The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
High Performance Hibernate JavaZone 2016Vlad Mihalcea
This document discusses high performance with Hibernate. It covers various topics related to improving performance such as connection providers, identifier generators, relationships, batching, fetching, and caching. The document provides metrics, comparisons, and best practices for each topic. It emphasizes the importance of performance and how even small improvements can significantly impact response times and throughput.
Brk3288 sql server v.next with support on linux, windows and containers was...Bob Ward
This document discusses Microsoft's plans to deliver SQL Server on Linux and other heterogeneous environments. Key points include:
- SQL Server will be available on Linux, Windows, and Docker containers, allowing choice of operating system. It will support multiple languages and tools.
- Microsoft is delivering more options in response to businesses adopting heterogeneous environments with various data types, languages, and platforms.
- The document outlines SQL Server's capabilities on Linux such as high availability, security, and tools/drivers available now or in development.
User defined partitioning is a new partitioning strategy in Treasure Data that allows users to specify which column to use for partitioning, in addition to the default "time" column. This provides more flexible partitioning that better fits customer data platform workloads. The user can define partitioning rules through Presto or Hive to improve query performance by enabling colocated joins and filtering data by the partitioning column.
Inside sql server in memory oltp sql sat nyc 2017Bob Ward
This document provides a high-level summary of In-Memory OLTP in SQL Server:
- In-Memory OLTP stores and processes transactional data entirely in memory using natively compiled stored procedures to avoid concurrency bottlenecks like locks and latches.
- Data is stored in memory-optimized tables using either a hash index or range index for fast lookup. Transactions are logged and written to checkpoint files for durability.
- The Hekaton engine handles all transaction processing in memory without locks by using techniques like multi-version concurrency control and lock-free data structures. Checkpoint files are used to reconstruct the database after a restart.
- Natively compiled stored procedures provide improved performance by
Experience sql server on l inux and dockerBob Ward
Microsoft SQL Server provides a full-featured database for Linux that offers high performance, security and flexibility across languages and platforms at a lower cost compared to other commercial databases. It has the most consistent data platform with industry-leading performance on Linux and Windows and supports machine learning and artificial intelligence capabilities. SQL Server on Linux allows customers to deploy the database on their choice of Linux distribution for both traditional and container-based workloads.
Gs08 modernize your data platform with sql technologies wash dcBob Ward
The document discusses the challenges of modern data platforms including disparate systems, multiple tools, high costs, and siloed insights. It introduces the Microsoft Data Platform as a way to manage all data in a scalable and secure way, gain insights across data without movement, utilize existing skills and investments, and provide consistent experiences on-premises, in the cloud, and hybrid environments. Key elements of the Microsoft Data Platform include SQL Server, Azure SQL Database, Azure SQL Data Warehouse, Azure Data Lake, and Analytics Platform System.
WLST is a scripting tool that can be used to manage Oracle WebLogic Server domains and instances. It has two modes - offline for configuring domains without a running server, and online for managing running servers. The document discusses using WLST offline to create domains from templates, and online to perform tasks like deployment, configuration, and monitoring of running servers through JMX.
This session shows an overview of the features and architecture of SQL Server on Linux and Containers. It covers install, config, performance, security, HADR, Docker containers, and tools. Find the demos on http://aka.ms/bobwardms
High Performance Computing - Cloud Point of Viewaragozin
This document discusses high performance computing in the cloud. It covers different types of workloads like I/O bound, CPU bound, and latency bound tasks. It also discusses handling task streams and structured batch jobs in the cloud. It proposes using techniques like worker pools, task queues, routing overlays, and task stealing for scheduling tasks. It discusses challenges around distributing large data sets across cloud resources and proposes solutions like caching data in memory grids. Finally, it argues that frameworks like Hadoop are not well suited for the cloud and proposes cloud-friendly alternatives like Peregrine and Spark.
WebLogic is experiencing an out of memory issue which is causing it to momentarily hang. When the WebLogic java process runs out of memory in either the Java heap or native heap, it logs an "OutOfMemory" error to the PIA_weblogic.log file. This usually occurs during times of high load on the PeopleSoft environment. To resolve it, the Java heap size needs to be increased using the -Xms and -Xmx Java parameters or more memory needs to be added to the server hardware. Monitoring tools can help identify when memory usage is high.
Sizing MongoDB on AWS with Wired Tiger-Patrick and Vigyan-FinalVigyan Jain
This document provides guidance on sizing MongoDB deployments on AWS for optimal performance. It discusses key considerations for capacity planning like testing workloads, measuring performance, and adjusting over time. Different AWS services like compute-optimized instances and storage options like EBS are reviewed. Best practices for WiredTiger like sizing cache, effects of compression and encryption, and monitoring tools are covered. The document emphasizes starting simply and scaling based on business needs and workload profiling.
Boost Development With Java EE7 On EAP7 (Demitris Andreadis)Red Hat Developers
JBoss EAP7 brings support for the most recent industry standards and technologies, including Java EE7, the latest edition of the premier enterprise development standard. This session will provide an overview of the major additions to Java EE7, and how your team can use these capabilities on the advanced EAP7 runtime to produce better applications with less code.
SQL Server In-Memory OLTP: What Every SQL Professional Should KnowBob Ward
Perhaps you have heard the term “In-Memory” but not sure what it means. If you are a SQL Server Professional then you will want to know. Even if you are new to SQL Server, you will want to learn more about this topic. Come learn the basics of how In-Memory OLTP technology in SQL Server 2016 and Azure SQL Database can boost your OLTP application by 30X. We will compare how In-Memory OTLP works vs “normal” disk-based tables. We will discuss what is required to migrate your existing data into memory optimized tables or how to build a new set of data and applications to take advantage of this technology. This presentation will cover the fundamentals of what, how, and why this technology is something every SQL Server Professional should know
For our eReader development project, we had to find a persistent storage for our JSON documents. After initial scanning we zeroed into two products DynamoDB and MongoDB. These slides take a deeper dive in the selection of our JSON data store.
Hekaton is the original project name for In-Memory OLTP and just sounds cooler for a title name. Keeping up the tradition of deep technical “Inside” sessions at PASS, this half-day talk will take you behind the scenes and under the covers on how the In-Memory OLTP functionality works with SQL Server.
We will cover “everything Hekaton”, including how it is integrated with the SQL Server Engine Architecture. We will explore how data is stored in memory and on disk, how I/O works, how native complied procedures are built and executed. We will also look at how Hekaton integrates with the rest of the engine, including Backup, Restore, Recovery, High-Availability, Transaction Logging, and Troubleshooting.
Demos are a must for a half-day session like this and what would an inside session be if we didn’t bring out the Windows Debugger. As with previous “Inside…” talks I’ve presented at PASS, this session is level 500 and not for the faint of heart. So read through the docs on In-Memory OLTP and bring some extra pain reliever as we move fast and go deep.
This session will appear as two sessions in the program guide but is not a Part I and II. It is one complete session with a small break so you should plan to attend it all to get the maximum benefit.
This document discusses using MongoDB as an agile NoSQL database for big data applications. It describes MongoDB's schema-less design, horizontal scaling, and replication capabilities which make it a good fit for frequently changing agile projects. The document includes examples of using MongoDB for an e-commerce catalog with dynamic product data and reviews from multiple sources.
This document summarizes a presentation about migrating to PostgreSQL. It discusses PostgreSQL's history and features, including its open source nature, performance, extensibility, and support for JSON, XML, and other data types. It also covers installation, common SQL features, indexing, concurrency control using MVCC, and best practices for optimization. The presentation aims to explain why developers may want to use PostgreSQL as an alternative or complement to other databases.
The presentation describes how to design robust solution for tagging search, how to use tagging for faceted search. Various architecture and data patterns are considered. We discuss relational databases like Oracle, full text search servers like Apache Solr. We will see how Oracle 18c features permit to use embedded faceted search.
Silicon Valley JUG - How to generate customized java 8 code from your databaseSpeedment, Inc.
The best code is the one you never need to write. Using code generation and automated builds you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it is handed over to a machine? In this tutorial, you will learn how to use open-source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you as a developer 100% control of the generated code. This will not only increase your productivity, but also help you build safer and more maintainable Java applications.
How to generate customized java 8 code from your databaseSpeedment, Inc.
Did you know that database classes, that require many lines of Java and SQL code, may be replaced with a single line of Java 8 code? In this tutorial session you will learn how to use standard Java 8 Streams as an alternative to traditional Object Relational Mappers (ORM). We will use the open-source tool Speedment to show how development speed can be increased and how the application code can be more concise and run faster.
The document provides an introduction to Typesafe Activator and the Play Framework. It discusses how Activator is a tool that helps developers get started with the Typesafe Reactive Platform and Play applications. It also covers some core features of Play like routing, templates, assets, data access with Slick and JSON, and concurrency with Futures, Actors, and WebSockets.
This document provides an overview of single page applications (SPAs) and AngularJS. It discusses why SPAs are useful, how they work, and key aspects of AngularJS like data binding, directives, routing, and dependency injection. Code samples are presented to demonstrate basic concepts like data binding, controllers, filters, and building an e-commerce application with routing and services. Future sessions are proposed to cover integration with Node.js backends, testing with Karma, and custom directives.
SenchaCon 2016 - How to Auto Generate a Back-end in MinutesSpeedment, Inc.
Connecting your JavaScript application to a database is tedious. Back-end developers spend hours modeling the database, securing connections, writing SQL, optimizing queries, deploying to a server, and fixing bugs. In this session, you'll learn how Ext Speeder gives your front-end team a tool to automatically generate a full back-end. In minutes, a REST API between a Sencha Ext JS Grid application and a relational database is created. This will save you a huge amount of time and also minimizes the risk of human error. Application time-to-market has never been shorter.
SenchaCon 2016 - How to Auto Generate a Back-end in MinutesMalin Weiss
Connecting your JavaScript application to a database is tedious. Back-end developers spend hours modeling the database, securing connections, writing SQL, optimizing queries, deploying to a server, and fixing bugs. In this session, you'll learn how Ext Speeder gives your front-end team a tool to automatically generate a full back-end. In minutes, a REST API between a Sencha Ext JS Grid application and a relational database is created. This will save you a huge amount of time and also minimizes the risk of human error. Application time-to-market has never been shorter.
SenchaCon 2016: How to Auto Generate a Back-end in Minutes - Per Minborg, Emi...Sencha
The document describes how Ext Speeder can auto-generate a complete backend in minutes by graphically connecting to a database, selecting tables and columns, and pressing "Generate". This generates code that provides a REST API and handles tasks like filtering, sorting, skipping, and caching data for high performance. Ext Speeder aims to reduce traditional backend development time from around 24 hours to under 1 hour.
This document discusses technologies for creating and maintaining web applications. It covers Ruby and the Rails framework. Ruby is designed to be programmer-focused rather than machine-focused, helping create dynamic and self-explained code. Rails enables quickly building web servers through conventions, reuse, single responsibility principles, and features that provide quick setup, deployment, and built-in scalability. The document also discusses front-end architecture with client-side logic, and Rails features for development, deployment, databases, assets, and multi-environment configuration.
The document discusses different workflows for using Entity Framework to access and manage data, including model first, database first, and code first approaches. It also covers using Entity Framework with WCF Data Services to expose data via OData endpoints. Key topics include entity data models, reverse engineering databases, defining mappings, and generating databases from code using migrations. Live demos are provided for database first and code first workflows as well as creating and consuming a WCF Data Services API.
JDD2015: Java Everywhere Again—with DukeScript - Jaroslav TulachPROIDEA
JAVA EVERYWHERE AGAIN—WITH DUKESCRIPT
For a long time, Java was perfect for creating cross-platform applications, but the advent of iPhone, iPad, and Android devices changed everything, resulting in a totally fragmented world. Catering to all these platform is troublesome and expensive. That’s why DukeScript was created: to make it easy to create cross-platform Java applications again. The goal of this hands-on lab is to create a cross-platform application from scratch that will run on iOS, Android, desktop, browser, and embedded devices such as the Raspberry Pi. You’ll learn about the Model-View-ViewModel (MVVM) architecture, which enables you to write and test business code totally independently of the view, and, finally, you’ll see it combined with a view to complete a working application.
IMPORTANT
Before conference, please follow the steps to prepare for the session:
- perform the Maven repository initialization by creating the archetype and building it as
described at DukeScript website
- also download NetBeans IDE (either latest beta or at least 8.0.2)
- Installing Android SDK rev. 19 or bringing own Mac Book with XCode installed can be also found beneficial
Masterin Large Scale Java Script ApplicationsFabian Jakobs
Writing large desktop-like web applications is a challenge. Adapting such an application to different markets, languages or brands is even more of a challenge. This talk shows how the open source JavaScript framework qooxdoo can be leveraged to build such a rich internet application. As a real-life example the free web mail client gmx.com is used. This talk discusses the development model, customization and deployment of such an application.
Learn how JavaScript applications of this size and complexity are fundamentally different from classic web applications, and what issues come up when building fast, multi-language, multi-brand JavaScript applications.
Whether you are building a mobile app or a web app, Apache Usergrid (incubating) can provide you with a complete backend that supports authentication, persistence and social features like activities and followers all via a comprehensive REST API — and backed by Cassandra, giving you linear scalability. This session will tell you what you need to know to be a Usergrid contributor, starting with the basics of building and running Usergrid from source code. You’ll learn how to find your way around the Usergrid code base, how the code for the Stack, Portal and SDKs and how to use the test infrastructure to test your changes to Usergrid. You’ll learn the Usergrid contributor workflow, how the project uses JIRA and Github to manage change and how to contribute your changes to the project. The session will also cover the Usergrid roadmap and what the community is currently working on.
- The document discusses AngularJS, a JavaScript framework for building web applications. It provides an overview of key AngularJS concepts like MVC architecture, data binding, directives, and services.
- Tools like Yeoman and Grunt are recommended for scaffolding AngularJS projects and automating tasks. The document emphasizes writing test-driven code and following AngularJS best practices for modularity and performance.
- Examples are provided to demonstrate how to write AngularJS controllers and compare simple versus more sophisticated applications built with the framework. Warnings are given about potential challenges like supporting older browsers and SEO.
Java script nirvana in netbeans [con5679]Ryan Cuprak
This document discusses using NetBeans as an IDE for JavaScript development. It provides an overview of NetBeans' features for JavaScript including syntax highlighting, code completion, debugging, support for frameworks like Angular and Node.js, and mobile development with Apache Cordova. It also demonstrates how to set up and configure NetBeans for common JavaScript tasks like adding libraries, using build tools like Grunt and Gulp, and setting up unit testing with Karma and Jasmine.
DevOps is changing today's software development world by helping us build better software, faster. However most of the knowledge and experience with DevOps is based around application software and ignores the database. We will examine how the concepts and principles of DevOps can be applied to database development by looking at both automated comparison analysis as well as migration script management. Automated building, testing, and deployment of database changes will be shown.
About the Presenter
Steve Jones is a Microsoft SQL Server MVP and has been working with SQL Server since version 4.2 on OS/2. After working as a DBA and developer for a variety of companies, Steve co-founded the community website SQLServerCentral.com in 2001. Since 2004, Steve has been the full-time editor of the site, ensuring it continues to be a great resource for SQL Server professionals. Over the last decade, Steve has written hundreds of articles about SQL Server for SQLServerCentral.com, SQL Server Standard magazine, SQL Server Magazine, and Database Journal.
Escaping the yellow bubble - rewriting Domino using MongoDb and AngularMark Leusink
Slides from my ICON UK 2014 session held on September 13, 2014 at IBM Southbank, London.
The session was an introduction to the MEAN stack (Mongo, Express, Angular and Node).
The MEAN stack allows you to build fast, responsive, and maintainable full-stack websites using JavaScript. The stack uses four innovative frameworks: MongoDB for rapid data access, Express for simplified web development, Angular for componentized and fluid UI, and Node for speed.
Not sure if the MEAN stack is for you? Then come to this free warm-up session. We give you a quick tour of all of the pieces of the stack. How to get you machine ready. And show you what it is like to build a site using it.
This session is for both front and backend developers. We'll show you how JavaScript, the world's most ubiquitous language, can help you to master the web.
This presentation is regarding on the Internship first industrial training at IJSE. This is a partial fulfillment of Industrial training module in Department of Electrical and Information Engineering,Faculty of Engineering, University of Ruhuna.
This session introduces tools that can help you analyze and troubleshoot performance with SharePoint 2013. This sessions presents tools like perfmon, Fiddler, Visual Round Trip Analyzer, IIS LogParser, Developer Dashboard and of course we create Web and Load Tests in Visual Studio 2013.
At the end we also take a look at some of the tips and best practices to improve performance on SharePoint 2013.
Similar to JavaOne2016 - How to Generate Customized Java 8 Code from Your Database [TUT4489] (20)
Web applications are becoming increasingly data intensive and complex. Yet, users demand a great user experience, including blazingly fast speeds, across many device types. In this talk, we will show you how you can dramatically improve the performance of your web applications by using Sencha Ext JS and Ext Speeder. You will learn how to: accelerate your back-end data requests up to 10x by leveraging sophisticated in-memory, object-oriented techniques, significantly improve application responsiveness without making any modifications to your client Ext JS application, and quickly get started with database acceleration in standard J2EE environments.
NYJavaSIG - Big Data Microservices w/ SpeedmentSpeedment, Inc.
Microservices solutions can provide fast access to large datasets by synchronizing SQL data into an in-JVM memory store and using key-value and column key stores. This allows querying terabytes of data in microseconds by mapping the data in memory and providing application programming interfaces. The solution uses periodic synchronization to initially load and periodically reload data, as well as reactive synchronization to capture and replay database changes.
JavaOne2016 - Microservices: Terabytes in Microseconds [CON4516]Speedment, Inc.
By leveraging memory-mapped files, Speedment and the Chronicle Engine supports large Java maps that easily can exceed the size of your server’s RAM.Because the Java maps are mapped onto files, these maps can be shared instantly between several microservice JVMs and new microservice instances can be added, removed, or restarted very quickly. Data can be retrieved with predictable ultralow latency for a wide range of operations. The solution can be synchronized with an underlying database so that your in-memory maps will be consistently “alive.” The mapped files can be tens of terabytes, which has been done in real-world deployment cases, and a large number of micro services can share these maps simultaneously. Learn more in this session.
DZone Java 8 Block Buster: Query Databases Using StreamsSpeedment, Inc.
Speedment Open Source is a new library that provides many interesting Java 8 features. It is written entirely in Java 8 from start. Speedment uses standard Streams for querying the database and thanks to that, you do not have to learn any new query API. You do not have to think at all about JDBC, ResultSet and other database specific things either.
Hear the talk to the article live from DZone Leader Per Åke Minborg. Read the full article here:
https://dzone.com/articles/java-8-query-databases-using-streams
Attend this session to learn how to rapidly develop blazingly fast cross-platform big data applications using Sencha and Speedment. Sencha enables developers to leverage the power of modern web technology (for example, HTML5, CSS, and JavaScript) to build universal web applications that can run on desktops, tablets, and smartphones. Speedment, on the other hand, enables developers to rapidly convert their large relational databases into in-memory Java objects (within Java Virtual Machine) that speed up data access by orders of magnitude.
Java one2015 - Work With Hundreds of Hot Terabytes in JVMsSpeedment, Inc.
Presentation Summary: By leveraging on memory mapped files, the Chronicle Engine supports large maps that easily can exceed the size of your server’s RAM, thus allowing application developers to create huge JVM:s where data can be obtained quickly and with predictable latency. The Chronicle Engine can be synchronized with an underlying database using Speedment so that your in-memory maps will be “alive” and change whenever data changes in the underlying database. Speedment can also automatically derive domain models directly from the database so that you can start using the solution very quickly. Because the Java Maps are mapped onto files, the maps can also be shared instantly between several JVM:s and when you restart a JVM, it may start very quickly without having to reload data from the underlying database. The mapped files can be hundreds of terabytes which has been done in real world deployment cases.
eXtreme Tuesday Club at Pivotal Labs ft. Speemdnet / San Francisco - SEP 2015Speedment, Inc.
This document summarizes Speedment, an open source Java library that allows developers to work with relational databases using Java 8 features like lambda expressions and streams.
Speedment was created in 2010 to simplify database access and increase productivity by avoiding object-relational mappers. It allows developers to focus on business logic rather than database queries. The Speedment API embraces Java 8 paradigms like streams, filters, and optionals to interact with database entities.
The document outlines how Speedment can be used to perform common database tasks like initialization, persistence, querying, and multi-threading in just a few lines of code without writing SQL. It also describes how Speedment is configured and concludes that it allows code generation
1) Accelerated ORM for Java 8 is an open source ORM solution called Speedment that keeps all data fully in-memory for extreme speed and uses reactive programming.
2) Speedment aims to improve developer productivity by allowing applications to work with relational databases as if they were object-oriented while avoiding the slowdowns of traditional ORMs.
3) Speedment's API is designed around Java 8 features like streams and uses code generation so developers can focus on their problem domain rather than database details.
SAP Open Source meetup/Speedment - Palo Alto 2015Speedment, Inc.
This document introduces Speedment ORM, an open source in-memory object-relational mapper (ORM) for Java 8. Speedment ORM keeps all data fully in-memory to provide extremely fast access and query times of O(1) by avoiding disk access. It uses code generation to reduce boilerplate code and allows applications to work with databases as if they were object-oriented. Speedment ORM can scale across multiple servers using technologies like Hazelcast. It aims to simplify database application development by hiding database details and allowing developers to focus on their problem domain using Java 8 features and a simple API.
The Rise of Supernetwork Data Intensive ComputingLarry Smarr
Invited Remote Lecture to SC21
The International Conference for High Performance Computing, Networking, Storage, and Analysis
St. Louis, Missouri
November 18, 2021
Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Em...Erasmo Purificato
Slide of the tutorial entitled "Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends" held at UMAP'24: 32nd ACM Conference on User Modeling, Adaptation and Personalization (July 1, 2024 | Cagliari, Italy)
Blockchain technology is transforming industries and reshaping the way we conduct business, manage data, and secure transactions. Whether you're new to blockchain or looking to deepen your knowledge, our guidebook, "Blockchain for Dummies", is your ultimate resource.
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc
Six months into 2024, and it is clear the privacy ecosystem takes no days off!! Regulators continue to implement and enforce new regulations, businesses strive to meet requirements, and technology advances like AI have privacy professionals scratching their heads about managing risk.
What can we learn about the first six months of data privacy trends and events in 2024? How should this inform your privacy program management for the rest of the year?
Join TrustArc, Goodwin, and Snyk privacy experts as they discuss the changes we’ve seen in the first half of 2024 and gain insight into the concrete, actionable steps you can take to up-level your privacy program in the second half of the year.
This webinar will review:
- Key changes to privacy regulations in 2024
- Key themes in privacy and data governance in 2024
- How to maximize your privacy program in the second half of 2024
Best Practices for Effectively Running dbt in Airflow.pdfTatiana Al-Chueyr
As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.
This webinar will cover a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code. We’ll walk through:
- Standard ways of running dbt (and when to utilize other methods)
- How Cosmos can be used to run and visualize your dbt projects in Airflow
- Common challenges and how to address them, including performance, dependency conflicts, and more
- How running dbt projects in Airflow helps with cost optimization
Webinar given on 9 July 2024
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdfNeo4j
Presented at Gartner Data & Analytics, London Maty 2024. BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Join this session to hear their story, the lessons they learned along the way and how their future innovation plans include the exploration of uses of EKG + Generative AI.
Support en anglais diffusé lors de l'événement 100% IA organisé dans les locaux parisiens d'Iguane Solutions, le mardi 2 juillet 2024 :
- Présentation de notre plateforme IA plug and play : ses fonctionnalités avancées, telles que son interface utilisateur intuitive, son copilot puissant et des outils de monitoring performants.
- REX client : Cyril Janssens, CTO d’ easybourse, partage son expérience d’utilisation de notre plateforme IA plug & play.
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
論文紹介:A Systematic Survey of Prompt Engineering on Vision-Language Foundation ...Toru Tamaki
Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip Torr "A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models" arXiv2023
https://arxiv.org/abs/2307.12980
YOUR RELIABLE WEB DESIGN & DEVELOPMENT TEAM — FOR LASTING SUCCESS
WPRiders is a web development company specialized in WordPress and WooCommerce websites and plugins for customers around the world. The company is headquartered in Bucharest, Romania, but our team members are located all over the world. Our customers are primarily from the US and Western Europe, but we have clients from Australia, Canada and other areas as well.
Some facts about WPRiders and why we are one of the best firms around:
More than 700 five-star reviews! You can check them here.
1500 WordPress projects delivered.
We respond 80% faster than other firms! Data provided by Freshdesk.
We’ve been in business since 2015.
We are located in 7 countries and have 22 team members.
With so many projects delivered, our team knows what works and what doesn’t when it comes to WordPress and WooCommerce.
Our team members are:
- highly experienced developers (employees & contractors with 5 -10+ years of experience),
- great designers with an eye for UX/UI with 10+ years of experience
- project managers with development background who speak both tech and non-tech
- QA specialists
- Conversion Rate Optimisation - CRO experts
They are all working together to provide you with the best possible service. We are passionate about WordPress, and we love creating custom solutions that help our clients achieve their goals.
At WPRiders, we are committed to building long-term relationships with our clients. We believe in accountability, in doing the right thing, as well as in transparency and open communication. You can read more about WPRiders on the About us page.
Best Programming Language for Civil EngineersAwais Yaseen
The integration of programming into civil engineering is transforming the industry. We can design complex infrastructure projects and analyse large datasets. Imagine revolutionizing the way we build our cities and infrastructure, all by the power of coding. Programming skills are no longer just a bonus—they’re a game changer in this era.
Technology is revolutionizing civil engineering by integrating advanced tools and techniques. Programming allows for the automation of repetitive tasks, enhancing the accuracy of designs, simulations, and analyses. With the advent of artificial intelligence and machine learning, engineers can now predict structural behaviors under various conditions, optimize material usage, and improve project planning.
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptxSynapseIndia
Your comprehensive guide to RPA in healthcare for 2024. Explore the benefits, use cases, and emerging trends of robotic process automation. Understand the challenges and prepare for the future of healthcare automation
Quality Patents: Patents That Stand the Test of TimeAurora Consulting
Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality.
Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality.
Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality.
Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank?
** Episode Overview **
In this first episode of our quality series, Kristen Hansen and the panel discuss:
⦿ What do we mean when we say patent quality?
⦿ Why is patent quality important?
⦿ How to balance quality and budget
⦿ The importance of searching, continuations, and draftsperson domain expertise
⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications
https://www.aurorapatents.com/patently-strategic-podcast.html
Mitigating the Impact of State Management in Cloud Stream Processing SystemsScyllaDB
Stream processing is a crucial component of modern data infrastructure, but constructing an efficient and scalable stream processing system can be challenging. Decoupling compute and storage architecture has emerged as an effective solution to these challenges, but it can introduce high latency issues, especially when dealing with complex continuous queries that necessitate managing extra-large internal states.
In this talk, we focus on addressing the high latency issues associated with S3 storage in stream processing systems that employ a decoupled compute and storage architecture. We delve into the root causes of latency in this context and explore various techniques to minimize the impact of S3 latency on stream processing performance. Our proposed approach is to implement a tiered storage mechanism that leverages a blend of high-performance and low-cost storage tiers to reduce data movement between the compute and storage layers while maintaining efficient processing.
Throughout the talk, we will present experimental results that demonstrate the effectiveness of our approach in mitigating the impact of S3 latency on stream processing. By the end of the talk, attendees will have gained insights into how to optimize their stream processing systems for reduced latency and improved cost-efficiency.
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JavaOne2016 - How to Generate Customized Java 8 Code from Your Database [TUT4489]
1. Tutorial: How to Generate Customized Java 8
Code from Your Database
Per Minborg
CTO, Speedment, Inc
Emil Forslund
Developer, Speedment, Inc.
2. Every Decision a Developer Makes is a
Trade-off
The best code is
no code at all
3. Using Code Generation
• Makes the code efficient
and short
• Modifications are done
once and applied
everywhere
• Minimizes errors
• “DRY” (Don’t Repeat
Yourself) vs. ”WET” (We
Enjoy Typing)
• “Code your code”
But how can we control the generated code?
4. About Us
Per Minborg
• Founder of several IT companies
• Lives in Palo Alto
• 20 years of Java experience
• 15+ US patents
• Speaker at Java events
• Blog: Minborg’s Java Pot
Emil Forslund
• Java Developer
• Lives in Palo Alto
• 8 years of Java
experience
• Speaker at Java events
• Blog: Age of Java
Spire
• Speedment Open Source mascot
• Lives on GitHub
• 1.5 years of mascot experience
5. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
6. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
7. Do You Recognize This Code?
Class.forName("org.postgresql.Driver");
try (final Connection conn = DriverManager.getConnection(
"jdbc:postgresql://hostname:port/dbname",
"username",
"password")) {
// Database Logic Here...
}
8. Why Creating DB-Apps is So Time
Consuming
• Even trivial database operations require a
lot of boilerplate code
• Mixing SQL and Java is error-prone
• ORMs require you to write annotated
POJOs for every table
• Creating even a simple DB app can take
hours
9. Open-Source Project Speedment
• Stream ORM Java toolkit and
runtime
• Generate domain-model from the
database
• No need for complicated
configurations or setup
• All operations are type-safe
• Data is accessed using Java 8
Streams
• Business friendly Apache 2-
license
11. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
14. So How Do the Generated Code Work?
• Code is organized based on database structure
• Hash-sums make sure user changes are not overwritten
If the DB structure changes, the code is
updated with the press of a button
15. Entities, Managers and Applications
• An Entity represents a row in a table
• Is a POJO
• Customer
• CustomerImpl
• A Manager represents a table
• Responsible for the CRUD operations
• CustomerManager
• CustomerManagerImpl
• An Application represents the entire project
• Responsible for configuration and settings
• SalesApplication
• SalesApplicationBuilder
16. Querying the Database using Streams
• Queries are expressed
using Java 8 streams
• Streams are analyzed to
produce high-performance
queries
17. Expressing Queries as Streams
customers.stream()
.filter(Customer.REGION.equal(Region.NORTH_AMERICA))
.filter(Customer.REGISTERED.greaterOrEqual(startOfYear))
.count();
Standard Stream
API
Generated Enum
Constants
Only 1 value is loaded from
DB
Full Type-Safety
SELECT COUNT('id') FROM 'customer'
WHERE 'customer'.'region' = ‘North America’
AND 'customer'.'registered' >= ‘2016-01-01’;
18. Querying the Database using Streams
SELECT * FROM 'customer'
REGION.equal(NORTH_AMERICA)
REGISTERED.greaterOrEqual(2016-01-01)
count()
Sourc
e
Filter
Filter
Term.
Pipeline
19. Querying the Database using Streams
SELECT * FROM 'customer'
WHERE 'customer'.'region' = ‘North America’
REGION.equal(NORTH_AMERICA)
REGISTERED.greaterOrEqual(2016-01-01)
count()
Sourc
e
Filter
Filter
Term.
Pipeline
20. Querying the Database using Streams
SELECT * FROM 'customer'
WHERE 'customer'.'region' = ‘North America’
AND 'customer'.'registered' >= ‘2016-01-01’;
REGISTERED.greaterOrEqual(2016-01-01)
count()
Sourc
e
Filter
Term.
Pipeline
21. Querying the Database using Streams
SELECT COUNT('id') FROM 'customer'
WHERE 'customer'.'region' = ‘North America’
AND 'customer'.'registered' >= ‘2016-01-01’;
count()
Sourc
e
Term.
Pipeline
22. Querying the Database using Streams
SELECT COUNT('id') FROM 'customer'
WHERE 'customer'.'region' = ‘North America’
AND 'customer'.'registered' >= ‘2016-01-01’;
Sourc
e
Pipeline
23. Expressing Queries as Streams
// Gets the second page of customers in North America
// sorted by name in the form of a JSON array
“[“+
customers.stream()
.filter(REGION.equal(Region.NORTH_AMERICA))
.sorted(NAME.comparator())
.skip(10)
.limit(10) // JVM from here…
.map(JsonEncoder.allOf(customers)::apply)
.collect(joining(“, ”))
+”]”;
24. Expressing Queries as Streams
// Supports parallelism on custom executors
// with full control of thread work item layout
customers.stream()
.parallel()
.filter(REGION.equal(Region.NORTH_AMERICA))
.forEach(expensiveOperatation());
26. Step 1: Getting Speedment using Maven
<plugin>
<groupId>com.speedment</groupId>
<artifactId>speedment-maven-plugin</artifactId>
<version>3.0.0-EA</version>
<dependencies>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
</dependencies>
</plugin>
Generate source files based on database
The JDBC connector to use
27. Step 2: Initializing Speedment
SalesApplication app = new SalesApplicationBuilder()
.withPassword("qwerty")
.build();
CustomerManager customers = app.getOrThrow(CustomerManager.class);
These classes are generated
automatically
Instance is configured using Builder-
pattern
A manager class is generated for every database table
28. Step 3: Querying
Region fromWhere = Region.NORTH_AMERICA;
Instant fromWhen = Instant.parse("2016-01-01");
long count = customers.stream()
.filter(Customer.REGION.equal(fromWhere))
.filter(Customer.REGISTERED.greaterOrEqual(fromWhen))
.count();
32. Live Demo: Speedment
• Generate Domain Model
• Write Java Stream that:
• Determine the ID of a certain city
• Alphabetical list of last names of
salespersons in that city
• Execute
33. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
34. Controlling the Code Generation
• So far we have queried a
database with streams
• We have used code generation
to create entities and managers
• Can it be used for more?
35. What is Available out of the Box?
• MVC oriented code generation
• Modular design
• Database domain model
• JSON configuration (DSL)
• Java language namer
• Translator and TranslatorDecorator
• Maven goals
• Type mappers
36. MVC Oriented Code Generation
• Model
• File, Class, Interface, Enum, Field, Method, Constructor,
Type, Generic, Annotation, …
• View
• Renders a model to Java (or another language)
• Set code style using custom views
• Control
• AutoImport, AutoEquals, AutoJavadoc, SetGetAdd, FinalParameters
• Write custom controllers to automate recurring tasks
37. MVC Oriented Code Generation
• Separation of concerns
• Code generation is type safe
• Catch errors compile time
• Discover methods directly in the IDE
• Reuse code segments and controllers
41. Java Language Namer
• Camel caser: converts from “some_db_name” to
“someDbName”
• Java naming conventions: user, User and USER
• Detects keywords like “final”,”static” and escapes them
• Detects collisions
• Pluralizer: bag → bags, entity → entities, fish → fish
42. Translator and TranslatorDecorator
• Translator
• Renders a DB entity like a Table to a new Class or an Interface
• TranslatorDecorator
• Modifies an existing Class or Interface
43. Maven Goals
• speedment:tool
• Launches the graphical tool
• Allows customization of configuration model
• Code generation
• speedment:generate
• Code generation without launching the tool
• speedment:reload
• Reloads database metadata without launching the tool
• speedment:clear
• Removes all the generated classes (except manual changes) without launching the
tool
44. Type Mappers
• Controls how columns are implemented
• Runtime conversion between Database and Java types
java.sql.Timestamp long
45. Generation vs. Templates
• Separation of concerns
• Easily change code style
• Minimize maintenance
• Maximize reusability
46. Generate a New Custom Class
1. Create a new Translator
2. Model how the new class
should look
3. Define a Plugin Class
4. Include it in project pom.xml
Example: Generate a Point class
47. Step 1: Create a New Translator Class
public class PointTranslator extends
AbstractJavaClassTranslator<Project, Class> {
public final static TranslatorKey<Project, Class> POINT_KEY =
new TranslatorKey.of(“generated_point", Class.class);
public PointTranslator(Project document) { super(document, Class::of); }
@Override
protected Class makeCodeGenModel(File file) {
return newBuilder(file, getClassOrInterfaceName())
.forEveryProject((clazz, project) -> {
// Generate Content Here
}).build();
}
@Override
protected String getClassOrInterfaceName() { return ”Point"; }
@Override
protected String getJavadocRepresentText() { return "A 2-dimensional coordinate."; }
}
Every translator is identified by a
TranslatorKey
Name of generated class
Javadoc
Called every time the translator is invoked
forEvery(Project|Dbms|Schema|Table|Column|
…)
49. Step 3: Define a Plugin Class
public class PointPlugin {
@ExecuteBefore(RESOLVED)
protected void install(CodeGenerationComponent codeGen) {
codeGen.put(
Project.class,
PointTranslator.POINT_KEY,
PointTranslator::new
);
}
}
The key defined earlier
Will execute when Speedment is
being initialized
How the translator is constructed
50. Step 4: Include it in Project pom.xml
<plugin>
<groupId>com.speedment</groupId>
<artifactId>speedment-maven-plugin</artifactId>
<version>3.0.0-EA</version>
<dependencies>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
<dependency>
<groupId>com.example</groupId>
<artifactId>point-plugin</artifactId>
<version>1.0.0-SNAPSHOT</version>
</dependency>
</dependencies>
<configuration>
<components>
<component>com.example.pointplugin.PointPlugin</component>
</components>
</configuration>
</plugin>
This tells Speedment to load the plugin
Make sure our plugin project is on the classpath
51. Execute
/**
* A 2-dimensional coordinate.
* <p>
* This file is safe to edit. It will not be overwritten by
the code generator.
*
* @author company
*/
public class Point {
private final int x;
private final int y;
public Point(int x, int y) {
this.x = x;
this.y = y;
}
public int getX() {
return x;
}
public int getY() {
return y;
}
The following file is generated: public int hashCode() {
int hashCode = 31;
hashCode += 41 * x;
hashCode += 41 * y;
return hashCode;
}
public Boolean equals(Object other) {
if (this == other) return true;
else if (other == null) return false;
else if (!(other instanceof Point)) {
return false;
}
final Point point = (Point) other;
return x == point.x && y == point.y;
}
public String toString() {
return new StringBuilder(“Point{”)
.append(“x: “).append(x).append(“, “)
.append(“y: “).append(y).append(“}”);
}
}
52. A More Concrete Example
1. Create a new Translator
2. Model how the new class
should look
3. Define a Plugin Class
4. Include it in project pom.xml
Example: Generate an Enum of
tables in the database
53. Step 1: Create a New Translator Class
public class TableEnumTranslator extends
AbstractJavaClassTranslator<Project, Enum> {
public final static TranslatorKey<Project, Enum> TABLES_ENUM_KEY =
new TranslatorKey.of(“tables_enum", Enum.class);
public TableEnumTranslator(Project document) { super(document, Enum::of); }
@Override
protected Enum makeCodeGenModel(File file) {
return newBuilder(file, getClassOrInterfaceName())
.forEveryProject((clazz, project) -> {
// Generate Content Here
}).build();
}
@Override
protected String getClassOrInterfaceName() { return ”Tables"; }
@Override
protected String getJavadocRepresentText() { return "An enumeration of tables in the database."; }
}
Every translator is identified by a
TranslatorKey
Name of generated class
Javadoc
Called every time the translator is invoked
forEvery(Project|Dbms|Schema|Table|Column|
…)
55. Step 3: Define a Plugin Class
public class TableEnumPlugin {
@ExecuteBefore(RESOLVED)
protected void install(CodeGenerationComponent codeGen) {
codeGen.put(
Project.class,
TableEnumTranslator.TABLES_ENUM_KEY,
TableEnumTranslator::new
);
}
}
56. Step 4: Include it in Project pom.xml
<plugin>
<groupId>com.speedment</groupId>
<artifactId>speedment-maven-plugin</artifactId>
<version>3.0.0-EA</version>
<dependencies>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
<dependency>
<groupId>com.example</groupId>
<artifactId>table-enum-plugin</artifactId>
<version>1.0.0-SNAPSHOT</version>
</dependency>
</dependencies>
<configuration>
<components>
<component>com.example.tableenumplugin.TableEnumPlugin</component>
</components>
</configuration>
</plugin>
This tells Speedment to load the plugin
Make sure our plugin project is on the
classpath
57. Execute
/**
* An enumeration of tables in the database.
* <p>
* This file is safe to edit. It will not be overwritten by the code generator.
*
* @author company
*/
enum Tables {
CITY, SALESPERSON;
}
The following file is generated:
58. Generate all the Things
• Gson Adapters
• Spring Configuration Files
• REST Controllers
• and much more…
59. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
60. Add New Method to Existing Classes
• So far we have
• Queried a database with generated
classes
• Generated a custom class
• How do we modify the existing
generation of classes?
61. Add New Method to Existing Classes
• Fit Into Existing Class Hierarchy
• Change Naming Conventions
• Optimize Internal Implementations
• Add Custom Methods
62. Add New Method to Existing Classes
Example: Add a getColumnCount
method to generated managers
1. Create a new
TranslatorDecorator class
2. Write code generation logic
3. Add it to Speedment
63. Step 1: Creating a New Decorator Class
public class ColumnCountDecorator implements TranslatorDecorator<Table, Interface> {
@Override
public void apply(JavaClassTranslator<Table, Interface> translator) {
translator.onMake(builder -> {
builder.forEveryTable((intrf, table) -> {
// Code generation logic goes here
});
});
}
}
64. Step 2: Write Code Generation Logic
int columnCount = table.columns().count();
intrf.add(Method.of("getColumnCount", int.class)
.default_()
.set(Javadoc.of("Returns the number of columns in this table.")
.add(RETURN.setValue("the column count"))
)
.add("return " + columnCount + ";")
);
65. Step 3: Add it to Speedment
public final class TableEnumPlugin {
@ExecuteBefore(RESOLVED)
protected void install(CodeGenerationComponent codeGen) {
codeGen.put(
Project.class,
TableEnumTranslator.TABLES_ENUM_KEY,
TableEnumTranslator::new
);
codeGen.add(
Table.class,
StandardTranslatorKey.GENERATED_MANAGER,
new ColumnCountDecorator()
);
}
}
Modify an existing translator key
Our new decorator
The same plugin class as we
created earlier
67. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
69. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
70. Additional Features
• Add GUI Tool components for
custom configuration
• Extend the JSON DSL
dynamically with plugins
• Automate your build
environment with Maven
• Add custom data type
mappers
71. Additional Features
• Plugin a custom namer
• Generate classes that are related to other domain models
• Generate classes for other languages
• Style the GUI Tool
73. Agenda
• Problem Description
• Code Generation in Database Applications
• How Does it Work?
• Hands on Demo
• Controlling the Code Generation
• Generate Custom Classes
• Add new Method to Existing Classes
• Hands on Demo
• Additional Features
• Real World Examples
• Questions & Answers
74. In-JVM-Memory Data Store
• Alternative stream source
• Uses code generation
• Optimized serializers for
offheap storage
• No changes to user-written
code
• 10-100x faster queries