An Introduction to Apache Hadoop MapReduce

•Transferir como ODP, PDF•

3 gostaram•1,170 visualizações

An Introduction to Apache Hadoop MapReduce, what is it and how does it work ? What is the map reduce cycle and how are jobs managed. Why should it be used and who are big users and providers ?

Tecnologia Negócios

Apache Hadoop MapReduce
● What is it ?
● Why use it ?
● How does it work
● Some examples
● Big users

MapReduce – What is it ?
● Processing engine of Hadoop
● Developers create Map and Reduce jobs
● Used for big data batch processing
● Parallel processing of huge data volumes
● Fault tolerant
● Scalable

MapReduce – What use it ?
● Your data in Terabyte / Petabyte range
● You have huge I/O
● Hadoop framework takes care of
– Job and task management
– Failures
– Storage
– Replication
● You just write Map and Reduce jobs

MapReduce – How does it work ?
Take word counting as an example, something that Google does
all of the time.

MapReduce – How does it work ?
● Input data split into shards
● Split data mapped to key,value pairs i.e. Bear,1
● Mapped data shuffled/sorted by key i.e. Bear
● Sorted data reduced i.e. Bear, 2
● Final data stored on HDFS
● There might be extra map layer before shuffle
● JobTracker controls all tasks in job
● TaskTracker controls map and reduce

MapReduce - Some examples
A visual example with colours to show you the cycle
Split -> Map -> Shuffle -> Reduce

MapReduce - Some examples
A visual example of MapReduce with job and task trackers added to
individual map and reduce jobs.

Hadoop MapReduce – Big users
● Users
– Facebook
– Yahoo
– Amazon
– Ebay
● Providers
– Amazon
– Cloudera
– HortonWorks
– MapR

Contact Us
● Feel free to contact us at
– www.semtech-solutions.co.nz
– info@semtech-solutions.co.nz
● We offer IT project consultancy
● We are happy to hear about your problems
● You can just pay for those hours that you need
● To solve your problems

Mais conteúdo relacionado

Mais de Mike Frampton

This presentation gives an overview of the Prometheus project. It explains Prometheus in terms of it's visualisation, time series processing capabilities and architecture. It also examines it's query language PromQL. Links for further information and connecting http://www.amazon.com/Michael-Frampton/e/B00NIQDOOM/ https://nz.linkedin.com/pub/mike-frampton/20/630/385 https://open-source-systems.blogspot.com/

Prometheus

Mike Frampton

Apache Tephra

Mike Frampton

This presentation gives an overview of the Apache Kudu project. It explains the Kudu project in terms of it's architecture, schema, partitioning and replication. It also provides an example deployment scale. Links for further information and connecting http://www.amazon.com/Michael-Frampton/e/B00NIQDOOM/ https://nz.linkedin.com/pub/mike-frampton/20/630/385 https://open-source-systems.blogspot.com/

Apache Kudu

Apache Bahir

Apache Arrow

JanusGraph DB

Apache Ignite

Apache Samza

Apache Flink

Apache Edgent

Apache CouchDB

An introduction to Apache Mesos

Mike Frampton

An introduction to Pentaho

Mike Frampton

An introduction to Apache Thrift

Mike Frampton

An introduction to Apache Cassandra

Mike Frampton

An example Hadoop Install

Mike Frampton

An Introduction to Apache Hadoop Yarn

Mike Frampton

An Introduction to Cloud Computing

Mike Frampton

An Introduction to Hadoop Hue Gui

Mike Frampton

An introduction to Apache Hadoop Hive

Mike Frampton

Mais de Mike Frampton (20)

Prometheus

Apache Tephra

Apache Kudu

Apache Bahir

Apache Arrow

JanusGraph DB

Apache Ignite

Apache Samza

Apache Flink

Apache Edgent

Apache CouchDB

An introduction to Apache Mesos

An introduction to Pentaho

An introduction to Apache Thrift

An introduction to Apache Cassandra

An example Hadoop Install

An Introduction to Apache Hadoop Yarn

An Introduction to Cloud Computing

An Introduction to Hadoop Hue Gui

An introduction to Apache Hadoop Hive

Último

GenAI Risks & Security Meetup 01052024.pdf

lior mazor

Following the popularity of "Cloud Revolution: Exploring the New Wave of Serverless Spatial Data," we're thrilled to announce this much-anticipated encore webinar. In this sequel, we'll dive deeper into the Cloud-Native realm by uncovering practical applications and FME support for these new formats, including COGs, COPC, FlatGeoBuf, GeoParquet, STAC, and ZARR. Building on the foundation laid by industry leaders Michelle Roby of Radiant Earth and Chris Holmes of Planet in the first webinar, this second part offers an in-depth look at the real-world application and behind-the-scenes dynamics of these cutting-edge formats. We will spotlight specific use-cases and workflows, showcasing their efficiency and relevance in practical scenarios. Discover the vast possibilities each format holds, highlighted through detailed discussions and demonstrations. Our expert speakers will dissect the key aspects and provide critical takeaways for effective use, ensuring attendees leave with a thorough understanding of how to apply these formats in their own projects. Elevate your understanding of how FME supports these cutting-edge technologies, enhancing your ability to manage, share, and analyze spatial data. Whether you're building on knowledge from our initial session or are new to the serverless spatial data landscape, this webinar is your gateway to mastering cloud-native formats in your workflows.

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Safe Software

MINDCTI Revenue Release Quarter One 2024

MIND CTI

Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe 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 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

apidays

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

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

Top 10 Most Downloaded Games on Play Store in 2024

SynarionITSolutions

presentation ICT roal in 21st century education

jfdjdjcjdnsjd

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

debabhi2

Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia

A Year of the Servo Reboot: Where Are We Now?

Igalia

In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

Drew Madelung

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

Boston Institute of Analytics

Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

DianaGray10

Tata AIG General Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

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

Joaquim Jorge

The Good, the Bad and the Governed - Why is governance a dirty word? David O'Neill, Chief Operating Officer - APIContext 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 Good, the Bad and the Governed by David O'Neill, ...

apidays

Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 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 Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...

apidays

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Principled Technologies

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

Artificial Intelligence Chap.5 : Uncertainty

Khushali Kathiriya

An Introduction to Apache Hadoop MapReduce

1. Apache Hadoop MapReduce ● What is it ? ● Why use it ? ● How does it work ● Some examples ● Big users

2. MapReduce – What is it ? ● Processing engine of Hadoop ● Developers create Map and Reduce jobs ● Used for big data batch processing ● Parallel processing of huge data volumes ● Fault tolerant ● Scalable

3. MapReduce – What use it ? ● Your data in Terabyte / Petabyte range ● You have huge I/O ● Hadoop framework takes care of – Job and task management – Failures – Storage – Replication ● You just write Map and Reduce jobs

4. MapReduce – How does it work ? Take word counting as an example, something that Google does all of the time.

5. MapReduce – How does it work ? ● Input data split into shards ● Split data mapped to key,value pairs i.e. Bear,1 ● Mapped data shuffled/sorted by key i.e. Bear ● Sorted data reduced i.e. Bear, 2 ● Final data stored on HDFS ● There might be extra map layer before shuffle ● JobTracker controls all tasks in job ● TaskTracker controls map and reduce

6. MapReduce - Some examples A visual example with colours to show you the cycle Split -> Map -> Shuffle -> Reduce

7. MapReduce - Some examples A visual example of MapReduce with job and task trackers added to individual map and reduce jobs.

8. Hadoop MapReduce – Big users ● Users – Facebook – Yahoo – Amazon – Ebay ● Providers – Amazon – Cloudera – HortonWorks – MapR

9. Contact Us ● Feel free to contact us at – www.semtech-solutions.co.nz – info@semtech-solutions.co.nz ● We offer IT project consultancy ● We are happy to hear about your problems ● You can just pay for those hours that you need ● To solve your problems

10. Contact Us ● Feel free to contact us at – www.semtech-solutions.co.nz – info@semtech-solutions.co.nz ● We offer IT project consultancy ● We are happy to hear about your problems ● You can just pay for those hours that you need ● To solve your problems

An Introduction to Apache Hadoop MapReduce

Recomendados

Recomendados

Mais conteúdo relacionado

Mais de Mike Frampton

Mais de Mike Frampton (20)

Último

Último (20)

An Introduction to Apache Hadoop MapReduce