This document discusses Hortonworks' approach to addressing challenges around managing large volumes of diverse data. It presents Hortonworks' Hadoop Data Platform (HDP) as a solution for consolidating siloed data into a central data lake on a single cluster. This allows different data types and workloads like batch, interactive, and real-time processing to leverage shared services for security, governance and operations while preserving existing tools. The HDP also enables new use cases for analytics like real-time personalization and segmentation using diverse data sources.
What is Hadoop brief intro for Georgian Partners CTO Conference. This outlines the origins of Open Source Apache Hadoop and how Hortonworks fits into this picture. There is also a brief introduction to YARN, the new resource negotiation layer.
2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitectureAdam Muise
An introduction to Hadoop's core components as well as the core Hadoop use case: the Data Lake. This deck was delivered at Big Data Congress 2014 in Saint John, NB on Feb 24.
What is Hadoop brief intro for Georgian Partners CTO Conference. This outlines the origins of Open Source Apache Hadoop and how Hortonworks fits into this picture. There is also a brief introduction to YARN, the new resource negotiation layer.
2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitectureAdam Muise
An introduction to Hadoop's core components as well as the core Hadoop use case: the Data Lake. This deck was delivered at Big Data Congress 2014 in Saint John, NB on Feb 24.
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
Creating a Data Science Team from an Architect's perspective. This is about team building on how to support a data science team with the right staff, including data engineers and devops.
Database is the new black. Ever the backbone of information architectures, database technology continually evolves to meet growing and changing business needs. New types of data and applications make the database more important than ever, and understanding which technology best serves your use case is paramount to building durable systems. These days, the choices are many, so users should be careful when deciding which direction to go. Register for this Exploratory Webcast to hear veteran database Analyst Dr. Robin Bloor explain why the database market has exploded in recent years. He'll outline the current database landscape, and provide insights about which kinds of technologies are suitable for the growing variety of business needs today. He'll also focus on key auxiliary technologies that enable modern databases to do perform efficiently.
Presentation regarding big data. The presentation also contains basics regarding Hadoop and Hadoop components along with their architecture. Contents of the PPT are
1. Understanding Big Data
2. Understanding Hadoop & It’s Components
3. Components of Hadoop Ecosystem
4. Data Storage Component of Hadoop
5. Data Processing Component of Hadoop
6. Data Access Component of Hadoop
7. Data Management Component of Hadoop
8.Hadoop Security Management Tool: Knox ,Ranger
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
Big Data Analytics Tutorial | Big Data Analytics for Beginners | Hadoop Tutor...Edureka!
This Edureka Big Data Analytics Tutorial will help you to understand the basics of Big Data domain. Learn how to analyze Big Data in this tutorial. Below are the topics covered in this tutorial:
1) Big Data Introduction
2) What is Big Data Analytics?
3) Why Big Data Analytics?
4) Stages in Big Data Analytics
5) Big Data Analytics Domains
6) Big Data Analytics Use Cases
Subscribe to our channel to get updates.
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
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
Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala Desing Pathshala
Learn Hadoop and Bigdata Analytics, Join Design Pathshala training programs on Big data and analytics.
This slide covers the basics of Hadoop and Big Data.
For training queries you can contact us:
Email: admin@designpathshala.com
Call us at: +91 98 188 23045
Visit us at: http://designpathshala.com
Join us at: http://www.designpathshala.com/contact-us
Course details: http://www.designpathshala.com/course/view/65536
Big data Analytics Course details: http://www.designpathshala.com/course/view/1441792
Business Analytics Course details: http://www.designpathshala.com/course/view/196608
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.
this presentation describes the company from where I did my summer training and what is bigdata why we use big data, big data challenges, the issue in big data, the solution of big data issues, hadoop, docker , Ansible etc.
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
Creating a Data Science Team from an Architect's perspective. This is about team building on how to support a data science team with the right staff, including data engineers and devops.
Database is the new black. Ever the backbone of information architectures, database technology continually evolves to meet growing and changing business needs. New types of data and applications make the database more important than ever, and understanding which technology best serves your use case is paramount to building durable systems. These days, the choices are many, so users should be careful when deciding which direction to go. Register for this Exploratory Webcast to hear veteran database Analyst Dr. Robin Bloor explain why the database market has exploded in recent years. He'll outline the current database landscape, and provide insights about which kinds of technologies are suitable for the growing variety of business needs today. He'll also focus on key auxiliary technologies that enable modern databases to do perform efficiently.
Presentation regarding big data. The presentation also contains basics regarding Hadoop and Hadoop components along with their architecture. Contents of the PPT are
1. Understanding Big Data
2. Understanding Hadoop & It’s Components
3. Components of Hadoop Ecosystem
4. Data Storage Component of Hadoop
5. Data Processing Component of Hadoop
6. Data Access Component of Hadoop
7. Data Management Component of Hadoop
8.Hadoop Security Management Tool: Knox ,Ranger
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
Big Data Analytics Tutorial | Big Data Analytics for Beginners | Hadoop Tutor...Edureka!
This Edureka Big Data Analytics Tutorial will help you to understand the basics of Big Data domain. Learn how to analyze Big Data in this tutorial. Below are the topics covered in this tutorial:
1) Big Data Introduction
2) What is Big Data Analytics?
3) Why Big Data Analytics?
4) Stages in Big Data Analytics
5) Big Data Analytics Domains
6) Big Data Analytics Use Cases
Subscribe to our channel to get updates.
Check our complete Hadoop playlist here: https://goo.gl/4OyoTW
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
Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala Desing Pathshala
Learn Hadoop and Bigdata Analytics, Join Design Pathshala training programs on Big data and analytics.
This slide covers the basics of Hadoop and Big Data.
For training queries you can contact us:
Email: admin@designpathshala.com
Call us at: +91 98 188 23045
Visit us at: http://designpathshala.com
Join us at: http://www.designpathshala.com/contact-us
Course details: http://www.designpathshala.com/course/view/65536
Big data Analytics Course details: http://www.designpathshala.com/course/view/1441792
Business Analytics Course details: http://www.designpathshala.com/course/view/196608
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.
this presentation describes the company from where I did my summer training and what is bigdata why we use big data, big data challenges, the issue in big data, the solution of big data issues, hadoop, docker , Ansible etc.
Today, when data is mushrooming and coming in heterogeneous forms, there is a growing need for a flexible, adaptable, efficient and cost effective integration platform which will take minimum on-boarding time and interact and entertain n number of platforms. Talend fits just perfect in this space with a proven track record, so learning talend makes lot of sense for anybody associated with data world.
If you understand how to manage, transform, store your organisation data (retail, banking, airlines, research, insurance, cards etc.) and effectively represent it which is the backbone behind any successful MIS system/reporting/dash board then you are a key person that organisation most sought after.
Hadoop was born out of the need to process Big Data.Today data is being generated liked never before and it is becoming difficult to store and process this enormous volume and large variety of data, In order to cope this Big Data technology comes in.Today Hadoop software stack is go-to framework for large scale,data intensive storage and compute solution for Big Data Analytics Applications.The beauty of Hadoop is that it is designed to process large volume of data in clustered commodity computers work in parallel.Distributing the data that is too large across the nodes in clusters solves the problem of having too large data sets to be processed onto the single machine.
Hadoop Training | Hadoop Training For Beginners | Hadoop Architecture | Hadoo...Simplilearn
This presentation about Hadoop training will help you understand the need for Hadoop, what is Hadoop and concepts including Hadoop ecosystem, Hadoop features, how HDFS works, what is MapReduce and how YARN works. Finally, we will implement a banking case study using Hadoop. To solve the issue of rapidly increasing data, we need big data technologies such as Hadoop, Spark, Storm, Cassandra and many more. Hadoop can store and process vast volumes of data. You will understand the architecture of HDFS, MapReduce workflow and the architecture of YARN. In the demo, you will learn in detail on how to export data from RDBMS (MySQL) into HDFS using Sqoop commands. Now, let us get started and gain expertise with Hadoop training video.
Below topics are explained in this Hadoop training presentation:
1. Need for Hadoop
2. What is Hadoop
3. Hadoop ecosystem
4. Hadoop features
5. What is HDFS
6. What is MapReduce
7. What is YARN
8. Bank case study
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Hadoop and the Data Warehouse: Point/Counter PointInside Analysis
Robin Bloor and Teradata
Live Webcast on April 22, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=2e69345c0a6a4e5a8de6fc72652e3bc6
Can you replace the data warehouse with Hadoop? Is Hadoop an ideal ETL subsystem? And what is the real magic of Hadoop? Everyone is looking to capitalize on the insights that lie in the vast pools of big data. Generating the value of that data relies heavily on several factors, especially choosing the right solution for the right context. With so many options out there, how do organizations best integrate these new big data solutions with the existing data warehouse environment?
Register for this episode of The Briefing Room to hear veteran analyst Dr. Robin Bloor as he explains where Hadoop fits into the information ecosystem. He’ll be briefed by Dan Graham of Teradata, who will offer perspective on how Hadoop can play a critical role in the analytic architecture. Bloor and Graham will interactively discuss big data in the big picture of the data center and will also seek to dispel several common misconceptions about Hadoop.
Visit InsideAnlaysis.com for more information.
Enterprise Hadoop is Here to Stay: Plan Your Evolution StrategyInside Analysis
The Briefing Room with Neil Raden and Teradata
Live Webcast on August 19, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=1acd0b7ace309f765dc3196001d26a5e
Modern enterprises have been able to solve information management woes with the data warehouse, now a staple across the IT landscape that has evolved to a high level of sophistication and maturity with thousands of global implementations. Today’s modern enterprise has a similar challenge; big data and the fast evolution of the Hadoop ecosystem create plenty of new opportunities but also a significant number of operational pains as new solutions emerge.
Register for this episode of The Briefing Room to hear veteran Analyst Neil Raden as he explores the details and nature of Hadoop’s evolution. He’ll be briefed by Cesar Rojas of Teradata, who will share how Teradata solves some of the Hadoop operational challenges. He will also explain how the integration between Hadoop and the data warehouse can help organizations develop a more responsive and robust data management environment.
Visit InsideAnlaysis.com for more information.
Foundation for Success: How Big Data Fits in an Information ArchitectureInside Analysis
BDIA Roundtable
Live Webcast on April 9, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=c84869fcca958d278b210cfca2a023a0
Big Data can offer big value and big challenges, and there are lots of solutions and promises out there. But in order to harness the most insight from Big Data, organizations need to solve pain points with more than triage. Since data challenges continue to permeate the information landscape, businesses would do well to incorporate solutions that fit into the infrastructure and provide a sustainable method for managing and analyzing Big Data.
Register for this Roundtable Webcast to hear veteran Analysts Robin Bloor, Mike Ferguson and Richard Winter as they offer their perspectives on the evolving Big Data industry. They’ll comment on the proposed Big Data Information Architecture, and take questions from the audience. This is the second event of The Bloor Group's Interactive Research Report for 2014 which will focus on illuminating optimal Big Data Information Architectures. The series will include a dozen interviews with today's Big Data visionaries, plus three interactive Webcasts and a detailed findings report.
Visit InsideAnlaysis.com for more information.
Introductory Big Data presentation given during one of our Sizing Servers Lab user group meetings. The presentation is targeted towards an audience of about 20 SME employees. It also contains a short description of the work packages for our BIg Data project proposal that was submitted in March.
2015 nov 27_thug_paytm_rt_ingest_brief_finalAdam Muise
Paytm Labs provides a quick overview of their Hadoop data ingest platform. We cover our journey from a batch focused ingest system with SQOOP to a streaming ingest supported by Kafka, Confluent.io, Hadoop, Cassandra, and Spark Streaming. This presentation also provides an overview of our complete data platform including our feature creation template
Moving to a data-centric architecture: Toronto Data Unconference 2015Adam Muise
Why use a datalake? Why use lambda? A conversation starter for Toronto Data Unconference 2015. We will discuss technologies such as Hadoop, Kafka, Spark Streaming, and Cassandra.
An overview of securing Hadoop. Content primarily by Balaji Ganesan, one of the leaders of the Apache Argus project. Presented on Sept 4, 2014 at the Toronto Hadoop User Group by Adam Muise.
Sept 17 2013 - THUG - HBase a Technical IntroductionAdam Muise
HBase Technical Introduction. This deck includes a description of memory design, write path, read path, some operational tidbits, SQL on HBase (Phoenix and Hive), as well as HOYA (HBase on YARN).
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
4. The
leaders
of
Hadoop’s
development
We
do
Hadoop
Community
driven,
Enterprise
Focused
Drive
InnovaDon
in
the
plaEorm
–
We
lead
the
roadmap
100%
Open
Source
–
DemocraDzed
Access
to
Data
5. We
do
Hadoop
successfully.
> Develop
Open
Source
Hadoop
> Distribute
Hadoop
with
HDP
> Support
> Professional
Services
> Training
6. Hortonworks Approach
1 Innovate the Core
Architect and build
innovation at the core of
Hadoop
• YARN: Data Operating
System
• HDFS as the storage layer
• Key processing engines
Extend Hadoop as an
2 Enterprise Data Platform 3 Enable the Ecosystem
Extend Hadoop with enterprise
capabilities for governance,
security & operations
Apply enterprise software rigor
to the open source development
process
Enable the leaders in the data
center to easily adopt & extend
their platforms
• Establish Hadoop as standard
component of a modern data
architecture
• Joint engineering
Script
Pig
YARN
SQL
Hive/Tez,
HCatalog
NoSQL
HBase
Accumulo
Stream
Storm
:
Data
Opera>ng
System
Batch
Map
Reduce
HDFS
(Hadoop
Distributed
File
System)
HDP
2.2
Governance
& Integration
Security
Operations
Data Access
YARN
Data Management
Memory
Spark
7. …all done completely 4 in Open Source
Innova>ng
within
the
community
for
the
enterprise
• Open
• Complete
adopDon
and
minimizes
lock
in
• Enables
Script
Pig
YARN
Source:
fastest
path
to
innovaDon
for
a
plaEorm
technology
open
source
plaEorm
speeds
enterprise
and
ecosystem
the
market
to
funcDon
much
bigger
much
faster
Memory
Spark
SQL
Hive/Tez,
HCatalog
NoSQL
HBase
Accumulo
Stream
Storm
:
Data
Opera>ng
System
Batch
Map
Reduce
HDFS
(Hadoop
Distributed
File
System)
HDP
2.2
Governance
& Integration
Security
Operations
Data Access
YARN
Data Management
Driving
our
innova>on
through
Apache
SoQware
Founda>on
Projects
Apache
Project
CommiTers
PMC
Members
Hadoop
27
20
Pig
5
5
Hive
16
4
Tez
15
15
HBase
6
4
Phoenix
4
4
Accumulo
2
2
Storm
3
2
Slider
10
10
Flume
1
0
Sqoop
1
1
Ambari
32
27
Oozie
3
2
Zookeeper
2
1
Knox
11
5
Argus
10
n/a
Falcon
5
3
TOTAL
153
105
15. Data
The
soluDon?
EDW
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
Data
Yet
Another
EDW
DDataat
Data
Data
a
Data
Data
Data
Data
Data
AnalyDcal
DB
DDataat
a
Data
Data
Data
Data
Data
Data
OLTP
DDataat
a
Data
Data
Data
Data
Data
Data
Another
EDW
DDataat
Data
Data
a
Data
Data
Data
Data
16. Data
Ummm…you
Data
dropped
something
Data
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
Data
Data
Data
DDDaDatataaatt
a
Data
Data
Data
Data
Data
Data
DDDaaDattataaa
Data
t
a
Data
Data
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
Data
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
DaDtaat
a
Data
Data
Data
Data
EDW
DDataat
a
Data
Data
Data
Data
Data
Data
Yet
Another
EDW
DDataat
Data
Data
a
Data
Data
Data
Data
AnalyDcal
DB
DDataat
a
Data
Data
Data
Data
Data
Data
OLTP
DDataat
a
Data
Data
Data
Data
Data
Data
Another
EDW
DDataat
Data
Data
a
Data
Data
Data
Data
18. Data
Silos.
Your
data
silos
are
lonely
places.
EDW
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Accounts
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Customers
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Web
ProperDes
DDataat
Data
Data
a
Data
Data
Data
Data
Data
19. …
Data
likes
to
be
together.
EDW
DDataat
a
Data
Data
Data
Data
Data
Accounts
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Customers
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Web
ProperDes
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
Data
20. Facebook
DDataat
a
Data
Data
Data
Data
Data
likes
to
socialize
too.
EDW
DDataat
a
Data
Data
Data
Data
Data
Accounts
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Customers
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Data
Web
ProperDes
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
Data
Machine
Data
DDataat
Data
Data
a
Data
Data
Data
Data
Twiber
DDataat
a
Data
Data
Data
Data
Data
Data
Data
Data
CDR
DDataat
a
Data
Data
Data
Data
Data
Data
Weather
Data
DDataat
Data
Data
a
Data
Data
Data
Data
21. New
types
of
data
don’t
quite
fit
into
your
prisDne
view
of
the
world.
My
Lible
Data
Empire
DaDtaat
Data
a
Data
Data
Data
Data
Data
Data
Logs
Data
Data
Data
Data
Data
Data
Data
Machine
Data
Data
Data
Data
Data
Data
Data
Data
?
?
?
?
22. To
resolve
this,
some
people
take
hints
from
Lord
Of
The
Rings...
24. …but
that
has
its
problems
too.
EDW
DDataat
a
Data
Data
Data
Data
Data
Data
Data
SchemaD
ata
DaDtaat
a
ETL
ETL
ETL
ETL
EDW
DDataat
a
Data
Data
Data
Data
Data
Data
Data
SchemaD
ata
DaDtaat
a
ETL
ETL
ETL
ETL
25. What
if
the
data
was
processed
and
stored
centrally?
What
if
you
didn’t
need
to
force
it
into
a
single
schema?
We
call
it
a
Modern
Data
Architecture*
*AKA
Data
Lake
26. A Modern Data Architecture
• Consolidate siloed data sets structured
and unstructured
• Central data set on a single cluster
• Multiple workloads across batch
interactive and real time
• Central services for security, governance
and operation
• Preserve existing investment in current
tools and platforms
• Single view of the customer, product,
supply chain
APPLICATIONS
DATA
SYSTEM
Business
Analy>cs
Custom
Applica>ons
Packaged
Applica>ons
RDBMS
EDW
MPP
Batch Interactive Real-Time
YARN:
Data
Opera>ng
System
1
°
°
°
°
°
°
°
°
°
°
°
°
°
°
°
°
°
°
N
CRM
ERP
Other
1
°
°
°
°
°
°
HDFS
(Hadoop
Distributed
File
System)
SOURCES
EXISTING
Systems
Clickstream
Web
&Social
Geoloca>on
Sensor
&
Machine
Server
Logs
Unstructured
29. Your
segmentaDon
today.
Male
Female
Age:
25-‐30
Town/City
Middle
Income
Band
Product
Category
Preferences
30. Looking
to
start
a
business
Your
segmentaDon
with
beber
data.
Male
Female
Age:
27
but
feels
old
GPS
coordinates
$65-‐68k
per
year
Product
recommendaDons
per
Dme
of
day
and
per
weather
Tea
Party
Hippie
Walking
into
Starbucks
right
now…
A
depressed
Toronto
Maple
Leaf’s
Fan
Products
lem
in
basket
indicate
drunk
amazon
shopper
Purchase
history
indicates
a
risk
taker
Thinking
about
a
new
house
Unhappy
with
his
cell
phone
plan
Pregnant
Spent
25
minutes
looking
at
tea
cozies
31. Pick
up
all
of
that
data
that
was
prohibiDvely
expensive
to
store
and
use.
32. To
approach
these
use
cases
you
need
an
affordable
plaEorm
that
stores,
processes,
and
analyzes
the
data.
33. Don’t
wait
for
your
data.
Batch
is
omen
too
late
to
influence
the
person
who
is
in
your
store
or
on
your
website
right
now.
34. Streaming Processing, Search, and Storage
APACHE
KAFKA
YARN
HDFS
Hortonworks
Data
Plaaorm
2.2
Search
Slider
Solr
Online
Data
Processing
HBase
Real
Time
Stream
Processing
Storm
SQL
Hive
Streaming
Ingest
Stream
data
into
Hadoop
and
process
it
in
near
real-‐;me
Real-‐Dme
data
feeds
36. What’s New in HDP 2.2
New and Improved YARN
Ready Engines
• Enterprise SQL at Hadoop Scale with
Stinger.next
• Enterprise Ready Spark on YARN
• Deep YARN integration for real-time
engines: HBase, Accumulo, Storm
• Enabling ISVs with a general SDK and API
for direct YARN integration
• Only solution to provide real-time to micro
batch for analyzing the internet of things
• Other engines/tools: Solr, Cascading
Continued Innovation of
Central Enterprise Services
• Centralized security administration
and policy enforcement
• Ease of use and operations agility
features to speed cluster
deployment
• 100% uptime target with cluster
rolling upgrades
Expanded Deployment Options
• Enhanced business continuity with
replication/archival across on-premises
and cloud storage tiers (Azure Blob, S3)
• Simultaneous ship of Windows and Linux
installs
• Expand Azure support beyond HDInsight
Azure to include HDP for Windows or
Linux in Azure VMs
HDP
2.2
Delivering
Apache
Hadoop
for
the
Enterprise
37. Complete List of New Features in HDP 2.2
Apache Hadoop YARN
• Slide existing services onto YARN through ‘Slider’
• GA release of HBase, Accumulo, and Storm on
YARN
• Support long running services: handling of logs,
containers not killed when AM dies, secure token
renewal, YARN Labels for tagging nodes for specific
workloads
• Support for CPU Scheduling and CPU Resource
Isolation through CGroups
Apache Hadoop HDFS
• Heterogeneous storage: Support for archival
• Rolling Upgrade (This is an item that applies to the
entire HDP Stack. YARN, Hive, HBase, everything.
We now support comprehensive Rolling Upgrade
across the HDP Stack).
• Multi-NIC Support
• Heterogeneous storage: Support memory as a
storage tier (TP)
• HDFS Transparent Data Encryption (TP)
Apache Hive, Apache Pig, and Apache Tez
• Hive Cost Based Optimizer: Function Pushdown &
Join re-ordering support for other join types: star &
bushy.
• Hive SQL Enhancements including:
• ACID Support: Insert, Update, Delete
• Temporary Tables
• Metadata-only queries return instantly
• Pig on Tez
• Including DataFu for use with Pig
• Vectorized shuffle
• Tez Debug Tooling & UI
Hue
• Support for HiveServer 2
• Support for Resource Manager HA
Apache Spark
• Refreshed Tech Preview to Spark 1.1.0 (available
now)
• ORC File support & Hive 0.13 integration
• Planned for GA of Spark 1.2.0
• Operations integration via YARN ATS and Ambari
• Security: Authentication
• Apache Solr
• Added Banana, a rich and flexible UI for visualizing
time series data indexed in Solr
• Cascading
• Cascading 3.0 on Tez distributed with HDP
— coming soon
Apache Falcon
• Authentication Integration
• Lineage – now GA. (it’s been a tech preview
feature…)
• Improve UI for pipeline management & editing: list,
detail, and create new (from existing elements)
• Replicate to Cloud – Azure & S3
Apache Sqoop, Apache Flume & Apache Oozie
• Sqoop import support for Hive types via HCatalog
• Secure Windows cluster support: Sqoop, Flume,
Oozie
• Flume streaming support: sink to HCat on secure
cluster
• Oozie HA now supports secure clusters
• Oozie Rolling Upgrade
• Operational improvements for Oozie to better
support Falcon
• Capture workflow job logs in HDFS
• Don’t start new workflows for re-run
• Allow job property updates on running jobs
Apache HBase, Apache Phoenix, & Apache
Accumulo
• HBase & Accumulo on YARN via Slider
• HBase HA
• Replicas update in real-time
• Fully supports region split/merge
• Scan API now supports standby RegionServers
• HBase Block cache compression
• HBase optimizations for low latency
• Phoenix Robust Secondary Indexes
• Performance enhancements for bulk import into
Phoenix
• Hive over HBase Snapshots
• Hive Connector to Accumulo
• HBase & Accumulo wire-level encryption
• Accumulo multi-datacenter replication
Apache Storm
• Storm-on-YARN via Slider
• Ingest & notification for JMS (IBM MQ not
supported)
• Kafka bolt for Storm – supports sophisticated
chaining of topologies through Kafka
• Kerberos support
• Hive update support – Streaming Ingest
• Connector improvements for HBase and HDFS
• Deliver Kafka as a companion component
• Kafka install, start/stop via Ambari
• Security Authorization Integration with Ranger
Apache Slider
• Allow on-demand create and run different versions
of heterogeneous applications
• Allow users to configure different application
instances differently
• Manage operational lifecycle of application
instances
• Expand / shrink application instances
• Provide application registry for publish and
discovery
Apache Knox & Apache Ranger (Argus) & HDP
Security
• Apache Ranger – Support authorization and auditing
for Storm and Knox
• Introducing REST APIs for managing policies in
Apache Ranger
• Apache Ranger – Support native grant/revoke
permissions in Hive and HBase
• Apache Ranger – Support Oracle DB and storing of
audit logs in HDFS
• Apache Ranger to run on Windows environment
• Apache Knox to protect YARN RM
• Apache Knox support for HDFS HA
• Apache Ambari install, start/stop of Knox
Apache Ambari
• Support for HDP 2.2 Stack, including support for
Kafka, Knox and Slider
• Enhancements to Ambari Web configuration
management including: versioning, history and
revert, setting final properties and downloading client
configurations
• Launch and monitor HDFS rebalance
• Perform Capacity Scheduler queue refresh
• Configure High Availability for ResourceManager
• Ambari Administration framework for managing user
and group access to Ambari
• Ambari Views development framework for
customizing the Ambari Web user experience
• Ambari Stacks for extending Ambari to bring custom
Services under Ambari management
• Ambari Blueprints for automating cluster
deployments
• Performance improvements and enterprise usability
guardrails
38. Hortonworks Data Platform:
A comprehensive data management platform
Hortonworks
Data
Plaaorm
2.2
Java
Scala
Cascading
Tez
Stream
Storm
YARN: Data Operating System
(Cluster
Resource
Management)
Script
Pig
SQL
Hive
TezTez
1 ° ° ° ° ° ° °
° ° ° ° ° ° ° °
° °
° °
Others
ISV
Engines
° ° ° ° °
° ° ° ° °
HDFS
(Hadoop Distributed File System)
Search
Solr
NoSQL
HBase
Accumulo
Sli der
Slider
GOVERNANCE
BATCH, INTERACTIVE & REAL-TIME DATA ACCESS SECURITY
OPERATIONS
In-Memory
Spark
Provision,
Manage &
Monitor
Ambari
Zookeeper
Scheduling
Oozie
Data Workflow,
Lifecycle &
Governance
Falcon
Sqoop
Flume
Kafka
NFS
WebHDFS
Authentication
Authorization
Accounting
Data Protection
Storage: HDFS
Resources: YARN
Access: Hive, …
Pipeline: Falcon
Cluster: Knox
Cluster: Ranger
Linux Windows Deployment Choice On-Premises Cloud
YARN
is the architectural
center of HDP
Enables batch, interactive
and real-time workloads
Provides comprehensive
enterprise capabilities
The widest range of
deployment options
Delivered
Completely
in
the
OPEN