A brave new world in mutable big data relational storage (Strata NYC 2017)Todd Lipcon
The ever-increasing interest in running fast analytic scans on constantly updating data is stretching the capabilities of HDFS and NoSQL storage. Users want the fast online updates and serving of real-time data that NoSQL offers, as well as the fast scans, analytics, and processing of HDFS. Additionally, users are demanding that big data storage systems integrate natively with their existing BI and analytic technology investments, which typically use SQL as the standard query language of choice. This demand has led big data back to a familiar friend: relationally structured data storage systems.
Todd Lipcon explores the advantages of relational storage and reviews new developments, including Google Cloud Spanner and Apache Kudu, which provide a scalable relational solution for users who have too much data for a legacy high-performance analytic system. Todd explains how to address use cases that fall between HDFS and NoSQL with technologies like Apache Kudu or Google Cloud Spanner and how the combination of relational data models, SQL query support, and native API-based access enables the next generation of big data applications. Along the way, he also covers suggested architectures, the performance characteristics of Kudu and Spanner, and the deployment flexibility each option provides.
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv larsgeorge
This talk is about showing the complexity in building a data pipeline in Hadoop, starting with the technology aspect, and the correlating to the skillsets of current Hadoop adopters.
Hadoop Operations for Production Systems (Strata NYC)Kathleen Ting
Hadoop is emerging as the standard for big data processing and analytics. However, as usage of the Hadoop clusters grow, so do the demands of managing and monitoring these systems.
In this full-day Strata Hadoop World tutorial, attendees will get an overview of all phases for successfully managing Hadoop clusters, with an emphasis on production systems — from installation, to configuration management, service monitoring, troubleshooting and support integration.
We will review tooling capabilities and highlight the ones that have been most helpful to users, and share some of the lessons learned and best practices from users who depend on Hadoop as a business-critical system.
Hadoop 3.0 has been years in the making, and now it's finally arriving. Andrew Wang and Daniel Templeton offer an overview of new features, including HDFS erasure coding, YARN Timeline Service v2, YARN federation, and much more, and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.
Apache Kudu (Incubating): New Hadoop Storage for Fast Analytics on Fast Data ...Cloudera, Inc.
The Hadoop ecosystem has improved real-time access capabilities recently, narrowing the gap with relational database technologies. However, gaps remain in the storage layer that complicate the transition to Hadoop-based architectures. In this session, the presenter will describe these gaps and discuss the tradeoffs between real-time transactional access and fast analytic performance from the perspective of storage engine internals. The session also will cover Kudu (currently in beta), the new addition to the open source Hadoop ecosystem with outof-the-box integration with Apache Spark and Apache Impala (incubating), that achieves fast scans and fast random access from a single API.
Structor - Automated Building of Virtual Hadoop ClustersOwen O'Malley
Discusses vagrant scripts to setup and deploy a working Hadoop multiple node cluster with or without security. All source code is available on https://github.com/hortonworks/structor .
A brave new world in mutable big data relational storage (Strata NYC 2017)Todd Lipcon
The ever-increasing interest in running fast analytic scans on constantly updating data is stretching the capabilities of HDFS and NoSQL storage. Users want the fast online updates and serving of real-time data that NoSQL offers, as well as the fast scans, analytics, and processing of HDFS. Additionally, users are demanding that big data storage systems integrate natively with their existing BI and analytic technology investments, which typically use SQL as the standard query language of choice. This demand has led big data back to a familiar friend: relationally structured data storage systems.
Todd Lipcon explores the advantages of relational storage and reviews new developments, including Google Cloud Spanner and Apache Kudu, which provide a scalable relational solution for users who have too much data for a legacy high-performance analytic system. Todd explains how to address use cases that fall between HDFS and NoSQL with technologies like Apache Kudu or Google Cloud Spanner and how the combination of relational data models, SQL query support, and native API-based access enables the next generation of big data applications. Along the way, he also covers suggested architectures, the performance characteristics of Kudu and Spanner, and the deployment flexibility each option provides.
Data Pipelines in Hadoop - SAP Meetup in Tel Aviv larsgeorge
This talk is about showing the complexity in building a data pipeline in Hadoop, starting with the technology aspect, and the correlating to the skillsets of current Hadoop adopters.
Hadoop Operations for Production Systems (Strata NYC)Kathleen Ting
Hadoop is emerging as the standard for big data processing and analytics. However, as usage of the Hadoop clusters grow, so do the demands of managing and monitoring these systems.
In this full-day Strata Hadoop World tutorial, attendees will get an overview of all phases for successfully managing Hadoop clusters, with an emphasis on production systems — from installation, to configuration management, service monitoring, troubleshooting and support integration.
We will review tooling capabilities and highlight the ones that have been most helpful to users, and share some of the lessons learned and best practices from users who depend on Hadoop as a business-critical system.
Hadoop 3.0 has been years in the making, and now it's finally arriving. Andrew Wang and Daniel Templeton offer an overview of new features, including HDFS erasure coding, YARN Timeline Service v2, YARN federation, and much more, and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.
Apache Kudu (Incubating): New Hadoop Storage for Fast Analytics on Fast Data ...Cloudera, Inc.
The Hadoop ecosystem has improved real-time access capabilities recently, narrowing the gap with relational database technologies. However, gaps remain in the storage layer that complicate the transition to Hadoop-based architectures. In this session, the presenter will describe these gaps and discuss the tradeoffs between real-time transactional access and fast analytic performance from the perspective of storage engine internals. The session also will cover Kudu (currently in beta), the new addition to the open source Hadoop ecosystem with outof-the-box integration with Apache Spark and Apache Impala (incubating), that achieves fast scans and fast random access from a single API.
Structor - Automated Building of Virtual Hadoop ClustersOwen O'Malley
Discusses vagrant scripts to setup and deploy a working Hadoop multiple node cluster with or without security. All source code is available on https://github.com/hortonworks/structor .
Adopting Hadoop to manage your Big Data is an important step, but not the end-solution to your Big Data challenges. Here are some of the additional considerations you must face:
Choosing the right cloud for the job: The massive computing and storage resources that are needed to support Big Data applications make cloud environments an ideal fit, and more than ever, there is a growing number of choices of cloud infrastructure types and providers. Given the diverse options, and the dynamic environments involved, it becomes ever more important to maintain the flexibility for all your IT needs.
Big Data is a complex beast: It involves many and different moving parts, in large clusters, and is continually growing and evolving. Managing such an environment manually is not a viable option. The question is, how can you achieve automation of all this complexity?
The world beyond Hadoop: Big Data is not just Hadoop – there is a whole rapidly growing ecosystem to contend with, including NoSQL, data processing, analytics tools… As well as your own application services. How can you manage deployment, configuration, scaling and failover of all the different pieces, in a consistent way?
In this session, you’ll learn how to deploy and manage your Hadoop cluster on any Cloud, as well as manage the rest of your big data application stack using a new open source framework called Cloudify.
A presentation on Hadoop for scientific researchers given at Universitat Rovira i Virgili in Catalonia, Spain in October 2010. http://etseq.urv.cat/seminaris/seminars/3/
introduction to data processing using Hadoop and PigRicardo Varela
In this talk we make an introduction to data processing with big data and review the basic concepts in MapReduce programming with Hadoop. We also comment about the use of Pig to simplify the development of data processing applications
YDN Tuesdays are geek meetups organized the first Tuesday of each month by YDN in London
Hadoop, Pig, and Twitter (NoSQL East 2009)Kevin Weil
A talk on the use of Hadoop and Pig inside Twitter, focusing on the flexibility and simplicity of Pig, and the benefits of that for solving real-world big data problems.
Apache Hive provides SQL-like access to your stored data in Apache Hadoop. Apache HBase stores tabular data in Hadoop and supports update operations. The combination of these two capabilities is often desired, however, the current integration show limitations such as performance issues. In this talk, Enis Soztutar will present an overview of Hive and HBase and discuss new updates/improvements from the community on the integration of these two projects. Various techniques used to reduce data exchange and improve efficiency will also be provided.
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Application architectures with Hadoop – Big Data TechCon 2014hadooparchbook
Building applications using Apache Hadoop with a use-case of clickstream analysis. Presented by Mark Grover and Jonathan Seidman at Big Data TechCon, Boston in April 2014
Webinar: Productionizing Hadoop: Lessons Learned - 20101208Cloudera, Inc.
Key insights in installing, configuring, and running Hadoop and Cloudera's Distribution for Hadoop in production. These are lessons learned from Cloudera helping organizations move to a productions state with Hadoop.
Hadoop Essentials -- The What, Why and How to Meet Agency ObjectivesCloudera, Inc.
This session will provide an executive overview of the Apache Hadoop ecosystem, its basic concepts, and its real-world applications. Attendees will learn how organizations worldwide are using the latest tools and strategies to harness their enterprise information to solve business problems and the types of data analysis commonly powered by Hadoop. Learn how various projects make up the Apache Hadoop ecosystem and the role each plays to improve data storage, management, interaction, and analysis. This is a valuable opportunity to gain insights into Hadoop functionality and how it can be applied to address compelling business challenges in your agency.
http://www.learntek.org/product/big-data-and-hadoop/
http://www.learntek.org
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses. We are dedicated to designing, developing and implementing training programs for students, corporate employees and business professional.
"Analyzing Twitter Data with Hadoop - Live Demo", presented at Oracle Open World 2014. The repository for the slides is in https://github.com/cloudera/cdh-twitter-example
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
Hortonworks - What's Possible with a Modern Data Architecture?Hortonworks
This is Mark Ledbetter's presentation from the September 22, 2014 Hortonworks webinar “What’s Possible with a Modern Data Architecture?” Mark is vice president for industry solutions at Hortonworks. He has more than twenty-five years experience in the software industry with a focus on Retail and supply chain.
John Sing's Edge 2013 presentation, detailing when/where/how external storage products and/or system software (i.e. GPFS) can be effectively used in a Hadoop storage environment. Many Hadoop situations absolutely required direct attached storage. However, there are many intelligent situations where shared external storage may make sense in a Hadoop environment. This presentation details how/why/where, and promotes taking an intelligent, Hadoop-aware approach to deciding between internal storage and external shared storage. Having full awareness of Hadoop considerations is essential to selecting either internal or external shared storage in Hadoop environment.
Marcel Kornacker is a tech lead at Cloudera
In this talk from Impala architect Marcel Kornacker, you will explore: How Impala's architecture supports query speed over Hadoop data that not only convincingly exceeds that of Hive, but also that of a proprietary analytic DBMS over its own native columnar format. The current state of, and roadmap for, Impala's analytic SQL functionality. An example configuration and benchmark suite that demonstrate how Impala offers a high level of performance, functionality, and ability to handle a multi-user workload, while retaining Hadoop’s traditional strengths of flexibility and ease of scaling.
This talk was held at the 11th meeting on April 7 2014 by Marcel Kornacker.
Impala (impala.io) raises the bar for SQL query performance on Apache Hadoop. With Impala, you can query Hadoop data – including SELECT, JOIN, and aggregate functions – in real time to do BI-style analysis. As a result, Impala makes a Hadoop-based enterprise data hub function like an enterprise data warehouse for native Big Data.
Data ingest is a deceptively hard problem. In the world of big data processing, it becomes exponentially more difficult. It's not sufficient to simply land data on a system, that data must be ready for processing and analysis. The Kite SDK is a data API designed for solving the issues related to data infest and preparation. In this talk you'll see how Kite can be used for everything from simple tasks to production ready data pipelines in minutes.
REA Group's journey with Data Cataloging and Amundsenmarkgrover
REA Group's journey with Data Cataloging. Presented at Amundsen community meeting on November 5th, 2020.
Presented by Stacy Sterling, Abhinay Kathuria and Alex Kompos at REA Group.
Amundsen: From discovering to security datamarkgrover
Hear about how Lyft and Square are solving data discovery and data security challenges using a shared open source project - Amundsen.
Talk details and abstract:
https://www.datacouncil.ai/talks/amundsen-from-discovering-data-to-securing-data
Amundsen: From discovering to security datamarkgrover
Hear about how Lyft and Square are solving data discovery and data security challenges using a shared open source project - Amundsen.
Talk details and abstract:
https://www.datacouncil.ai/talks/amundsen-from-discovering-data-to-securing-data
Talk on Data Discovery and Metadata by Mark Grover from July 2019.
Goes into detail of the problem, build/buy/adopt analysis and Lyft's solution - Amundsen, along with thoughts on the future.
TensorFlow Extension (TFX) and Apache Beammarkgrover
Talk on TFX and Beam by Robert Crowe, developer advocate at Google, focussed on TensorFlow.
Learn how the TensorFlow Extended (TFX) project is utilizing Apache Beam to simplify pre- and post-processing for ML pipelines. TFX provides a framework for managing all of necessary pieces of a real-world machine learning project beyond simply training and utilizing models. Robert will provide an overview of TFX, and talk in a little more detail about the pieces of the framework (tf.Transform and tf.ModelAnalysis) which are powered by Apache Beam.
In this Strata 2018 presentation, Ted Malaska and Mark Grover discuss how to make the most of big data at speed.
https://conferences.oreilly.com/strata/strata-ny/public/schedule/detail/72396
Near real-time anomaly detection at Lyftmarkgrover
Near real-time anomaly detection at Lyft, by Mark Grover and Thomas Weise at Strata NY 2018.
https://conferences.oreilly.com/strata/strata-ny/public/schedule/detail/69155
Presentation on dogfooding data at Lyft by Mark Grover and Arup Malakar on Oct 25, 2017 at Big Analytics Meetup (https://www.meetup.com/SF-Big-Analytics/events/243896328/)
Top 5 mistakes when writing Spark applicationsmarkgrover
This is a talk given at Advanced Spark meetup in San Francisco (http://www.meetup.com/Advanced-Apache-Spark-Meetup/events/223668878/). It focusses on common mistakes when writing Spark applications and how to avoid them.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/