MapReduce is a programming model and framework developed by Google for processing and generating large datasets in a distributed computing environment. It allows parallel processing of large datasets across clusters of computers using a simple programming model. It works by breaking the processing into many small fragments of work that can be executed in parallel by the different machines, and then combining the results at the end.
Geoff Rothman Presentation on Parallel ProcessingGeoff Rothman
Presentation to University of Kentucky Computer Science graduate studentrs on high level Cloud Computing, how MapReduce works, and the current competition for Parallel Processing on a Massive Scale
Social Media Marketing Overview presented at the 11/18/10 Pathways to Entrepreneurial Success Forum held at Monroe Community College. Contains an overview of the top social media platforms, 5 steps to get started with social media marketing and the 4 rules you must follow.
Geoff Rothman Presentation on Parallel ProcessingGeoff Rothman
Presentation to University of Kentucky Computer Science graduate studentrs on high level Cloud Computing, how MapReduce works, and the current competition for Parallel Processing on a Massive Scale
Social Media Marketing Overview presented at the 11/18/10 Pathways to Entrepreneurial Success Forum held at Monroe Community College. Contains an overview of the top social media platforms, 5 steps to get started with social media marketing and the 4 rules you must follow.
Functional Web Development – An Introduction to React.js
with Bertrand Karerangabo
Presented at FITC's Web Unleashed 2014 conference
on September 18 2014
More info at www.fitc.ca
React.js is a UI framework created by Facebook and Instagram. Its primary design goal is to help build large applications with data that changes over time. To do so at scale, conventional wisdom and some long-held assumptions about software development had to be challenged. Gone are the “M” and the “C” in MVC. Gone are templates and special HTML directives. Gone also are traditional data-bindings. The results are applications that are extremely fast and reliable, out of the box.
Bertrand Karerangabo will dive into those concepts that make React.js unique and along the way, also learn how to build web applications from simple, composable and reusable components.
OBJECTIVE
Rethink web development best practices and explore how you can build ambitious and performant application using functional programming with a virtual DOM representation.
TARGET AUDIENCE
Javascript developers working on medium to large dynamic applications.
ASSUMED AUDIENCE KNOWLEDGE
A solid understanding of Javascript and the DOM is strongly recommended.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
What React.js is and why it was built.
How to deal with the “evil” of mutable state in non-trivial applications.
A strategy for working around notoriously slow and expensive DOM operations.
The way to truly separate concerns, instead of just technologies, in an application.
The SEO, performance and usability benefits that come from using a client-side framework that plays nice with the server.
Writing MapReduce Programs using Java | Big Data Hadoop Spark Tutorial | Clou...CloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2kyXPo0
This CloudxLab Writing MapReduce Programs tutorial helps you to understand how to write MapReduce Programs using Java in detail. Below are the topics covered in this tutorial:
1) Why MapReduce?
2) Write a MapReduce Job to Count Unique Words in a Text File
3) Create Mapper and Reducer in Java
4) Create Driver
5) MapReduce Input Splits, Secondary Sorting, and Partitioner
6) Combiner Functions in MapReduce
7) Job Chaining and Pipes in MapReduce
Big Data & Analytics MapReduce/Hadoop – A programmer’s perspectiveEMC
In this session two of the most prominent technologies in the realm of Big Data are covered; namely MapReduce and Hadoop.
We will take an in-depth look at MapReduce, Hadoop, and the Hadoop ecosystem, including:
1. Hadoop Setup and Maintenance
2. MapReduce/Hadoop Programming
3. Interacting with the Hadoop Distributed File System (HDFS)
A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps, which are then input to the reduce tasks. Typically both the input and the output of the job are stored in a file-system.
Storm is a distributed realtime computation system. Similar to how Hadoop provides a set of general primitives for doing batch processing, Storm provides a set of general primitives for doing realtime computation.
Storm often coexists in Big Data architectures with Hadoop. We will talk about different approaches to this interoperability between the systems, their benefits & trade-offs, and a new open source library available for high throughput use.
Frustrated trying to run/debug MapReduce applications on my laptop, I decided to spin my own MR framework to solve the problems of efficiency, configuration, and error messages. Go is a compiled language and has inherent support for distribution in the form of channels. I took advantage of these two strengths to create GoMR.
In this talk, I give an overview of the framework, the programming style I used to create it, and an evaluation of the framework against a current state of the art system, Apache Spark.
I show how I leveraged Kubernetes, a container orchestration system, to scale GoMR to many machines. As much as possible, GoMR off-loads the work of a control plane onto Kubernetes.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Functional Web Development – An Introduction to React.js
with Bertrand Karerangabo
Presented at FITC's Web Unleashed 2014 conference
on September 18 2014
More info at www.fitc.ca
React.js is a UI framework created by Facebook and Instagram. Its primary design goal is to help build large applications with data that changes over time. To do so at scale, conventional wisdom and some long-held assumptions about software development had to be challenged. Gone are the “M” and the “C” in MVC. Gone are templates and special HTML directives. Gone also are traditional data-bindings. The results are applications that are extremely fast and reliable, out of the box.
Bertrand Karerangabo will dive into those concepts that make React.js unique and along the way, also learn how to build web applications from simple, composable and reusable components.
OBJECTIVE
Rethink web development best practices and explore how you can build ambitious and performant application using functional programming with a virtual DOM representation.
TARGET AUDIENCE
Javascript developers working on medium to large dynamic applications.
ASSUMED AUDIENCE KNOWLEDGE
A solid understanding of Javascript and the DOM is strongly recommended.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
What React.js is and why it was built.
How to deal with the “evil” of mutable state in non-trivial applications.
A strategy for working around notoriously slow and expensive DOM operations.
The way to truly separate concerns, instead of just technologies, in an application.
The SEO, performance and usability benefits that come from using a client-side framework that plays nice with the server.
Writing MapReduce Programs using Java | Big Data Hadoop Spark Tutorial | Clou...CloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2kyXPo0
This CloudxLab Writing MapReduce Programs tutorial helps you to understand how to write MapReduce Programs using Java in detail. Below are the topics covered in this tutorial:
1) Why MapReduce?
2) Write a MapReduce Job to Count Unique Words in a Text File
3) Create Mapper and Reducer in Java
4) Create Driver
5) MapReduce Input Splits, Secondary Sorting, and Partitioner
6) Combiner Functions in MapReduce
7) Job Chaining and Pipes in MapReduce
Big Data & Analytics MapReduce/Hadoop – A programmer’s perspectiveEMC
In this session two of the most prominent technologies in the realm of Big Data are covered; namely MapReduce and Hadoop.
We will take an in-depth look at MapReduce, Hadoop, and the Hadoop ecosystem, including:
1. Hadoop Setup and Maintenance
2. MapReduce/Hadoop Programming
3. Interacting with the Hadoop Distributed File System (HDFS)
A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps, which are then input to the reduce tasks. Typically both the input and the output of the job are stored in a file-system.
Storm is a distributed realtime computation system. Similar to how Hadoop provides a set of general primitives for doing batch processing, Storm provides a set of general primitives for doing realtime computation.
Storm often coexists in Big Data architectures with Hadoop. We will talk about different approaches to this interoperability between the systems, their benefits & trade-offs, and a new open source library available for high throughput use.
Frustrated trying to run/debug MapReduce applications on my laptop, I decided to spin my own MR framework to solve the problems of efficiency, configuration, and error messages. Go is a compiled language and has inherent support for distribution in the form of channels. I took advantage of these two strengths to create GoMR.
In this talk, I give an overview of the framework, the programming style I used to create it, and an evaluation of the framework against a current state of the art system, Apache Spark.
I show how I leveraged Kubernetes, a container orchestration system, to scale GoMR to many machines. As much as possible, GoMR off-loads the work of a control plane onto Kubernetes.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
20. Main Function
Class MyJob{
public static void main(String[] args) {
JobConf conf = new JobConf(MyJob.class);
conf.setJobName(”Caculate feedback log time distributionquot;);
// set path
conf.setInputPath(new Path(args[0]));
conf.setOutputPath(new Path(args[1]));
// set map reduce
conf.setOutputKeyClass(Text.class); // set every word as key
conf.setOutputValueClass(IntWritable.class); // set 1 as value
conf.setMapperClass(MapClass.class);
conf.setCombinerClass(Reduce.class);
conf.setReducerClass(ReduceClass.class);
onf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
// run
JobClient.runJob(conf);
}}
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