Spring Data is a high level SpringSource project whose purpose is to unify and ease the access to different kinds of persistence stores, both relational database systems and NoSQL data stores.
Java and Spring Data JPA: Easy SQL Data Access
Abstract
Presenter: Miya W. Longwe, MBA, MSE, Tech Lead, Staples, Inc, Framingham MA 01702
Accessing data repositories in various applications programming languages typically involves writing of tedious boilerplate lines of code. Some application development frameworks such as Spring have tried to make the experience more succinct by providing abstraction layers such as HibernateTemplate and JdbcTemplate, etc. Despite these APIs, the developers still spend a lot time writing repetitive code than concentrating on implementing business requirements. Developers at Spring, led by Oliver Gierke, introduced Spring Data JPA which “aims to significantly improve the implementation of data access layers by reducing the effort to the amount that's actually needed. As a developer you write your repository interfaces, including custom finder methods, and Spring will provide the implementation automatically”.
Spring Data JPA provides a powerful, out-of-the-box alternative to creating your own DAO framework. You declare custom repository operations on an interface, and the framework generates dynamic implementations (not code generation) automatically, based on conventions around method names. As part of the presentation, we'll also review a demo to look at Spring Java configuration (as opposed to XML configuration), and investigate the @Profile annotation – configuration details which may make life a bit easier in various ways when setting up unit testing of our repository classes, using out-of-the-box alternative to creating DAO framework, how to create custom repositories, pagination and support for custom queries among other features.
Presenter's Bio
Miya W. Longwe is a Senior Software Engineer and Tech Lead at Staples, Inc. where he is currently working on an initiative to re-platform the company’s ecommerce architecture to offer platform-driven, modular products that can be quickly customized, enhanced, and branded as needed.
Miya has been a software professional since 1997. His 16 years software development career includes working for large companies to small startups, building solutions for enterprises and consumers, working with a broad range of technologies.
Miya Longwe is a hands-on java developer. He believes that in order to be a relevant and effective software developer one needs to remain a deeply knowledgeable, up-to-date, and productive software developer. His research interests include model-driven engineering, domain specific languages, test driven development and project risk management.
Miya graduated from the University of Malawi (Lilongwe, Malawi) and has an MBA from the University of Wales Cardiff Business School (Wales, UK) and a Masters in Software Engineering from Brandeis University (MA, USA).
Occasionally, Miya can be spotted fishing the banks of the south shore (MA) with his two boys, William and Daniel.
Spring Data is a high level SpringSource project whose purpose is to unify and ease the access to different kinds of persistence stores, both relational database systems and NoSQL data stores.
Java and Spring Data JPA: Easy SQL Data Access
Abstract
Presenter: Miya W. Longwe, MBA, MSE, Tech Lead, Staples, Inc, Framingham MA 01702
Accessing data repositories in various applications programming languages typically involves writing of tedious boilerplate lines of code. Some application development frameworks such as Spring have tried to make the experience more succinct by providing abstraction layers such as HibernateTemplate and JdbcTemplate, etc. Despite these APIs, the developers still spend a lot time writing repetitive code than concentrating on implementing business requirements. Developers at Spring, led by Oliver Gierke, introduced Spring Data JPA which “aims to significantly improve the implementation of data access layers by reducing the effort to the amount that's actually needed. As a developer you write your repository interfaces, including custom finder methods, and Spring will provide the implementation automatically”.
Spring Data JPA provides a powerful, out-of-the-box alternative to creating your own DAO framework. You declare custom repository operations on an interface, and the framework generates dynamic implementations (not code generation) automatically, based on conventions around method names. As part of the presentation, we'll also review a demo to look at Spring Java configuration (as opposed to XML configuration), and investigate the @Profile annotation – configuration details which may make life a bit easier in various ways when setting up unit testing of our repository classes, using out-of-the-box alternative to creating DAO framework, how to create custom repositories, pagination and support for custom queries among other features.
Presenter's Bio
Miya W. Longwe is a Senior Software Engineer and Tech Lead at Staples, Inc. where he is currently working on an initiative to re-platform the company’s ecommerce architecture to offer platform-driven, modular products that can be quickly customized, enhanced, and branded as needed.
Miya has been a software professional since 1997. His 16 years software development career includes working for large companies to small startups, building solutions for enterprises and consumers, working with a broad range of technologies.
Miya Longwe is a hands-on java developer. He believes that in order to be a relevant and effective software developer one needs to remain a deeply knowledgeable, up-to-date, and productive software developer. His research interests include model-driven engineering, domain specific languages, test driven development and project risk management.
Miya graduated from the University of Malawi (Lilongwe, Malawi) and has an MBA from the University of Wales Cardiff Business School (Wales, UK) and a Masters in Software Engineering from Brandeis University (MA, USA).
Occasionally, Miya can be spotted fishing the banks of the south shore (MA) with his two boys, William and Daniel.
As with most Java technologies, building applications with JPA or JAXB is straightforward, but performance tuning is something that takes experience. In this session we will identify key performance tuning opportunities and techniques and how the tooling provided within Eclipse and in EclipseLink can be used to identify issues and configure solutions. We will discuss optimizing the cache, queries and mappings along with optimization features available for distributed applications.
A SERIAL COMPUTING MODEL OF AGENT ENABLED MINING OF GLOBALLY STRONG ASSOCIATI...ijcsa
The intelligent agent based model is a popular approach in constructing Distributed Data Mining (DDM) systems to address scalable mining over large scale and ever increasing distributed data. In an agent based
distributed system, variety of agents coordinate and communicate with each other to perform the various
tasks of the Data Mining (DM) process. In this study a serial computing mode of a multi-agent system
(MAS) called Agent enabled Mining of Globally Strong Association Rules (AeMGSAR) is presented based
on the serial itinerary of the mobile agents. A Running environment is also designed for the implementation and performance study of AeMGSAR system.
To view recording of this webinar please use below URL
http://wso2.com/library/webinars/2015/11/wso2-product-release-webinar-wso2-complex-event-processor-4.0/
In this webinar, Lasantha and Suho will discuss the following key features and improvements in detail:
Integrating WSO2 CEP with Apache Storm to achieve distributed real-time stream processing
Key features of the latest version of Siddhi
New transports that enhances integration capabilities of WSO2 CEP
Creating query templates using execution manager
Using the analytics dashboard to visualize results in real-time
NET Systems Programming Learned the Hard Way.pptxpetabridge
What is a thread quantum and why is it different on Windows Desktop and Windows Server? What's the difference between a blocking call and a blocking flow? Why did our remoting benchmarks suddenly drop when we moved to .NET 6? When should I try to write lock-free code? What does the `volatile` keyword mean?
Welcome to the types of questions my team and I are asked, or ask ourselves, on a regular basis - we're the makers of Akka.NET, a high performance distributed actor system library and these are the sorts of low-level questions we need to answer in order to build great experiences for our own users.
In this talk we're going to learn about .NET systems programming, the low level components we hope we can take for granted, but sometimes can't. In particular:
- The `ThreadPool` and how work queues operate in practice;
- Synchronization mechanisms - including `lock`-less ones;
- Memory management, `Span<T>`, and garbage collection;
- `await`, `Task`, and the synchronization contexts; and
- Crossing user-code and system boundaries in areas such as sockets.
This talk will help .NET developers understand why their code works the way it does and what to do in scenarios that demand high performance.
Back-2-Basics: .NET Coding Standards For The Real World (2011)David McCarter
Revamped for 2011 (90% new material), this session will guide any level of programmer to greater productivity by providing the information needed to write consistent, maintainable code. Learn about project setup, assembly layout, code style, defensive programming and much, much more. Code tips are included to help you write better, error free applications. Lots of code examples in C# and VB.NET. This session is based off my latest book, David McCarter's .NET Coding Standards.
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
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
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
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.
8. Architectural tiers of a typical JPA-based application User Application OpenJPA Standard JPA API JDBC API 400 million records
9. Architectural tiers of a Slice-based application User Application OpenJPA Standard JPA API JDBC API Slice OpenJPA is a plugabble platform User-defined Data Distribution Policy 4x100 million records
10. Separate Persistence Unit configured to partitioned databases C A [1] D A Unit A C A [2] C B [1] D B Unit B C B [2] C C [1] D C Unit C C C [2]
11. Same persistence unit switches contexts to partitioned databases C A [1] D A Persistence Unit C A [2] C C [2] C C [1] C B [2] C B [1] D B D C
12. Same persistence unit connected to partitioned databases C[1] D A Persistence Unit C[2] D B D C
13. Features of Slice Slice-based User Application OpenJPA Standard JPA API JDBC API Slice No changes to Application code User-defined Data Distribution Policy Flexible per-Slice Configuration Parallel Query Execution Heterogeneous Databases Master-based Sequence Targeted Query No changes to Domain Model User-defined Query Target Policy No changes to Database Schema 4x100 millon records
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19. Distribution Policy decides target slice for each instance public interface DistributionPolicy { /** * Decide the name of the slice where the given persistent * instance would be stored. * * @param pc The newly persistent or to-be-merged object. * @param slices name of the configured slices. * @param context persistence context managing the given instance. * * @return identifier of the slice. This name must match one of the * configured slice names. * @see DistributedConfiguration#getSliceNames() */ String distribute ( Object pc, List<String> slices, Object context); } Slice runtime will call this method while persisting or merging a root instance. The instance and its persistent closure will be stored in the returned slice.
20. Details on Distribution Policy a b em.persist(a); // or em.merge(a); persistence context MyPolicy.distribute(a,…) { return “One” ; } One One < property name=" openjpa.slice.DistributionPolicy " value=“ acme.org.MyPolicy "/> Slice attaches moniker to managed instance as it enters a persistence context Slice runtime calls User Application CascadeType.PERSIST CascadeType.MERGE c One
23. Instances that violate persistent closure must be replicated Stock CSCO Ask-152 Bid-153 Trader-1 Trader-2 Trade-15 Stock GS Ask-210 Bid-211 Trader-7 Trader-1 Trade-21 slice.One slice.Two Trader-1 will violate collocation constraint and must be replicated across all slices. Data partitioned by Stock sectors
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25. Replication Policy public interface ReplicationPolicy { /** * Decide the name of the slices where the given persistent * instance would be replicated. * * @param pc The newly persistent or to-be-merged object. * @param slices name of the configured slices. * @param context persistence context managing the given instance. * * @return identifier(s) of the slice. Each name must match one of the * configured slice names. * @see DistributedConfiguration#getSliceNames() */ String[] replicate ( Object pc, List<String> slices, Object context); } Slice runtime will call this method while persisting any replicated instance.
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27. Query Target Policy decides target slice for each query public interface QueryTargetPolicy { /** * Decide the name of the slice(s) where the given query * will be executed. * * @param query The query string to be executed. * @param params the bound parameters of the query. * @param language the language of the query * @param slices name of the configured slices * @param context persistence context executing the query. * * @return identifier of the target slices. Null value implies * all configured slices. */ String[] getTargets ( String query, Map params, String language, List<String> slices, Object context); } Slice runtime will call this method for every query. Default policy targets all available slices.
28. Intrusive way to control target slices for a query EntityManager em = …; String jpql = " SELECT p FROM Person p where p.name=:name ”; TypedQuery <Person> query1 = em.createQuery(jpql, Person. class ); // Set a single slice as query target query1.setHint( SlicePersistence.HINT_TARGET , “ One "); List < Person > result1 = query1.setParameter(“ name ”, “ XYZ ”) .getResultList(); TypedQuery <Person> query2 = em.createQuery(jpql , Person. class ); // Set multiple slices as query targets query2.setHint( SlicePersistence.HINT_TARGET , Arrays.asList( new String []{“ One “,” Two ”}); List < Person > result2 = query2.setParameter(“ name ”, “ ABC ”) .getResultList();
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38. META-INF/persistence.xml configures a persistence unit <? xml version=" 1.0 " encoding=" UTF-8 "?> < persistence xmlns=" http://java.sun.com/xml/ns/persistence " xmlns:xsi=" http://www.w3.org/2001/XMLSchema-instance " version=" 1.0 " xsi:schemaLocation=" http://java.sun.com/xml/ns/persistence http://java.sun.com/xml/ns/persistence/persistence_2_0.xsd "> < persistence-unit name=" test “ transaction=“ RESOURCE_LOCAL ”> < provider > org.apache.openjpa.persistence.PersistenceProviderImpl </ provider > < class > domain.EntityA </ class > < class > domain.EntityB </ class > < properties > < property name=" openjpa.ConnectionDriverName " value=" com.mysql.jdbc.Driver "/> < property name=" openjpa.ConnectionURL " value=" jdbc:mysql://localhost/test "/> < property name=" openjpa.jdbc.SynchronizeMappings " value=" buildSchema "/> < property name=" openjpa.Log " value=" SQL=TRACE "/> </ properties > </ persistence-unit > List of known Persistent types Vendor-specific configuration Governed by XML Schema JPA Provider is pluggable Identified by Unit Name
57. An example data distribution policy /** * This distribution policy determines the sector of the stock and * picks the slice at ordinal index of the enumerated Sector. */ public class SectorDistributionPolicy implements DistributionPolicy { public String distribute( Object pc, List < String > slices, Object context) { Stock stock = null ; if (pc instanceof Tradable ) { stock = (( Tradable )pc).getStock(); } else if (pc instanceof Stock ) { stock = ( Stock )pc; } else if (pc instanceof Trade ) { stock = (( Trade )pc).getStock(); } else { throw new IllegalArgumentException(“ No policy for “ + pc); } return stock != null ? slices.get(stock.getSector().ordinal()) : null ; } }
58. An example query target policy public static final String MATCH_BID = " select new Match(a,b) from Ask a, Bid b " + " where b = :bid and a.stock.symbol = b.stock.symbol " + " and a.price <= b.price and a.volume >= b.volume " + " and NOT (a.seller = b.buyer) “ + “ and a.trade is NULL and b.trade is NULL "; public class SectorBasedQueryTargetPolicy implements QueryTargetPolicy { public String [] getTargets( String query, Map < Object , Object > params, String language, List < String > slices, Object context) { Stock stock = null ; if (TradingService. MATCH_BID .equals(query)) { stock = ((Tradable)params.get(" bid ")).getStock(); return new String[]{slices.get(stock.getSector().ordinal())}; } return null ; } }