Building Community APIs using GraphQL, Neo4j, and KotlinNeo4j
Neo4j is a high performance, open-source graph database written in Java and Scala.
But of course, you can use and extend it from other JVM Languages, like Kotlin.
I've been using Kotlin on and off since 2012, that's when I wrote my first article about this pragmatic and clean programming language.
Today I want to demonstrate in 4 examples how you can use Neo4j with Kotlin.
In preparation for KotlinConf 2017 we started to gather community activity of the Kotlin community in a Neo4j graph.
You can see tweets, GitHub projects, StackOverflow questions and answers and meetup events in this database of developer activity.
After showing some examples we will explore how to query that database using a Kotlin driver for Neo4j.
Then we'll look at the Kotlin + Spring (Data) demo app, that shows community members who get a lot of praise on a Twitter wall.
My main Kotlin project over the last year has been the GraphQL extension for Neo4j.
So we'll have a look at how we can extend Neo4j with a custom HTTP API and how we integrate the GraphQL-Java library using Kotlin.
This extension manages a GraphQL schema to translate GraphQL queries to Neo4js native query language Cypher.
Another way to extend Neo4j is with user-defined procedures and functions which (with a small trick) are really easy to implement with Kotlin too.
We'll take a look at the procedures and functions we expose as part of the neo4j-graphql extension.
Presented at FOSDEM 2021: https://fosdem.org/2021/schedule/event/k8sconfigmgmtlandscape/
“We are all YAML engineers now” as Bob Walker said in 2018 in Ghent. So we now need something to manage these millions of lines of YAML. There’s the “Kubernetes application management tools” list by Bryan Grant with over 120 tool aiming at config management for Kubernetes. This area is evolving fast, and as k8s users we need some guidance to make informed decisions on what to use. In this talk I’ll describe the problem I need to solve and take a look into what we can learn from the previous generation of cfg mgmt tools. Then, will show some of the new tools and methods. Will not go into details of each solution, but rather compare different approaches and discuss which is good for specific needs.
Discover what's new in the Neo4j community for the week of 13 January 2018, including projects around FOSDEM, Knowledge Graphs, and the Azure template.
Shiny.collections - Google Docs-like live collaboration in Shiny!Marek Rogala
What users expect from web applications today differs dramatically from what was available 5 years ago. They are used to interactivity, data persistence, and what’s more, the ability to share live collaboration experiences, like in Google Docs. If one user changes the data, other users want to see the changes immediately on their screens. They don’t care whether it is a data-exploration app from a data scientist or a solution built by a team of software engineers.
Shiny is perfect for building interactive data-driven applications suited for the modern user. In this presentation, we show how to create real-time collaboration experience in Shiny apps.
From the presentation, you will learn the concepts of reactive databases, how to use them in Shiny, and how to adapt existing components to provide live collaboration.
We will present a package we developed for that. shiny.collections adds persistent reactive collections that can be effortlessly integrated with components like Shiny inputs, DT data table or rhandsontable. The package makes it easy to build collaborative Shiny applications with persistent data.
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.
Building Community APIs using GraphQL, Neo4j, and KotlinNeo4j
Neo4j is a high performance, open-source graph database written in Java and Scala.
But of course, you can use and extend it from other JVM Languages, like Kotlin.
I've been using Kotlin on and off since 2012, that's when I wrote my first article about this pragmatic and clean programming language.
Today I want to demonstrate in 4 examples how you can use Neo4j with Kotlin.
In preparation for KotlinConf 2017 we started to gather community activity of the Kotlin community in a Neo4j graph.
You can see tweets, GitHub projects, StackOverflow questions and answers and meetup events in this database of developer activity.
After showing some examples we will explore how to query that database using a Kotlin driver for Neo4j.
Then we'll look at the Kotlin + Spring (Data) demo app, that shows community members who get a lot of praise on a Twitter wall.
My main Kotlin project over the last year has been the GraphQL extension for Neo4j.
So we'll have a look at how we can extend Neo4j with a custom HTTP API and how we integrate the GraphQL-Java library using Kotlin.
This extension manages a GraphQL schema to translate GraphQL queries to Neo4js native query language Cypher.
Another way to extend Neo4j is with user-defined procedures and functions which (with a small trick) are really easy to implement with Kotlin too.
We'll take a look at the procedures and functions we expose as part of the neo4j-graphql extension.
Presented at FOSDEM 2021: https://fosdem.org/2021/schedule/event/k8sconfigmgmtlandscape/
“We are all YAML engineers now” as Bob Walker said in 2018 in Ghent. So we now need something to manage these millions of lines of YAML. There’s the “Kubernetes application management tools” list by Bryan Grant with over 120 tool aiming at config management for Kubernetes. This area is evolving fast, and as k8s users we need some guidance to make informed decisions on what to use. In this talk I’ll describe the problem I need to solve and take a look into what we can learn from the previous generation of cfg mgmt tools. Then, will show some of the new tools and methods. Will not go into details of each solution, but rather compare different approaches and discuss which is good for specific needs.
Discover what's new in the Neo4j community for the week of 13 January 2018, including projects around FOSDEM, Knowledge Graphs, and the Azure template.
Shiny.collections - Google Docs-like live collaboration in Shiny!Marek Rogala
What users expect from web applications today differs dramatically from what was available 5 years ago. They are used to interactivity, data persistence, and what’s more, the ability to share live collaboration experiences, like in Google Docs. If one user changes the data, other users want to see the changes immediately on their screens. They don’t care whether it is a data-exploration app from a data scientist or a solution built by a team of software engineers.
Shiny is perfect for building interactive data-driven applications suited for the modern user. In this presentation, we show how to create real-time collaboration experience in Shiny apps.
From the presentation, you will learn the concepts of reactive databases, how to use them in Shiny, and how to adapt existing components to provide live collaboration.
We will present a package we developed for that. shiny.collections adds persistent reactive collections that can be effortlessly integrated with components like Shiny inputs, DT data table or rhandsontable. The package makes it easy to build collaborative Shiny applications with persistent data.
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.
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.
Language documentation projects all over the world have accumulated a large and heterogeneous corpus of linguistic material. Because of its diversity, access to and analysis of the components is difficult, particularly for multimedia instances. The "Graph Annotation Framework" (GrAF), a standoff annotation method, is applied to utterance examples in time-aligned annotations of video samples. An easy-to-use programming interface defined in the Poio API, a project within the CLARIN framwork ("Common Language Resources and Technology Infrastructure"), then greatly simplifies access without the need to deal with multiple input formats in the source material. GrAF-XML provides a basis for exchanging results among the various projects that analyze the corpus.
All About GRAND Stack: GraphQL, React, Apollo, and Neo4j (Mark Needham) - Gre...GreeceJS
In this presentation, we explore application development using the GRAND stack (GraphQL, React, Apollo, Neo4j) for building web applications backed by a graph database. We will review the components to build a simple web application, including how to build a React component, an introduction to JSX, an overview of GraphQL and why it is a game-changer for front-end development. We'll learn how to model, store, and query data in the Neo4j graph database using GraphQL to power our web application.
The ripped path in combining frontend with the backend has been the REST API for years. Can you do it differently? Of course! Meet the alternative that has something to offer - GraphQL.
GlueCon 2015 - Publish your SQL data as web APIsRestlet
With increasing demand for universal access to data, web APIs are an easy way to provide data sets to partners, customers, or even the entire world! For many businesses, bridging the gap between SQL databases and web APIs is not as easy as it looks. There are however simple ways to create data-driven APIs without programming. We’ll provide an overview of the technical challenges and how to overcome them. We’ll also show example deployments of APIs that provide access to SQL data.
Dataset Descriptions in Open PHACTS and HCLSAlasdair Gray
This presentation gives an overview of the dataset description specification developed in the Open PHACTS project (http://www.openphacts.org/). The creation of the specification was driven by a real need within the project to track the datasets used.
Details of the dataset metadata captured and the vocabularies used to model this metadata are given together with the tools developed to enable the specification's uptake.
Over the course of the last 12 months, the W3C Healthcare and Life Science Interest Group have been developing a community profile for dataset descriptions. This has drawn on the ideas developed in the Open PHACTS specification. A brief overview of the forthcoming community profile is given in the presentation.
This presentation was given to the Network Data Exchange project http://www.ndexbio.org/ on 2 April 2014.
What does GraphQL and Traditional REST API have in common? Shouldn't the GraphQL be connected to some graphs or similar? What is actually GraphQL all about?
Join me in this talk, while I try to answer all this questions and much more.
In this talk I will explain what GraphQL is, what are differences and similarities compared to more traditional REST API and show you this on working examples, since code worth more then words only ;)
What does GraphQL and Traditional REST API have in common? Shouldn't the GraphQL be connected to some graphs or similar? What is actually GraphQL all about?
Join me in this talk, while I try to answer all this questions and much more.
In this talk I will explain what GraphQL is, what are differences and similarities compared to more traditional REST API and show you this on working examples, since code worth more then words only ;)
GitHub: https://github.com/vladimir-dejanovic/graphql-vs-traditional-rest-api-conftalk_demo
When moving from a proprietary and hosted IR solution to a local and open one, an intense migration schedule necessitated some time saving measures and ETD and faculty publications were moved with only submitter-assigned keywords. After seeing the reduction of controlled subject access points, FSU’s Digital Library Center developed a python script using direct matches between the submitted keywords and subject headings in LC’s linked data service to add subject elements to MODS records. Safely in post-migration, FSU Libraries can retroactively and automatically provide controlled subject access and linked data URIs to IR materials and integrate the script into the submission workflow for improved access to future materials.
Challenges in knowledge graph visualizationGraphAware
Visualizing a complex graph is a task of graph simplification and providing well-thought visual cues, the best UI goes unnoticed. This talk will summarize current approaches and present a novel user interaction pattern, which takes advantage of a performant Neo4j graph engine.
About the speaker:
Jan Zak - Senior Consultant at GraphAware; Data visualizations, graphs, maps; Based in Prague, Czech Republic
Introduction to Open Services for Lifecycle Collaboration (OSLC)Axel Reichwein
Quick Introduction on OSLC APIs For Digital Engineering Information Exchange (DEIX) Community explaining fundamental ideas behind OSLC including:
- Distributed Link Creation Strategy from within ANY application
- Link creation decoupled from link persistence/analysis/visualization
- Embeddable search dialogs to support user-friendly link target discovery in any application
- Standardized API discovery resources (Hypermedia API)
GraphQL - The new "Lingua Franca" for API-Developmentjexp
Three years ago, with the release of the GraphQL specification, Facebook took a fresh stab at the topic of "API design between remote services and applications." The key aspects of GraphQL provide a common, schema-based, domain-specific language and flexible, dynamic queries at interface boundaries.
In the talk, I'd like to compare GraphQL and REST and showcase benefits for developers and architects using a concrete example in application and API development, data source and system integration.
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.
Language documentation projects all over the world have accumulated a large and heterogeneous corpus of linguistic material. Because of its diversity, access to and analysis of the components is difficult, particularly for multimedia instances. The "Graph Annotation Framework" (GrAF), a standoff annotation method, is applied to utterance examples in time-aligned annotations of video samples. An easy-to-use programming interface defined in the Poio API, a project within the CLARIN framwork ("Common Language Resources and Technology Infrastructure"), then greatly simplifies access without the need to deal with multiple input formats in the source material. GrAF-XML provides a basis for exchanging results among the various projects that analyze the corpus.
All About GRAND Stack: GraphQL, React, Apollo, and Neo4j (Mark Needham) - Gre...GreeceJS
In this presentation, we explore application development using the GRAND stack (GraphQL, React, Apollo, Neo4j) for building web applications backed by a graph database. We will review the components to build a simple web application, including how to build a React component, an introduction to JSX, an overview of GraphQL and why it is a game-changer for front-end development. We'll learn how to model, store, and query data in the Neo4j graph database using GraphQL to power our web application.
The ripped path in combining frontend with the backend has been the REST API for years. Can you do it differently? Of course! Meet the alternative that has something to offer - GraphQL.
GlueCon 2015 - Publish your SQL data as web APIsRestlet
With increasing demand for universal access to data, web APIs are an easy way to provide data sets to partners, customers, or even the entire world! For many businesses, bridging the gap between SQL databases and web APIs is not as easy as it looks. There are however simple ways to create data-driven APIs without programming. We’ll provide an overview of the technical challenges and how to overcome them. We’ll also show example deployments of APIs that provide access to SQL data.
Dataset Descriptions in Open PHACTS and HCLSAlasdair Gray
This presentation gives an overview of the dataset description specification developed in the Open PHACTS project (http://www.openphacts.org/). The creation of the specification was driven by a real need within the project to track the datasets used.
Details of the dataset metadata captured and the vocabularies used to model this metadata are given together with the tools developed to enable the specification's uptake.
Over the course of the last 12 months, the W3C Healthcare and Life Science Interest Group have been developing a community profile for dataset descriptions. This has drawn on the ideas developed in the Open PHACTS specification. A brief overview of the forthcoming community profile is given in the presentation.
This presentation was given to the Network Data Exchange project http://www.ndexbio.org/ on 2 April 2014.
What does GraphQL and Traditional REST API have in common? Shouldn't the GraphQL be connected to some graphs or similar? What is actually GraphQL all about?
Join me in this talk, while I try to answer all this questions and much more.
In this talk I will explain what GraphQL is, what are differences and similarities compared to more traditional REST API and show you this on working examples, since code worth more then words only ;)
What does GraphQL and Traditional REST API have in common? Shouldn't the GraphQL be connected to some graphs or similar? What is actually GraphQL all about?
Join me in this talk, while I try to answer all this questions and much more.
In this talk I will explain what GraphQL is, what are differences and similarities compared to more traditional REST API and show you this on working examples, since code worth more then words only ;)
GitHub: https://github.com/vladimir-dejanovic/graphql-vs-traditional-rest-api-conftalk_demo
When moving from a proprietary and hosted IR solution to a local and open one, an intense migration schedule necessitated some time saving measures and ETD and faculty publications were moved with only submitter-assigned keywords. After seeing the reduction of controlled subject access points, FSU’s Digital Library Center developed a python script using direct matches between the submitted keywords and subject headings in LC’s linked data service to add subject elements to MODS records. Safely in post-migration, FSU Libraries can retroactively and automatically provide controlled subject access and linked data URIs to IR materials and integrate the script into the submission workflow for improved access to future materials.
Challenges in knowledge graph visualizationGraphAware
Visualizing a complex graph is a task of graph simplification and providing well-thought visual cues, the best UI goes unnoticed. This talk will summarize current approaches and present a novel user interaction pattern, which takes advantage of a performant Neo4j graph engine.
About the speaker:
Jan Zak - Senior Consultant at GraphAware; Data visualizations, graphs, maps; Based in Prague, Czech Republic
Introduction to Open Services for Lifecycle Collaboration (OSLC)Axel Reichwein
Quick Introduction on OSLC APIs For Digital Engineering Information Exchange (DEIX) Community explaining fundamental ideas behind OSLC including:
- Distributed Link Creation Strategy from within ANY application
- Link creation decoupled from link persistence/analysis/visualization
- Embeddable search dialogs to support user-friendly link target discovery in any application
- Standardized API discovery resources (Hypermedia API)
GraphQL - The new "Lingua Franca" for API-Developmentjexp
Three years ago, with the release of the GraphQL specification, Facebook took a fresh stab at the topic of "API design between remote services and applications." The key aspects of GraphQL provide a common, schema-based, domain-specific language and flexible, dynamic queries at interface boundaries.
In the talk, I'd like to compare GraphQL and REST and showcase benefits for developers and architects using a concrete example in application and API development, data source and system integration.
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/16WDJ8b.
Eli Collins overviews how to build new applications with Hadoop and how to integrate Hadoop with existing applications, providing an update on the state of Hadoop ecosystem, frameworks and APIs.Filmed at qconnewyork.com.
Eli Collins is the tech lead for Cloudera's Platform team, an active contributor to Apache Hadoop and member of its project management committee (PMC) at the Apache Software Foundation. Eli holds Bachelor's and Master's degrees in Computer Science from New York University and the University of Wisconsin-Madison, respectively.
In this talk, we shared some of our highlights of the GraphQL Europe conference.
You can see the full coverage of the conference here: https://www.graph.cool/talks/
Graph Analytics on Data from Meetup.comKarin Patenge
How to improve your Meetup experience by using Graph Analytics on data from Meetup.com. Slides from my session with "Women Who Code" group in Berlin on May 23, 2018.
apidays LIVE Paris 2021 - Stargate.io, An OSS Api Layer for your Cassandra by...apidays
apidays LIVE Paris 2021 - APIs and the Future of Software
December 7, 8 & 9, 2021
Stargate.io, An OSS Api Layer for your Cassandra
Cedrick Lunven, Director of Developer Relations at DataStax
This introductory level talk is about Apache Flink: a multi-purpose Big Data analytics framework leading a movement towards the unification of batch and stream processing in the open source.
With the many technical innovations it brings along with its unique vision and philosophy, it is considered the 4 G (4th Generation) of Big Data Analytics frameworks providing the only hybrid (Real-Time Streaming + Batch) open source distributed data processing engine supporting many use cases: batch, streaming, relational queries, machine learning and graph processing.
In this talk, you will learn about:
1. What is Apache Flink stack and how it fits into the Big Data ecosystem?
2. How Apache Flink integrates with Hadoop and other open source tools for data input and output as well as deployment?
3. Why Apache Flink is an alternative to Apache Hadoop MapReduce, Apache Storm and Apache Spark.
4. Who is using Apache Flink?
5. Where to learn more about Apache Flink?
GraphQL as an alternative approach to REST (as presented at Java2Days/CodeMon...luisw19
Originally designed by Facebook to allow its mobile clients to define exactly what data should be send back by an API and therefore avoid unnecessary roundtrips and data usage, GraphQL is a JSON based query language for Web APIs. Since it was open sourced by Facebook in 2015, it has undergone very rapid adoption and many companies have already switch to the GraphQL way of building APIs – see http://GraphQL.org/users.
However, with some many hundreds of thousands of REST APIs publicly available today (and many thousands others available internally), what are the implications of moving to GraphQL? Is it really worth the effort of replacing REST APIs specially if they’re successful and performing well in production? What are the pros/cons of using GraphQL? What tools / languages can be used for GraphQL? What about API Gateways? What about API design?
With a combination of rich content and hands-on demonstrations, attend this session for a point of view on how address these and many other questions, and most importantly get a better understanding and when/where/why/if GraphQL applies for your organisation or specific use case.
From http://www.csdn.net/article/2015-12-17/2826501
《Databricks公司联合创始人、Spark首席架构师辛湜:Spark发展:回顾2015,展望2016 》
辛湜介绍了Spark的目标是“Unified engine across data workloads and platforms”。在谈到Spark在2015年最大的改变时,他感觉应该是增加了DataFrames API。对于Spark的生态圈,他表示主要侧重三个不同的方向,一个是上层的应用,二是下层的环境,还有最重要的是连接到的数据源。
Present and future of unified, portable, and efficient data processing with A...DataWorks Summit
The world of big data involves an ever-changing field of players. Much as SQL stands as a lingua franca for declarative data analysis, Apache Beam aims to provide a portable standard for expressing robust, out-of-order data processing pipelines in a variety of languages across a variety of platforms. In a way, Apache Beam is a glue that can connect the big data ecosystem together; it enables users to "run any data processing pipeline anywhere."
This talk will briefly cover the capabilities of the Beam model for data processing and discuss its architecture, including the portability model. We’ll focus on the present state of the community and the current status of the Beam ecosystem. We’ll cover the state of the art in data processing and discuss where Beam is going next, including completion of the portability framework and the Streaming SQL. Finally, we’ll discuss areas of improvement and how anybody can join us on the path of creating the glue that interconnects the big data ecosystem.
Speaker
Davor Bonaci, Apache Software Foundation; Simbly, V.P. of Apache Beam; Founder/CEO at Operiant
Microsoft and Revolution Analytics -- what's the add-value? 20150629Mark Tabladillo
Microsoft has been a leader in the enterprise analytics space for years. In 2014, Microsoft had already created R language functionality within Azure Machine Learning. On April 6, 2015, Microsoft and closed on a deal to acquire Revolution Analytics, a company focusing on scalable processing solutions initiated by the well-known R language. Many data science projects and initial demos do not need high-volume solutions: however, having a high-volume answer for the R language allows for planning or working toward the largest data science solutions.
This presentation describes the add-value for the Revolution Analytics acquisition. The talk covers 1) an overview of current data science technologies from Microsoft; 2) a description of the R language; 3) a brief review of the add-value for R with Azure Machine Learning, and 4) a description of the performance architecture and demo of the language constructs developed by Revolution Analytics. Most of the presentation will be focused on sections two and four. It is anticipated that these technologies will be partially if not fully integrated into SQL Server 2016.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 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
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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.
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
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- 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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Assuring Contact Center Experiences for Your Customers With ThousandEyes
The Property Graph Query Language Landscape: openCypher and Property Graph Extensions to SQL
1. Property Graph Query Language Landscape
Alastair Green Neo4j
openCypher Implementers Group meeting 3, 27 July 2017
2. LDBC, openCypher, ISO/INCITS
There’s a lot going on!
April 2015 Linked Data Benchmark Council (LDBC) set up a Query Language TF
SQL used as the lingua franca of TPC benchmark definitions, where is the standard
graph query language. Now getting to the point of proposing new features.
openCypher announced autumn 2015: started with 2016 work on software artefacts
February 2017 first oCIM → oCIGs → implementer consensus model (no Neo4j veto)
INCITS Ad Hoc on SQL Extensions Property Graphs April 2017
“Project split” to set up formal ISO SQL/PGQ project with a four-year horizon June 2017
2
4. What’s being discussed? LDBC
LDBC Graph QL TF
Mix of vendors and researchers
Started with examination of existing languages (including Cypher, PGQL)
Composable language (closure over the PG data model, “returning graphs”)
Extended Property Graph Data Model “paths as first class citizens”
Complexity and its implications for path queries (relates to “morphism”)
Has reached the point where the group feels they are ready to propose syntax
Change an existing language, or create a new one?
4
5. The openCypher community: towards an open standard
In late 2015 Neo announced the openCypher initiative
Apache-licensed grammar, ANTLR parser, TCK
Open Cypher Improvements process based on Github issues/discussions
Work has started on a formal specification of Cypher (denotational semantics) by
University of Edinburgh
6. Governed by the openCypher Implementers Group
In 2017 two face-to-face openCypher Implementers Meetings have taken place
Regular openCypher Implementers Group virtual meetings scheduled through to October
Consensus-based governance:
open to all, but implementers
“at the heart of the consensus”
7. Cypher implementations
Cypher is used as the graph query language of four commercial/OSS databases
Neo4j Enterprise Server, SAP HANA Graph, AgensGraph/Postgres, and RedisGraph
There are other databases/query engines in gestation or in the research community
Memgraph, Ingraph, Scott Tiger, Cypher for Apache Spark, Graphflow ...
There are several other projects or tools that use Cypher
IDEA plugin from Neueda, language parsers, editors, GraphQL Cypher directives, ...
8. What’s being discussed? openCypher
openCypher
2016 Oracle paper on PGX, PGQL and Green Marl criticised Cypher
Path expressions weak PGQL “path patterns” are very nice concept
“Morphism”
No graph construction (composition in another form)
No views (composition in another form)
Meshed with pre-existing discussions in Neo4j Cypher Language Group
Other issues like sub-queries, SQL interactions, aggregation, … many live topics
8
9. What’s being discussed? INCITS/ISO
INCITS Ad Hoc, SQL/PGQ
Graph objects in SQL and relationship to relational data model
Should SQL be extended to incorporate graph data model concepts?
Should SQL interoperate with graph query engines with their own language(s)
Over to Jan Michels (Oracle), Ad-Hoc Group Chair
9
10. SQL and Cypher (and PGQL)
Alastair Green Neo4j
openCypher Implementers Group meeting 3, 27 July 2017