumably for the purpose of reducing the number of syscalls to the kernel. This actually involves two buffer-copies: first, data are copied from kernel buffers into a temporary direct buffer in JDK code; second, data are copied from the temporary direct buffer to the byte[] buffer owned by the BufferedInputStream. The size of the byte[] in BufferedInputStream is controlled by configuration property "io.file.buffer.size", and is default to 4K. In our production environment, this parameter is customized to 128K.3. Through the BufferedInputStream, the checksum bytes are saved into an internal ByteBuffer (whose size is roughly (PacketSize / 512 * 4) or 512B), and file bytes (compressed data) are deposited into the byte[] buffer supplied by the decompression layer. Since the checksum calculation requires a full 512 byte chunk while a user's request may not be aligned with a chunk boundary, a 512B byte[] buffer is used to align the input before copying partial chunks into user-supplied byte[] buffer. Also note that data are copied to the buffer in 512-byte pieces (as required by FSInputChecker API). Finally, all checksum bytes are copied to a 4-byte array for FSInputChecker to perform checksum verification. Overall, this step involves an extra buffer-copy.4. The decompression layer uses a byte[] buffer to receive data from the DFSClient layer. The DecompressorStream copies the data from the byte[] buffer to a 64K direct buffer, calls the native library code to decompress the data and stores the uncompressed bytes in another 64K direct buffer. This step involves two buffer-copies.5.LineReader maintains an internal buffer to absorb data from the downstream. From the buffer, line separators are discovered and line bytes are copied to form Text objects. This step requires two buffer-copies.The client creates the file by calling create() on Distributed FileSystem (step 1). Distributed FileSystem makes an RPC call to the namenode to create a new file in the filesystem’s namespace, with no blocks associated with it (step 2). The namenode performs various checks to make sure the file doesn’t already exist, and that the client has the right permissions to create the file.
The client opens the file it wishes to read by calling open() on the FileSystemobject,which for HDFS is an instance of DFS(step 1).DistributedFileSystem calls the namenode, using RPC, to determine the locations of the blocks for the first few blocks in the File (step 2). For each block, the namenode returns the addresses of the datanodes that have a copy of that block