Introduction to ArangoDB (nosql matters Barcelona 2012)ArangoDB Database
ArangoDB is a universal open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient sql-like query language or JavaScript/Ruby extensions.
The video is also available online:
http://2012.nosql-matters.org/bcn/speakers/
Apache Arrow Workshop at VLDB 2019 / BOSS SessionWes McKinney
Technical deep dive for database system developers in the Arrow columnar format, binary protocol, C++ development platform, and Arrow Flight RPC.
See demo Jupyter notebooks at https://github.com/wesm/vldb-2019-apache-arrow-workshop
HUG_Ireland_Apache_Arrow_Tomer_Shiran John Mulhall
A presentation by Tomer Shiran, CEO of Dremio made to Hadoop User Group (HUG) Ireland on "Hadoop Summit Night" on April 12th, 2016. This presentation covers Apache Arrow in detail.
Introduction to ArangoDB (nosql matters Barcelona 2012)ArangoDB Database
ArangoDB is a universal open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient sql-like query language or JavaScript/Ruby extensions.
The video is also available online:
http://2012.nosql-matters.org/bcn/speakers/
Apache Arrow Workshop at VLDB 2019 / BOSS SessionWes McKinney
Technical deep dive for database system developers in the Arrow columnar format, binary protocol, C++ development platform, and Arrow Flight RPC.
See demo Jupyter notebooks at https://github.com/wesm/vldb-2019-apache-arrow-workshop
HUG_Ireland_Apache_Arrow_Tomer_Shiran John Mulhall
A presentation by Tomer Shiran, CEO of Dremio made to Hadoop User Group (HUG) Ireland on "Hadoop Summit Night" on April 12th, 2016. This presentation covers Apache Arrow in detail.
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
Виталий Бондаренко "Fast Data Platform for Real-Time Analytics. Architecture ...Fwdays
We will start from understanding how Real-Time Analytics can be implemented on Enterprise Level Infrastructure and will go to details and discover how different cases of business intelligence be used in real-time on streaming data. We will cover different Stream Data Processing Architectures and discus their benefits and disadvantages. I'll show with live demos how to build Fast Data Platform in Azure Cloud using open source projects: Apache Kafka, Apache Cassandra, Mesos. Also I'll show examples and code from real projects.
Presto @ Treasure Data - Presto Meetup Boston 2015Taro L. Saito
Treasure Data simplifies event analytics for the complex digital
world. Our customers send us 1,000,000 events per second and issue 30,000+ Presto queries everyday to understand their customers better. One of the challenges is designing a cloud database with zero downtime to support a global customer base. We have achieved this goal by developing several open-source technologies; Fluentd and Embulk enable seamless log collection from stream/batch sources, and with MessagePack we can provide an extensible columnar store that accommodates future schema changes. Finally, Presto allows us to serve a wide variety of data processing our customers perform on our service. In this talk, I will present an overview of our system, and how our customers keep using Presto while collecting and extending their data set.
Apache Arrow is a new standard for in-memory columnar data processing. It is a complement to Apache Parquet and Apache ORC. In this deck we review key design goals and how Arrow works in detail.
Performance comparison: Multi-Model vs. MongoDB and Neo4jArangoDB Database
Native multi-model databases combine different data models like documents or graphs in one tool and even allow to mix them in a single query. How can this concept compete with a pure document store like MongoDB or a graph database like Neo4j? I myself and a lot of folks in the community asked that question.
So here are some benchmark results.
Hello, Enterprise! Meet Presto. (Presto Boston Meetup 10062015)Matt Fuller
Teradata has been hard at work on Presto, and we want to share with you what we've done so far and our roadmap going forward. From presto-admin, a tool for installing and administering Presto, to YARN/Ambari support, to fully certified JDBC and ODBC drivers, we are committed to making Presto the best, most enterprise-ready SQL-on Hadoop solution out there.
Find out how NoSQL can help your application with practical examples and use-cases from our Cloud Data Services Developer Advocate Glynn Bird. This webinar won't dwell on the science behind the database, but will walk you through real-life use-cases for NoSQL technologies that you can start using today.
Webinar: https://youtu.be/M_Jqw
Learn what you need to consider when moving from the world of relational databases to a NoSQL document store.
Hear from Developer Advocate Glynn Bird as he explains the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
Виталий Бондаренко "Fast Data Platform for Real-Time Analytics. Architecture ...Fwdays
We will start from understanding how Real-Time Analytics can be implemented on Enterprise Level Infrastructure and will go to details and discover how different cases of business intelligence be used in real-time on streaming data. We will cover different Stream Data Processing Architectures and discus their benefits and disadvantages. I'll show with live demos how to build Fast Data Platform in Azure Cloud using open source projects: Apache Kafka, Apache Cassandra, Mesos. Also I'll show examples and code from real projects.
Presto @ Treasure Data - Presto Meetup Boston 2015Taro L. Saito
Treasure Data simplifies event analytics for the complex digital
world. Our customers send us 1,000,000 events per second and issue 30,000+ Presto queries everyday to understand their customers better. One of the challenges is designing a cloud database with zero downtime to support a global customer base. We have achieved this goal by developing several open-source technologies; Fluentd and Embulk enable seamless log collection from stream/batch sources, and with MessagePack we can provide an extensible columnar store that accommodates future schema changes. Finally, Presto allows us to serve a wide variety of data processing our customers perform on our service. In this talk, I will present an overview of our system, and how our customers keep using Presto while collecting and extending their data set.
Apache Arrow is a new standard for in-memory columnar data processing. It is a complement to Apache Parquet and Apache ORC. In this deck we review key design goals and how Arrow works in detail.
Performance comparison: Multi-Model vs. MongoDB and Neo4jArangoDB Database
Native multi-model databases combine different data models like documents or graphs in one tool and even allow to mix them in a single query. How can this concept compete with a pure document store like MongoDB or a graph database like Neo4j? I myself and a lot of folks in the community asked that question.
So here are some benchmark results.
Hello, Enterprise! Meet Presto. (Presto Boston Meetup 10062015)Matt Fuller
Teradata has been hard at work on Presto, and we want to share with you what we've done so far and our roadmap going forward. From presto-admin, a tool for installing and administering Presto, to YARN/Ambari support, to fully certified JDBC and ODBC drivers, we are committed to making Presto the best, most enterprise-ready SQL-on Hadoop solution out there.
Find out how NoSQL can help your application with practical examples and use-cases from our Cloud Data Services Developer Advocate Glynn Bird. This webinar won't dwell on the science behind the database, but will walk you through real-life use-cases for NoSQL technologies that you can start using today.
Webinar: https://youtu.be/M_Jqw
Learn what you need to consider when moving from the world of relational databases to a NoSQL document store.
Hear from Developer Advocate Glynn Bird as he explains the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
UML-Driven Software Performance Engineering: A systematic mapping and a revie...Vahid Garousi
Slides for my invited talk in the 1st International Workshop on Advanced Topics on Software Engineering (ATSEN 2014), Istanbul Kultur University, on November 7, 2014
UML-Driven Software Performance Engineering: A systematic mapping and a review of several selected techniques
In English: Latest Trends in Software Engineering (Yazılım Mühendisliğinde S...Vahid Garousi
Latest Trends in Software Engineering
Yazılım Mühendisliğinde Son Trendler
Technology Seminars
Doç. Dr. Vahid Garousi
Department of Computer Engineering
Hacettepe University
Beytepe, Ankara
Turkey
DITA Quick Start Webinar Series: Getting Started with the DITA Open ToolkitSuite Solutions
Presenter: Adena Frazer, Senior Developer, Suite Solutions
Abstract:
In this webinar you will learn about the DITA Open Toolkit architecture and acquire the basics of running and benefiting from the DITA-OT. This webinar will guide you in:
• Leveraging your DITA content in a variety of output formats, such as PDF, XHTML, and HTML Help
• Customizing your DITA content processing
• Filtering your output for different audiences
Solving real world data problems with JerakiaCraig Dunn
This is the talk I gave at Config Management Camp 2016 in Ghent introducing Jerakia as a lookup tool that can be used in place of, or along side of hiera to solve some of the edge cases around data separation
Web services tutorial slides from my session at DPC 2012 in Amsterdam. In this 3-hour session we built the simplest possible service, and then extended it, looking at RPC, REST and SOAP along the way.
Accelerating analytics in the cloud with the Starburst Presto + Alluxio stackAlluxio, Inc.
Alluxio Tech Talk
January 21, 2020
Speakers:
Matt Fuller, Starburst
Dipti Borkar, Alluxio
With the advent of the public clouds and data increasingly siloed across many locations -- on premises and in the public cloud -- enterprises are looking for more flexibility and higher performance approaches to analyze their structured data.
Join us for this tech talk where we’ll introduce the Starburst Presto, Alluxio, and cloud object store stack for building a highly-concurrent and low-latency analytics platform. This stack provides a strong solution to run fast SQL across multiple storage systems including HDFS, S3, and others in public cloud, hybrid cloud, and multi-cloud environments. You’ll learn more about:
- The architecture of Presto, an open source distributed SQL engine
- How the Presto + Alluxio stack queries data from cloud object storage like S3 for faster and more cost-effective analytics
- Achieving data locality and cross-job caching with Alluxio regardless of where data is persisted
Solving Data Discovery Challenges at Lyft with Amundsen, an Open-source Metad...Databricks
Amundsen is the data discovery metadata platform that originated from Lyft which is recently donated to Linux Foundation AI. Since its open-sourced, Amundsen has been used and extended by many different companies within our community.
This presentation demonstrates how QueryPath can be used within Drupal to integrate web services and create rich mash-ups.
The "official" DrupalCon Paris video of this presentation can be found here: http://technosophos.com/content/querypath-mashups-and-web-services-video
A Day in the Life of a Druid Implementor and Druid's RoadmapItai Yaffe
Benjamin Hopp (Solutions Architect) @ Imply:
Druid is an emerging standard in the data infrastructure world, designed for high-performance slice-and-dice analytics (“OLAP”-style) on large data sets.
This talk is for you if you’re interested in learning more about pushing Druid’s analytical performance to the limit.
Perhaps you’re already running Druid and are looking to speed up your deployment, or perhaps you aren’t familiar with Druid and are interested in learning the basics.
Some of the tips in this talk are Druid-specific, but many of them will apply to any operational analytics technology stack.
The most important contributor to a fast analytical setup is getting the data model right.
The talk will center around various choices you can make to prepare your data to get best possible query performance.
We’ll look at some general best practices to model your data before ingestion such as OLAP dimensional modeling (called “roll-up” in Druid), data partitioning, and tips for choosing column types and indexes.
We’ll also look at how more can be less: often, storing copies of your data partitioned, sorted, or aggregated in different ways can speed up queries by reducing the amount of computation needed.
We’ll also look at Druid-specific optimizations that take advantage of approximations; where you can trade accuracy for performance and reduced storage.
You’ll get introduced to Druid’s features for approximate counting, set operations, ranking, quantiles, and more.
And we will finish with the latest and greatest Druid news, including details about the latest roadmap and releases.
Similar to Drupal Camp Berlin 2014 - Content Import in Drupal 7 Using Feeds (20)
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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/
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
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.
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
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
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.
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.
3. Agenda• What is Feeds?
• Key components / concepts
• 3rd part plugins
• Feeds Tamper
• Client cases
• Demos
• Ressources
• Questions
4. What is Feeds?• Flexible solution for importing data
• Easy to setup imports in no time
• Multiple simultaneous configurations (importers)
• UI for granular mapping of source and target
• Manually or scheduled import
• Stand-alone or content type for import
5. What is Feeds?• Formats: RSS, ATOM, CSV, OPML
• Data types: nodes, users, taxonomy terms
• Ctools plugins
• Features support
• Hooks / API
6. Key components● Fetcher:
○ Download, load or receive feed from a source
○ Standard: HTTP + upload
● Parser
○ Parse fetched source data
○ Standard: RSS/Atom, CSV, OPML, XML Sitemap
● Processor
○ Process the parsed data and store it in the target data type
○ Standard: Node, User, Taxonomy term
8. Feeds Tamper• Manipulate single fields before it is saved
• Examples:
○ Replace every instance of 'dog' with 'cat'.
○ Make every letter uppercase, lowercase, or capitalize every first letter.
○ Break a comma separated list of words into Taxonomy terms or a multivalued text field.
○ Combine separate 'firstname' and 'lastname' fields into one 'name' field.
○ Convert URL’s from relative to absolute.
• 20+ build in plugins for manipulation
• Custom tamper plugins using ctools
9. Client cases• Migration of nodes, files and taxonomy terms
• Import of departments and employees from local phone book.
• Import of events from external event system.
• Import of jobs / vacancies from HR system.
• Aggregation of multiple RSS feeds