Looming Marvelous - Virtual Threads in Java
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Today, we have 2 options for concurrency in Java: Simple, synchronous, blocking code with limited scalability that tracks well linearly at runtime, or complex, asynchronous libraries with high scalability, which are harder to handle Project Loom aims to bring together the best aspects of these two approaches and make them available to developers. In the talk, I'll briefly discuss the history and challenges of concurrency in Java before we dive into Loom's approaches and look a bit behind the scenes. Project Loom is included since Java 17 as a preview feature, it can already be tested to see how well it works with our applications and libraries. Spoiler: Pretty good.
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Looming Marvelous - Virtual Threads in Java Javaland.pdf
Nowadays we have 2 options for concurrency in Java:
* simple, synchronous, blocking code with limited scalability that tracks well linearly at runtime, or.
* complex, asynchronous libraries with high scalability that are harder to handle.
Project Loom aims to bring together the best aspects of these two approaches and make them available to developers.
In the talk, I'll briefly cover the history and challenges of concurrency in Java before we dive into Loom's approaches and do some behind-the-scenes implementation. To manage so many threads reasonably needs some structure - for this there are proposals for "Structured Concurrency" which we will also look at. Some examples and comparisons to test Loom will round up the talk.
Project Loom is included in Java 19 and 20 as a preview feature, it can already be tested how well it works with our applications and libraries.
Spoiler: Pretty good.
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and have been using it ever since. The language is
extremely powerful and easy to learn. But to truly
master it, you need to understand how it works
internally and how the database executes your
queries. In this session, you'll learn to look behind
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NBC News applied graph algorithms to the messages and follower networks of Russian Twitter trolls to gain further insights.
The Trumpworld organizational data correlated with US bills and government contracts offers starting points for further investigations.
New tools like graph databases allow data journalists to understand the intricate networks of the criminal, economic and political world better as those three examples show. Each journalist adding new connections helps others to validate their stories. They say "It's like magic".
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Looming Marvelous - Virtual Threads in Java Javaland.pdf
Nowadays we have 2 options for concurrency in Java:
* simple, synchronous, blocking code with limited scalability that tracks well linearly at runtime, or.
* complex, asynchronous libraries with high scalability that are harder to handle.
Project Loom aims to bring together the best aspects of these two approaches and make them available to developers.
In the talk, I'll briefly cover the history and challenges of concurrency in Java before we dive into Loom's approaches and do some behind-the-scenes implementation. To manage so many threads reasonably needs some structure - for this there are proposals for "Structured Concurrency" which we will also look at. Some examples and comparisons to test Loom will round up the talk.
Project Loom is included in Java 19 and 20 as a preview feature, it can already be tested how well it works with our applications and libraries.
Spoiler: Pretty good.
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Included in the JDK installation are a lot of handy tools for Java developers, from java, jshell and jcmd to jfr and jdeprscan. These allow you to analyze a running JVM, generate JRE's, run Java source code and much more. In this talk I would like to present a number of these tools with practical examples and thus expand the toolbox of the participants. With the command line tools, many tasks can be automated and executed more efficiently, leaving more time for the exciting things in developer life.
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and have been using it ever since. The language is
extremely powerful and easy to learn. But to truly
master it, you need to understand how it works
internally and how the database executes your
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the scenes at execution plans with PROFILE and
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structures, and operations help you minimize
Cypher and database operations. After this talk,
you should be able to speed up your Cypher
statements quite a bit.
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How Graphs Help Investigative Journalists to Connect the Dots
The Journalists of the ICIJ used graph technology to understand the relationships between the leaked pieces of information in the Panama and Paradise Papers.
NBC News applied graph algorithms to the messages and follower networks of Russian Twitter trolls to gain further insights.
The Trumpworld organizational data correlated with US bills and government contracts offers starting points for further investigations.
New tools like graph databases allow data journalists to understand the intricate networks of the criminal, economic and political world better as those three examples show. Each journalist adding new connections helps others to validate their stories. They say "It's like magic".
Join Michael for a look behind the scenes of graph based data ingestion, analysis and investigation.
We will use the open source graph database Neo4j, data visualization and graph algorithms to read between the lines.
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Michael Hunger explains the concepts behind Truffle and Graal and uses a practical example to show how you can use Python and JavaScript for “stored procedures” in a JVM-based database.
He demonstrates how to optimize the startup time of your application and container images by precompiling it to machine-code and examines its limits and the difference it makes. But nothing is perfect—Michael discusses the limitations and compares performances for the full picture.
Presentation at OSCON, PDX 2019.
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Now he asked me to help review the 2nd edition. Our discussions reminded me that each generation of developers should be taught this crucial skill. That's why I want to give an overview of core refactorings and code-smells but also demonstrate the tips and tricks of today's tools that make this task so much easier.
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We recently released the Neo4j graph algorithms library.
You can use these graph algorithms on your connected data to gain new insights more easily within Neo4j. You can use these graph analytics to improve results from your graph data, for example by focusing on particular communities or favoring popular entities.
We developed this library as part of our effort to make it easier to use Neo4j for a wider variety of applications. Many users expressed interest in running graph algorithms directly on Neo4j without having to employ a secondary system.
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Each of the files or classes of a projects source code represents a tree (AST). Looking at dependencies to other classes besides inheritance creates a graph though. Field types and method parameters are also implicit dependencies. Storing this information in a graph database like Neo4j allows for interesting queries and insights. Class-Graph provides that and is available as open-source github project.
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In this session Emil Eifrem provides a close look at the graph model and offers best use cases for effective, cost-efficient data storage and accessibility.
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Putting your data in a graph database is easy. We wanted to make it as easy to query the data. That's why we set out to create the cypher query language. This session introduces cypher shows a lot of examples and explains how it is used.
Geekout publish
Putting your data in a graph database is easy. We wanted to make it as easy to query the data. That's why we set out to create the Cypher query language. This session looks behind the scenes and explores how Cypher works internally, how it is implemented using Scala and talks about the lessons learned.
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These webinar slides provide a quick tour through graphs, graph databases, neo4j and spring data neo4j. The example app discussed is a twitter-graph.
Neo4j -[:LOVES]-> Cypher
The Neo4j Graph database was lacking a declarative query language.
We wanted to add a humane query language which is easy to read and understand. It borrows on other languages like SQL and SPARQL but brings it it's own flavor. Cypher uses ASCII ART to describe graph patterns that you're looking for.
We used Scala's parser combinator library in combination with functional approaches and lazy evaluation to develop the Cypher query language.
The talk describes the internals of the Cypher implementation.
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18 years ago I got hooked on Refactoring when Martin Fowler's first book came out. I've been using it since then on a daily basis on many different projects. Since then a lot has changed, especially with the help of modern IDEs with their automated refactorings and intentions.
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We recently released the Neo4j graph algorithms library.
You can use these graph algorithms on your connected data to gain new insights more easily within Neo4j. You can use these graph analytics to improve results from your graph data, for example by focusing on particular communities or favoring popular entities.
We developed this library as part of our effort to make it easier to use Neo4j for a wider variety of applications. Many users expressed interest in running graph algorithms directly on Neo4j without having to employ a secondary system.
We also tuned these algorithms to be as efficient as possible in regards to resource utilization as well as streamlined for later management and debugging.
In this session we'll look at some of these graph algorithms and the types of problems that you can use them for in your applications.
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I will show how to use the Neo4j-GraphQL extension, by creating an endpoint for the Game of Thrones dataset, and how we then can use our well-known tools (GraphiQL, apollo-client, graphql-cli, voyager) to interact with it.
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Despite the “Graph” in the name, GraphQL is mostly used to query relational databases or object models. But it is really well suited to querying graph databases too. In this talk, I’ll demonstrate how I implemented a GraphQL endpoint for the Neo4j graph database and how you would use it in your app.
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The world around us is full of connected information. Neo4j was originally developed to solve two complex "network" problems in a document management system, as it was too hard to manage rich connection information efficiently in traditional and new "NOSQL" databases.During this meetup, we will talk about the technology, and about the journey that a couple of technologists from Malmö took. You will learn* how Neo Technology grew from just the three founders in to a global database company with use-cases in every domain imaginable.* how focusing on customer and community feedback allows us to provide a solution for managing connected data to everyone, not just the large internet companies.
Of course we will also introduce the graph model, it's whiteboard friendlyness and how you get started with Neo4j and it's easy and powerful query language Cypher. We'll also compare the graph and relational data model to see how they differ in shape and capabilities. Finally we discuss the foundations that enable Graph databases to provide higher join performance, faster development processes and more inclusive software for all stakeholders. With use-cases from Gaming, Dating and Finance we'll see how to apply the graph capabilities to these domains to realize new functionality or opportunities that were not possible before.
Finally, if there's a question you've always wanted to ask/discuss, we'll have plenty of time for that at the end of Michael's presentation.
Class graph neo4j and software metrics
Each of the files or classes of a projects source code represents a tree (AST). Looking at dependencies to other classes besides inheritance creates a graph though. Field types and method parameters are also implicit dependencies. Storing this information in a graph database like Neo4j allows for interesting queries and insights. Class-Graph provides that and is available as open-source github project.
New Neo4j Auto HA Cluster
In this talk, Michael Hunger is going to shed some light over the new High Availability architecture for the popular Neo4j Graph Database. We are going to look at the different variants of the Paxos protocol, master failover strategies and cluster management state handling. This piece of infrastructure poses non-trivial challenges to distributed consensus-finding, an interesting session for anyone into scalable systems.
Spring Data Neo4j Intro SpringOne 2012
Graphs are everywhere. From websites adding social capabilities to Telcos providing personalized customer services, to innovative bioinformatics research, organizations are adopting graph databases as the best way to model and query connected data. If you can whiteboard, you can model your domain in a graph database.
In this session Emil Eifrem provides a close look at the graph model and offers best use cases for effective, cost-efficient data storage and accessibility.
Take Aways: Understand the model of a graph database and how it compares to document and relational databases Understand why graph databases are best suited for the storage, mapping and querying of connected data
Emil's presentation will be followed by a Hands-on Guide to Spring Data Neo4j. Spring Data Neo4j provides straightforward object persistence into the Neo4j graph database. Conceived by Rod Johnson and Neo Technology CEO Emil Eifrem, it is the founding project of the Spring Data effort. The library leverages a tight integration with the Spring Framework and the Spring Data infrastructure. Besides the easy to use object graph mapping it offers the powerful graph manipulation and query capabilities of Neo4j with a convenient API.
The talk introduces the different aspects of Spring Data Neo4j and shows applications in several example domains.
During the session we walk through the creation of a engaging sample application that starts with the setup and annotating the domain objects. We see the usage of Neo4jTemplate and the powerful repository abstraction. After deploying the application to a cloud PaaS we execute some interesting query use-cases on the collected data.
Intro to Cypher
Putting your data in a graph database is easy. We wanted to make it as easy to query the data. That's why we set out to create the cypher query language. This session introduces cypher shows a lot of examples and explains how it is used.
Geekout publish
Putting your data in a graph database is easy. We wanted to make it as easy to query the data. That's why we set out to create the Cypher query language. This session looks behind the scenes and explores how Cypher works internally, how it is implemented using Scala and talks about the lessons learned.
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An introduction of the Neo4j Graph database. Introduces the NOSQL space, the Graph Database concept, and Neo4j with examples.
Intro to Spring Data Neo4j
These webinar slides provide a quick tour through graphs, graph databases, neo4j and spring data neo4j. The example app discussed is a twitter-graph.
Neo4j -[:LOVES]-> Cypher
The Neo4j Graph database was lacking a declarative query language.
We wanted to add a humane query language which is easy to read and understand. It borrows on other languages like SQL and SPARQL but brings it it's own flavor. Cypher uses ASCII ART to describe graph patterns that you're looking for.
We used Scala's parser combinator library in combination with functional approaches and lazy evaluation to develop the Cypher query language.
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Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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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.
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💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
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Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
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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
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Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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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
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Here’s what you’ll gain:
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- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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