Optimizing Bursty Hadoop on AWS - Big Data Cloud - June 3rd Meetup

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Optimizing Bursty Hadoop on AWS - Big Data Cloud - June 3rd Meetup Presentation by Paul Baclace

Technologie Business

Big Data Cloud Meetup Big Data & Cloud Computing - Help, Educate & Demystify. June 3 rd 2011

Optimizing Bursty Hadoop ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Options ,[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Goals ,[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Logical Information Flow DataSource--> CloudStorage--> MapReduce--> CloudStorage--> Reports Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Variable Cost Factors ,[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Price Insensitive, Permanent EC2 Solution: ,[object Object],[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Elastic-MapReduce Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

EBS HDFS Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

EBS HDFS Solution (2) ,[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Performance ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Results 4 jobs per month, 100GB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.0000 S3_and_EMR 1200 14.000 0.000 6.35375 39.4150 EBS_HDFS_EC2_Tasks 0 20.000 0.425 5.67880 42.7152 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Results 40 jobs per month, 100GB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.000 S3_and_EMR 1200 14.000 0.000 6.35375 268.150 EBS_HDFS_EC2_Tasks 0 20.000 0.425 5.67880 247.152 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Results 4 jobs per month, 1TB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.000 S3_and_EMR 1200 140.000 0.000 6.35375 165.415 EBS_HDFS_EC2_Tasks 0 200.000 0.425 7.06300 228.252 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

Results 40 jobs per month, 1TB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.00 S3_and_EMR 1200 140.000 0.000 6.35375 394.15 EBS_HDFS_EC2_Tasks 0 200.000 0.425 7.06300 482.52 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

EC2 Hadoop Set Up Tips ,[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

EC2 Hadoop Set Up Tips (2) ,[object Object],[object Object],[object Object],[object Object],Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

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A tutorial given at NAACL HLT 2013. Richard Socher and Christopher Manning http://nlp.stanford.edu/courses/NAACL2013/ Machine learning is everywhere in today's NLP, but by and large machine learning amounts to numerical optimization of weights for human designed representations and features. The goal of deep learning is to explore how computers can take advantage of data to develop features and representations appropriate for complex interpretation tasks. This tutorial aims to cover the basic motivation, ideas, models and learning algorithms in deep learning for natural language processing. Recently, these methods have been shown to perform very well on various NLP tasks such as language modeling, POS tagging, named entity recognition, sentiment analysis and paraphrase detection, among others. The most attractive quality of these techniques is that they can perform well without any external hand-designed resources or time-intensive feature engineering. Despite these advantages, many researchers in NLP are not familiar with these methods. Our focus is on insight and understanding, using graphical illustrations and simple, intuitive derivations. The goal of the tutorial is to make the inner workings of these techniques transparent, intuitive and their results interpretable, rather than black boxes labeled "magic here". The first part of the tutorial presents the basics of neural networks, neural word vectors, several simple models based on local windows and the math and algorithms of training via backpropagation. In this section applications include language modeling and POS tagging. In the second section we present recursive neural networks which can learn structured tree outputs as well as vector representations for phrases and sentences. We cover both equations as well as applications. We show how training can be achieved by a modified version of the backpropagation algorithm introduced before. These modifications allow the algorithm to work on tree structures. Applications include sentiment analysis and paraphrase detection. We also draw connections to recent work in semantic compositionality in vector spaces. The principle goal, again, is to make these methods appear intuitive and interpretable rather than mathematically confusing. By this point in the tutorial, the audience members should have a clear understanding of how to build a deep learning system for word-, sentence- and document-level tasks. The last part of the tutorial gives a general overview of the different applications of deep learning in NLP, including bag of words models. We will provide a discussion of NLP-oriented issues in modeling, interpretation, representational power, and optimization.

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Recommendation Engines - An Architectural Guide

Recommendation Engines - An Architectural Guide

Recommendation Engines - An Architectural Guide

As the big data market matures, discussions about Hadoop are expanding from pure technology to how businesses can use it to innovate and leap frog competitors. In this session, Karmasphere will outline how technologists can effectively work with their CMOs - the likely drivers of widespread Hadoop adoption, to unlock its business value. The discussion will include: how changes in marketing are driving the adoption of Hadoop big data analytics, the evolving role of the data and business analysts and a review of real-world big data analytics use cases. Karmasphere will demonstrate how the Full Fidelity Analytics of Hadoop can empower high-tech, e-commerce, etail and reatil banking to quickly and easily analyze complex data types across silos and apply sophisticated analytics to personalize customer engagement and optimize revenue.

Why Hadoop is the New Infrastructure for the CMO?

Why Hadoop is the New Infrastructure for the CMO?

Why Hadoop is the New Infrastructure for the CMO?

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

At Facebook, we use various types of databases and storage system to satisfy the needs of different applications. The solutions built around these data store systems have a common set of requirements: they have to be highly scalable, maintenance costs should be low and they have to perform efficiently. We use a sharded mySQL+memcache solution to support real-time access of tens of petabytes of data and we use TAO to provide consistency of this web-scale database across geographical distances. We use Haystack datastore for storing the 3 billion new photos we host every week. We use Apache Hadoop to mine intelligence from 100 petabytes of clicklogs and combine it with the power of Apache HBase to store all Facebook Messages. This talk describes the reasons why each of these databases are appropriate for their workloads and the design decisions and tradeoffs that were made while implementing these solutions. We touch upon the consistency, availability and partitioning tolerance of each of these solutions. We touch upon the reasons why some of these systems need ACID semantics and other systems do not. We briefly touch upon some futures of how we plan to do big-data deployments across geographical locations and our requirements for a new breed of pure-memory and pure-SSD based transactional database.

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

Michael Ralph Stonebraker is a computer scientist specializing in database research. He is currently an adjunct professor at MIT, where he has been involved in the development of the Aurora, C-Store, H-Store, Morpheus, and SciDB systems.Through a series of academic prototypes and commercial startups, Stonebraker's research and products are central to many relational database systems on the market today. He is also the founder of a number of database companies, including Ingres, Illustra, Cohera, StreamBase Systems, Vertica, VoltDB, and Paradigm4. He was previously the Chief Technical Officer (CTO) of Informix & a Professor of Computer Science at University of California, Berkeley. He is also an editor for the book "Readings in Database Systems"

What Does Big Data Mean and Who Will Win

What Does Big Data Mean and Who Will Win

What Does Big Data Mean and Who Will Win

Big Data Analytics is characterized by analysis of data on three vectors: exploding data volume, proliferating data variety (relational, multi-media), and accelerating data velocity. However, other key vectors such as costs and skill set needed for Big Data Analytics are often overlooked. In this session, we will consider all five vectors by exploring various techniques where traditional but progressive technologies such as column store DBMS and Event Stream Processing is combined with open source frameworks such as Hadoop to exploit the full potential of Big Data Analytics. Agenda: - Big Data Analytics in the real world - Commercial and Open Source techniques - Bringing together Commercial and Open Source techniques * Architectures * Programming APIs (e.g. embedded and federated MapReduce) - Conclusions

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

Plus de BigDataCloud (20)

Webinar - Comparative Analysis of Cloud based Machine Learning Platforms

Webinar - Comparative Analysis of Cloud based Machine Learning Platforms

Webinar - Comparative Analysis of Cloud based Machine Learning Platforms

Crime Analysis & Prediction System

Crime Analysis & Prediction System

Crime Analysis & Prediction System

REAL-TIME RECOMMENDATION SYSTEMS

REAL-TIME RECOMMENDATION SYSTEMS

REAL-TIME RECOMMENDATION SYSTEMS

Cloud Computing Services

Cloud Computing Services

Cloud Computing Services

Google Enterprise Cloud Platform - Resources & $2000 credit!

Google Enterprise Cloud Platform - Resources & $2000 credit!

Google Enterprise Cloud Platform - Resources & $2000 credit!

Big Data in the Cloud - Solutions & Apps

Big Data in the Cloud - Solutions & Apps

Big Data in the Cloud - Solutions & Apps

Big Data Analytics in Motorola on the Google Cloud Platform

Big Data Analytics in Motorola on the Google Cloud Platform

Big Data Analytics in Motorola on the Google Cloud Platform

Streak + Google Cloud Platform

Streak + Google Cloud Platform

Streak + Google Cloud Platform

Using Advanced Analyics to bring Business Value

Using Advanced Analyics to bring Business Value

Using Advanced Analyics to bring Business Value

Creating Business Value from Big Data, Analytics & Technology.

Creating Business Value from Big Data, Analytics & Technology.

Creating Business Value from Big Data, Analytics & Technology.

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Deep Learning for NLP (without Magic) - Richard Socher and Christopher Manning

Recommendation Engines - An Architectural Guide

Recommendation Engines - An Architectural Guide

Recommendation Engines - An Architectural Guide

Why Hadoop is the New Infrastructure for the CMO?

Why Hadoop is the New Infrastructure for the CMO?

Why Hadoop is the New Infrastructure for the CMO?

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Hadoop : A Foundation for Change - Milind Bhandarkar Chief Scientist, Pivotal

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 29 2013 - Mike Stonebraker & Scott Jarr of VoltDB

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

Big Data Cloud Meetup - Jan 24 2013 - Zettaset

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

A Survey of Petabyte Scale Databases and Storage Systems Deployed at Facebook

What Does Big Data Mean and Who Will Win

What Does Big Data Mean and Who Will Win

What Does Big Data Mean and Who Will Win

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

Big Data Analytics in a Heterogeneous World - Joydeep Das of Sybase

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentation

Dernier

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

What is a good lead in your organisation? Which leads are priority? What happens to leads? When sales and marketing give different answers to these questions, or perhaps aren't sure of the answers at all, frustrations build and opportunities are left on the table. Join us for an illuminating session with Cian McLoughlin, HubSpot Principal Customer Success Manager, as we look at that crucial piece of the customer journey in which leads are transferred from marketing to sales.

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

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Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

The Digital Insurer

presentation ICT roal in 21st century education

presentation ICT roal in 21st century education

presentation ICT roal in 21st century education

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

Michael W. Hawkins

The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

Artificial Intelligence: Facts and Myths

Artificial Intelligence: Facts and Myths

Artificial Intelligence: Facts and Myths

Developing An App To Navigate The Roads of Brazil

Developing An App To Navigate The Roads of Brazil

Developing An App To Navigate The Roads of Brazil

This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

Antenna Manufacturer Coco

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

Martijn de Jong

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

This presentation explores the impact of HTML injection attacks on web applications, detailing how attackers exploit vulnerabilities to inject malicious code into web pages. Learn about the potential consequences of such attacks and discover effective mitigation strategies to protect your web applications from HTML injection vulnerabilities. for more information visit https://bostoninstituteofanalytics.org/category/cyber-security-ethical-hacking/

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

Boston Institute of Analytics

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

MySQL Webinar, presented on the 25th of April, 2024. Summary: MySQL solutions enable the deployment of diverse Database Architectures tailored to specific needs, including High Availability, Disaster Recovery, and Read Scale-Out. With MySQL Shell's AdminAPI, administrators can seamlessly set up, manage, and monitor these solutions, ensuring efficiency and ease of use in their administration. MySQL Router, on the other hand, provides transparent routing from the application traffic to the backend servers in the architectures, requiring minimal configuration. Completely built in-house and supported by Oracle, these solutions have been adopted by enterprises of all sizes for their business-critical applications. In this presentation, we'll delve into various database architecture solutions to help you choose the right one based on your business requirements. Focusing on technical details and the latest features to maximize the potential of these solutions.

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Maria Levchenko

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Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

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Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

Axa Assurance Maroc - Insurer Innovation Award 2024

presentation ICT roal in 21st century education

presentation ICT roal in 21st century education

presentation ICT roal in 21st century education

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

Artificial Intelligence: Facts and Myths

Artificial Intelligence: Facts and Myths

Artificial Intelligence: Facts and Myths

Developing An App To Navigate The Roads of Brazil

Developing An App To Navigate The Roads of Brazil

Developing An App To Navigate The Roads of Brazil

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

2024: Domino Containers - The Next Step. News from the Domino Container commu...

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

HTML Injection Attacks: Impact and Mitigation Strategies

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Handwritten Text Recognition for manuscripts and early printed texts

Optimizing Bursty Hadoop on AWS - Big Data Cloud - June 3rd Meetup

1. Big Data Cloud Meetup Big Data & Cloud Computing - Help, Educate & Demystify. June 3 rd 2011

2.

3.

4.

5. Logical Information Flow DataSource--> CloudStorage--> MapReduce--> CloudStorage--> Reports Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

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12. Results 4 jobs per month, 100GB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.0000 S3_and_EMR 1200 14.000 0.000 6.35375 39.4150 EBS_HDFS_EC2_Tasks 0 20.000 0.425 5.67880 42.7152 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

13. Results 40 jobs per month, 100GB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.000 S3_and_EMR 1200 14.000 0.000 6.35375 268.150 EBS_HDFS_EC2_Tasks 0 20.000 0.425 5.67880 247.152 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

14. Results 4 jobs per month, 1TB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.000 S3_and_EMR 1200 140.000 0.000 6.35375 165.415 EBS_HDFS_EC2_Tasks 0 200.000 0.425 7.06300 228.252 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

15. Results 40 jobs per month, 1TB StartupSec CostOff StandbyPerHr CostPerMapReduce CostPerMonth Perm_EC2_Cluster 0 5.525 0.000 0.00000 3978.00 S3_and_EMR 1200 140.000 0.000 6.35375 394.15 EBS_HDFS_EC2_Tasks 0 200.000 0.425 7.06300 482.52 Optimizing Bursty Hadoop on AWS June 3 rd 2011 Meetup

16.

17.