Hibernate OGM provides JPA support for NoSQL databases like Infinispan. It allows using the familiar JPA programming model while storing data in a flexible NoSQL database. Hibernate OGM acts as a JPA front-end that handles CRUD operations and basic queries, persisting objects to Infinispan. The goal is to encourage new data usage patterns with volume and types while using a familiar Java environment.
Real World Big Data, 100,000 transactions a second in a NoSQL DatabaseEric Bloch
This talk is about a Big Data use case requiring 100K transactions per second. It briefly cover the architecture of MarkLogic, an enterprise-grade NoSQL Document Database and why it's ideal for this case. The talk concludes with a detailed discussion of the techniques used, along with related performance analyses, to achieve the requirements.
Introducing Hibernate OGM: porting JPA applications to NoSQL, Sanne Grinovero...OpenBlend society
Hibernate OGM allows developers to use JPA to access NoSQL databases like Infinispan. It stores entities as tuples in the key-value store and uses Hibernate Search to index entities and support JP-QL queries. While still early, it aims to reuse familiar Hibernate concepts while taking advantage of NoSQL databases' flexibility, high availability, and scalability. It currently supports Infinispan but contributions are welcome to integrate other NoSQL databases.
View Barry Morris' presentation from the October 23 edition of The Briefing Room, entitled: “The Perfect Storm: The Impact of Analytics, Big Data and Cloud.” In this presentation, Morris introduces the NuoDB solution, an asynchronous, peer-to-peer database, specifically designed to meet 21st century database requirements. NuoDB is 100% SQL compliant and 100% ACID but scales elastically in the cloud or on-premise.
Big data hadoop-no sql and graph db-finalramazan fırın
This document discusses big data, Hadoop, NoSQL databases, and graph databases. It provides an overview of these topics and outlines potential uses for a telecommunications company, such as using big data to prevent customer churn, offer customer-specific campaigns, and get more customers. The document includes definitions and examples of key concepts like Hadoop, MapReduce, NoSQL databases, and the graph database Neo4j. It also summarizes trends in big data and provides examples of how telecom companies can analyze call detail records, model networks, and manage master customer data using these technologies.
Slides from workshop held on 12/14 in Asbury Park, NJ
http://www.meetup.com/Jersey-Shore-Tech/events/148118762/?gj=ro2_e&a=ro2_gnl&rv=ro2_e&_af_eid=148118762&_af=event
The Perfect Storm: The Impact of Analytics, Big Data and AnalyticsInside Analysis
The document discusses the impacts of analytics, big data, and cloud computing. It notes that these trends are driving rapid business changes by enabling closed-loop businesses, massive information volumes, and increased collaboration. Recent technology advances like mobile apps, analytics, data processing improvements, and social/enterprise tools can help address emerging needs. Key points discussed include the growth of data sources and types, improvements in memory and parallel processing, and the evolving relationship between business and IT.
EDF2012 Simon Riggs - Open Data, Open Database: PostgreSQLEuropean Data Forum
PostgreSQL is an open source relational database management system with a 24-year development history. It is free, robust, and popular. PostgreSQL supports many advanced features including user-defined types, functions, and extensions like PostGIS for geographic data. It can be used as a relational, object-relational, post-relational, key-value, document-centric, or big data database.
SQL? NoSQL? NewSQL?!? What’s a Java developer to do? - JDC2012 Cairo, EgyptChris Richardson
This document discusses different database options for developers including SQL, NoSQL, and NewSQL databases. It provides an overview of why developers may choose NoSQL databases like MongoDB or Cassandra over traditional SQL databases, as well as when a NewSQL database could be a better option. The document uses a fictional example of a food delivery application to illustrate how different database choices would work for persisting and querying application data.
Real World Big Data, 100,000 transactions a second in a NoSQL DatabaseEric Bloch
This talk is about a Big Data use case requiring 100K transactions per second. It briefly cover the architecture of MarkLogic, an enterprise-grade NoSQL Document Database and why it's ideal for this case. The talk concludes with a detailed discussion of the techniques used, along with related performance analyses, to achieve the requirements.
Introducing Hibernate OGM: porting JPA applications to NoSQL, Sanne Grinovero...OpenBlend society
Hibernate OGM allows developers to use JPA to access NoSQL databases like Infinispan. It stores entities as tuples in the key-value store and uses Hibernate Search to index entities and support JP-QL queries. While still early, it aims to reuse familiar Hibernate concepts while taking advantage of NoSQL databases' flexibility, high availability, and scalability. It currently supports Infinispan but contributions are welcome to integrate other NoSQL databases.
View Barry Morris' presentation from the October 23 edition of The Briefing Room, entitled: “The Perfect Storm: The Impact of Analytics, Big Data and Cloud.” In this presentation, Morris introduces the NuoDB solution, an asynchronous, peer-to-peer database, specifically designed to meet 21st century database requirements. NuoDB is 100% SQL compliant and 100% ACID but scales elastically in the cloud or on-premise.
Big data hadoop-no sql and graph db-finalramazan fırın
This document discusses big data, Hadoop, NoSQL databases, and graph databases. It provides an overview of these topics and outlines potential uses for a telecommunications company, such as using big data to prevent customer churn, offer customer-specific campaigns, and get more customers. The document includes definitions and examples of key concepts like Hadoop, MapReduce, NoSQL databases, and the graph database Neo4j. It also summarizes trends in big data and provides examples of how telecom companies can analyze call detail records, model networks, and manage master customer data using these technologies.
Slides from workshop held on 12/14 in Asbury Park, NJ
http://www.meetup.com/Jersey-Shore-Tech/events/148118762/?gj=ro2_e&a=ro2_gnl&rv=ro2_e&_af_eid=148118762&_af=event
The Perfect Storm: The Impact of Analytics, Big Data and AnalyticsInside Analysis
The document discusses the impacts of analytics, big data, and cloud computing. It notes that these trends are driving rapid business changes by enabling closed-loop businesses, massive information volumes, and increased collaboration. Recent technology advances like mobile apps, analytics, data processing improvements, and social/enterprise tools can help address emerging needs. Key points discussed include the growth of data sources and types, improvements in memory and parallel processing, and the evolving relationship between business and IT.
EDF2012 Simon Riggs - Open Data, Open Database: PostgreSQLEuropean Data Forum
PostgreSQL is an open source relational database management system with a 24-year development history. It is free, robust, and popular. PostgreSQL supports many advanced features including user-defined types, functions, and extensions like PostGIS for geographic data. It can be used as a relational, object-relational, post-relational, key-value, document-centric, or big data database.
SQL? NoSQL? NewSQL?!? What’s a Java developer to do? - JDC2012 Cairo, EgyptChris Richardson
This document discusses different database options for developers including SQL, NoSQL, and NewSQL databases. It provides an overview of why developers may choose NoSQL databases like MongoDB or Cassandra over traditional SQL databases, as well as when a NewSQL database could be a better option. The document uses a fictional example of a food delivery application to illustrate how different database choices would work for persisting and querying application data.
Size does not matter (if your data is in a silo)Ora Lassila
The document discusses the challenges of working with large, distributed datasets from multiple sources. It summarizes that data is often siloed without common semantics, making integration and reuse difficult. It proposes that semantic web technologies can help by providing shared descriptions of data through ontologies, treating physical data schemas as virtual views onto semantic models. This would allow automation, discovery, and flexible use of large-scale data.
Objectivity/DB: A Multipurpose NoSQL DatabaseInfiniteGraph
The speakers will describe the flexible configuration possibilities that Objectivity/DB provides, with an emphasis on how best to distribute data across multiple storage nodes. The session will start by describing the distributed processing architecture of Objectivity/DB before covering the new Placement Manager features. The speakers will also describe how Objectivity/DB compares and contrasts with other NoSQL solutions.
Big Data - architectural concerns for the new ageDebasish Ghosh
This document discusses big data architectural concerns for handling large volumes of data. It notes that new technologies have enabled more efficient use of big data, creating a positive feedback loop where more adoption of big data leads to even more data generation. This requires new ways of storing, retrieving, scaling and analyzing data in a distributed manner. Examples of distributed databases like Bigtable and Dynamo are discussed. The document recommends flexible schemas, storing data close to its domain model, and limiting data movement for efficiency.
Daniel Austin of PayPal presented on using MySQL Cluster to build a globally distributed database called YESQL. He discussed common myths about big data and NoSQL databases, including that big data always requires NoSQL and that the CAP theorem is simpler than it really is. Austin explained how MySQL Cluster was used to build YESQL to meet requirements like high availability, scalability and global replication within 1000ms. He reviewed the architecture involving tiling across AWS availability zones and lessons learned.
Converting Unstructured Docs to XML/DITA/ePubDCLab
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. Key challenges and considerations for converting different document types and formats are also outlined.
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. Key challenges and considerations for converting different document types and formats are also outlined.
Converting Unstructured Docs to XML/DITA/ePubDCLab
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. The rest of the document compares different XML formats and discusses best practices, challenges, and considerations for converting different types of content and formats.
NoSQL – Back to the Future or Yet Another DB Feature?Martin Scholl
The document argues that NoSQL technology takes a step back from relational databases by complicating data integration and quality assurance, and that NoSQL systems will eventually just become another feature of database management systems and cloud computing services, with future "PostSQL" databases being indistinguishable from general data communication services.
A Global In-memory Data System for MySQLDaniel Austin
This is my presentation from Percona Live! London last year. I describe my Big Data system built on MySQL/NDB and show that we can preserve the relational model for most Big Data purposes in the real world.
This presentation was give by Dave Read at the Semantic Technology and Business Conference in June 2012. The goal of the presentation talks about using semantic technology to mitigate mobile platform constraints at runtime.
See more at www.blueslate.net
Getting Started with MongoDB at Oracle Open World 2012MongoDB
The document provides an overview of getting started with MongoDB. It discusses the benefits of MongoDB, common use cases, and how to get stakeholder buy-in for MongoDB projects. It also addresses execution of MongoDB projects, operational aspects like replica sets and sharding, and the economics advantages in terms of developer, hardware, and software savings compared to relational databases. Finally, it discusses why 10gen is a leader in MongoDB and provides commercial support, upcoming MongoDB features, and free online training. The document concludes by advertising upcoming sessions on a MongoDB use case at Apollo Group.
This document summarizes a presentation about using MySQL and the NDB storage engine to build a globally distributed in-memory database system on AWS. It proposes using MySQL/NDB clusters tiled across AWS availability zones to provide high availability and performance at a large scale. Key challenges discussed include managing data consistency across wide geographical distances and dealing with limitations of AWS like network performance and lack of global load balancing. Lessons learned are that NDB can successfully compete with NoSQL for most use cases by providing ACID compliance without sacrificing availability or performance.
The document discusses building agile analytics applications using Hadoop. It recommends setting up an environment where insights can be repeatedly produced through iterative and interactive exploration of data. The document emphasizes making an application for exploring data rather than trying to design insights directly. Insights are discovered through many iterations of refining the data and interacting with it.
The document discusses strategies for developing agile analytics applications using Hadoop, emphasizing an iterative approach where data is explored interactively to discover insights which then form the basis for shipped applications, rather than trying to design insights up front. It recommends setting up an environment where insights are repeatedly produced and shared with the team using an interactive application from the start to facilitate collaboration between data scientists and developers.
The Synergy Between the Object Database, Graph Database, Cloud Computing and ...InfiniteGraph
This document summarizes a presentation given by Leon Guzenda on the synergy between object database, graph database, cloud computing and NoSQL paradigms. It provides a historical overview of object database management systems and discusses their inherent advantages over relational databases. It also covers how these technologies have evolved, including the development of "NoSQL" systems, and how an object database management system can leverage other technologies like Hadoop. The presentation concludes that object database management systems are still highly relevant and that graph databases can complement relational, NoSQL and object database technologies.
This document summarizes a presentation by Andrew Brust at the SQL Server Live! Orlando 2012 conference about Microsoft's strategy for big data. The presentation introduces key concepts like Hadoop, MapReduce, HDFS, and Hive. It describes Microsoft's HDInsight platform for running Hadoop on Windows Azure and integrating Hadoop with SQL Server and business intelligence tools using approaches like the Hive ODBC driver and PowerPivot. The presentation argues that Microsoft's technologies are making big data stored in Hadoop accessible to more business users.
Mansoura University CSED & Nozom web development sprintAl Sayed Gamal
The document outlines an agenda for a web development training covering client-side and server-side technologies. It discusses web browsers, HTML, CSS, JavaScript, mockup tools, server-side programming with Python and Django, databases with MySQL, and rapid application development methodologies. Key topics include the web scenario, HTML tags and document structure, CSS selectors and properties, JavaScript basics, mockups, Python syntax, the Django framework, and agile development with SCRUM.
Messaging becomes Data Distributions gets embedded event processing (not complex, made simple) - bending all the rules one benchmark at a time - Push Technology, Waratek and other things
London JBUG April 2015 - Performance Tuning Apps with WildFly Application ServerJBUG London
This document discusses performance tuning for Wildfly8 applications. It outlines reasons for tuning like contractual obligations and user experience. It describes benchmarking methodology like defining test objectives and harnessing test tools. Common bottlenecks like the web tier, EJB tier, and JMS/JDBC connections are discussed. Wildfly tuning controls like thread pools, bean instance counts, and pool sizes are covered. Ideal request flow and queuing with timeouts are addressed. Specific thread pool types like unbounded, bounded, and blocking-bounded are explained. The presentation ends with questions.
Lightning talk by Navin Surtani (Consultant, C2B2 ) presented at the London JBoss User Group event on the 14th of January 2015.
For more information see Navin's blog post 'Clustering Websockets on WildFly' here: http://blog.c2b2.co.uk/2014/12/clustering-websockets-on-wildfly.html
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Size does not matter (if your data is in a silo)Ora Lassila
The document discusses the challenges of working with large, distributed datasets from multiple sources. It summarizes that data is often siloed without common semantics, making integration and reuse difficult. It proposes that semantic web technologies can help by providing shared descriptions of data through ontologies, treating physical data schemas as virtual views onto semantic models. This would allow automation, discovery, and flexible use of large-scale data.
Objectivity/DB: A Multipurpose NoSQL DatabaseInfiniteGraph
The speakers will describe the flexible configuration possibilities that Objectivity/DB provides, with an emphasis on how best to distribute data across multiple storage nodes. The session will start by describing the distributed processing architecture of Objectivity/DB before covering the new Placement Manager features. The speakers will also describe how Objectivity/DB compares and contrasts with other NoSQL solutions.
Big Data - architectural concerns for the new ageDebasish Ghosh
This document discusses big data architectural concerns for handling large volumes of data. It notes that new technologies have enabled more efficient use of big data, creating a positive feedback loop where more adoption of big data leads to even more data generation. This requires new ways of storing, retrieving, scaling and analyzing data in a distributed manner. Examples of distributed databases like Bigtable and Dynamo are discussed. The document recommends flexible schemas, storing data close to its domain model, and limiting data movement for efficiency.
Daniel Austin of PayPal presented on using MySQL Cluster to build a globally distributed database called YESQL. He discussed common myths about big data and NoSQL databases, including that big data always requires NoSQL and that the CAP theorem is simpler than it really is. Austin explained how MySQL Cluster was used to build YESQL to meet requirements like high availability, scalability and global replication within 1000ms. He reviewed the architecture involving tiling across AWS availability zones and lessons learned.
Converting Unstructured Docs to XML/DITA/ePubDCLab
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. Key challenges and considerations for converting different document types and formats are also outlined.
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. Key challenges and considerations for converting different document types and formats are also outlined.
Converting Unstructured Docs to XML/DITA/ePubDCLab
The document discusses converting legacy documents to XML formats like DITA and ePub. It provides an overview of a data conversion laboratory with 30 years of experience converting over 1 billion pages across many industries. The rest of the document compares different XML formats and discusses best practices, challenges, and considerations for converting different types of content and formats.
NoSQL – Back to the Future or Yet Another DB Feature?Martin Scholl
The document argues that NoSQL technology takes a step back from relational databases by complicating data integration and quality assurance, and that NoSQL systems will eventually just become another feature of database management systems and cloud computing services, with future "PostSQL" databases being indistinguishable from general data communication services.
A Global In-memory Data System for MySQLDaniel Austin
This is my presentation from Percona Live! London last year. I describe my Big Data system built on MySQL/NDB and show that we can preserve the relational model for most Big Data purposes in the real world.
This presentation was give by Dave Read at the Semantic Technology and Business Conference in June 2012. The goal of the presentation talks about using semantic technology to mitigate mobile platform constraints at runtime.
See more at www.blueslate.net
Getting Started with MongoDB at Oracle Open World 2012MongoDB
The document provides an overview of getting started with MongoDB. It discusses the benefits of MongoDB, common use cases, and how to get stakeholder buy-in for MongoDB projects. It also addresses execution of MongoDB projects, operational aspects like replica sets and sharding, and the economics advantages in terms of developer, hardware, and software savings compared to relational databases. Finally, it discusses why 10gen is a leader in MongoDB and provides commercial support, upcoming MongoDB features, and free online training. The document concludes by advertising upcoming sessions on a MongoDB use case at Apollo Group.
This document summarizes a presentation about using MySQL and the NDB storage engine to build a globally distributed in-memory database system on AWS. It proposes using MySQL/NDB clusters tiled across AWS availability zones to provide high availability and performance at a large scale. Key challenges discussed include managing data consistency across wide geographical distances and dealing with limitations of AWS like network performance and lack of global load balancing. Lessons learned are that NDB can successfully compete with NoSQL for most use cases by providing ACID compliance without sacrificing availability or performance.
The document discusses building agile analytics applications using Hadoop. It recommends setting up an environment where insights can be repeatedly produced through iterative and interactive exploration of data. The document emphasizes making an application for exploring data rather than trying to design insights directly. Insights are discovered through many iterations of refining the data and interacting with it.
The document discusses strategies for developing agile analytics applications using Hadoop, emphasizing an iterative approach where data is explored interactively to discover insights which then form the basis for shipped applications, rather than trying to design insights up front. It recommends setting up an environment where insights are repeatedly produced and shared with the team using an interactive application from the start to facilitate collaboration between data scientists and developers.
The Synergy Between the Object Database, Graph Database, Cloud Computing and ...InfiniteGraph
This document summarizes a presentation given by Leon Guzenda on the synergy between object database, graph database, cloud computing and NoSQL paradigms. It provides a historical overview of object database management systems and discusses their inherent advantages over relational databases. It also covers how these technologies have evolved, including the development of "NoSQL" systems, and how an object database management system can leverage other technologies like Hadoop. The presentation concludes that object database management systems are still highly relevant and that graph databases can complement relational, NoSQL and object database technologies.
This document summarizes a presentation by Andrew Brust at the SQL Server Live! Orlando 2012 conference about Microsoft's strategy for big data. The presentation introduces key concepts like Hadoop, MapReduce, HDFS, and Hive. It describes Microsoft's HDInsight platform for running Hadoop on Windows Azure and integrating Hadoop with SQL Server and business intelligence tools using approaches like the Hive ODBC driver and PowerPivot. The presentation argues that Microsoft's technologies are making big data stored in Hadoop accessible to more business users.
Mansoura University CSED & Nozom web development sprintAl Sayed Gamal
The document outlines an agenda for a web development training covering client-side and server-side technologies. It discusses web browsers, HTML, CSS, JavaScript, mockup tools, server-side programming with Python and Django, databases with MySQL, and rapid application development methodologies. Key topics include the web scenario, HTML tags and document structure, CSS selectors and properties, JavaScript basics, mockups, Python syntax, the Django framework, and agile development with SCRUM.
Messaging becomes Data Distributions gets embedded event processing (not complex, made simple) - bending all the rules one benchmark at a time - Push Technology, Waratek and other things
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London JBUG April 2015 - Performance Tuning Apps with WildFly Application ServerJBUG London
This document discusses performance tuning for Wildfly8 applications. It outlines reasons for tuning like contractual obligations and user experience. It describes benchmarking methodology like defining test objectives and harnessing test tools. Common bottlenecks like the web tier, EJB tier, and JMS/JDBC connections are discussed. Wildfly tuning controls like thread pools, bean instance counts, and pool sizes are covered. Ideal request flow and queuing with timeouts are addressed. Specific thread pool types like unbounded, bounded, and blocking-bounded are explained. The presentation ends with questions.
Lightning talk by Navin Surtani (Consultant, C2B2 ) presented at the London JBoss User Group event on the 14th of January 2015.
For more information see Navin's blog post 'Clustering Websockets on WildFly' here: http://blog.c2b2.co.uk/2014/12/clustering-websockets-on-wildfly.html
Presentation delivered by Darran Lofthouse, Principal Software Engineer, Red Hat & Kabir Khan, Principal Software Engineer, Red Hat, during London JBoss User Group event on the 21st of May 2014.
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Presentation
Introductory talk to PicketLink from Federation through to Identity Management.
What is PicketLink?
PicketLink is an umbrella project for security and identity management for Java Applications. PicketLink is an important project under the security offerings from JBoss.
A Picket Fence is a secure system of pickets joined together via some type of links. Basically, the Pickets by themselves do not offer any security. But when they are brought together by linking them, they provide the necessary security.
This project is that link for other security systems or systems to bring together or join, to finally provide the necessary secure system.
For more information visit http://picketlink.org/
Presentation by Tomaz Cerar (Red Hat), delivered at the London JBoss User Group event on the 12th of February 2014.
Watch the video here: http://www.youtube.com/watch?v=eu9K5NLUKBI
Join London JBUG: http://www.c2b2.co.uk/jbug
Presentation delivered by Mircea Markus (JBoss) at the London JBoss User Group Event on Wednesday, the 4th of December 2013.
In this talk, Mircea Markus (Infinispan Lead) covers the major features added in the 6.0 release to the Infinispan ecosystem:
- querying in client/server mode
- better integration with the persistent storage
- multi-master cross-site replication
- support for heterogeneous clusters
Participants will take home a better understanding of Infinispan capabilities and the use cases in which it can be put at work. Ideally the attendees should have a basic knowledge of the in-memory data grids.
Compensating Transactions: When ACID is too muchJBUG London
The talk was presented by Dr Paul Robinson (Red Hat) at the London JBoss User Group event on the 25th of September 2013.
Video available soon
ACID transactions are a useful tool for application developers and can provide very strong guarantees, even in the presence of failures. However, ACID transactions are not always appropriate for every situation.
ACID transactions are achieved by holding locks on resources and require the ability to rollback changes. In some situations, the blocking nature of the protocol can be too limiting to performance, especially if the transaction is distributed. Also, some actions can’t simply be rolled back; for example, sending an email.
A common strategy for applications that can’t use ACID, is to throw out transactions altogether. However, with this approach you are missing out on many of the benefits that transactions can provide. There are alternative transaction models that relax some of the ACID properties, while still retaining many of the strong guarantees essential for building robust enterprise applications. These should be considered before deciding not to use transactions at all.
In this talk, I’ll present one such alternative to ACID transactions: compensation-based transactions. I’ll provide an overview of ACID and it’s limitations and describe some use-cases where ACID is not appropriate. I’ll then present our new API for compensation-based transactions and demonstrate how it can be used to address these problems. Finally, I’ll present our future plans to improve and expand our support for compensation-based transactions.
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Presentation by Rob Davies (Red Hat) delivered at the London JBoss USer Group event on the 10th of July 2013.
See the video here: http://youtu.be/VrJyKLAXVTg
As part of the FuseSource acquisition, Red Hat now supports Apache ActiveMQ as the recently released Red Hat JBoss A-MQ product.
ActiveMQ is the most widely used message-oriented middleware that uses messaging to connect remote applications written in Java, C/C++, Python, Perl, Ruby, and many other languages. ActiveMQ is standards based and supports messaging protocols such as AMQP 1.0, WebSockets, Stomp, OpenWire, and MQTT.
In this session, Rob Davies will discuss the product’s features and functionality, and demonstrate connectivity from a microprocessor to web sockets using JBoss A-MQ.
Easy Integration with Apache Camel and Fuse IDEJBUG London
The talk presented by James Strachan (Red Hat) on the 6th of March 2013 at the London JBoss USer Group event.
Visit London JBUG on Meetup http://www.meetup.com/JBoss-User-Group/
Talk by Mauricio Salatino and Esteban Aliverti presented at the JBUG London Event on the 12th of December 2012.
To watch the video please visit http://www.youtube.com/watch?v=9M1eaH3v4qg
Arquillian - Integration Testing Made EasyJBUG London
Slides by Davide D'Alto presented at JBUG London event on the 24th of October 2012.
You can watch the presentation video here http://youtu.be/MuqAx9SuIOk
The document describes how Infinispan was used to improve the performance and scalability of two different systems - an existing production system (Part 1) and a new greenfield project (Part 2).
For the existing system, Infinispan replaced EhCache to distribute caching across multiple nodes and reduce heap usage. Benchmarking was used to validate the solution. Issues encountered with Hotrod were addressed by using embedded caching instead.
For the new project, distributed caching did not work due to high network traffic. Distributed execution was used instead, where tasks are run on nodes containing the data to minimize traffic. This reduced latency from 2 seconds to 200ms.
JBoss jBPM, the future is now for all your Business Processes by Eric SchabellJBUG London
This document discusses jBPM5 and its capabilities for business process management. It begins with an overview of business process management and workflow. It then discusses how jBPM5 has evolved from a workflow engine to a full BPMS with support for BPMN 2.0, rules, events, flexible processes, and domain-specific processes. It highlights features like the Eclipse plugin, web designer, and integration capabilities. The document promotes jBPM5 as providing a flexible solution for all process and workflow needs.
Presented by Matt Brasier on 15th of June 2011 at the JBUG is Back! June Event - JBoss 7
More info: http://www.meetup.com/JBoss-User-Group/events/19943531/
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
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Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
2. Hibernate OGM
JPA for Infinispan and NoSQL
Emmanuel Bernard
Data Platform Architect
but actually doing things
JBoss By Red Hat
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
3. Before you leave
• JPA for NoSQL
• first key / value (Infinispan)
• Denormalization engine
• Reuse mature projects
• Influenced by the relational model
• Does queries too (gradual ramp up)
• Early phases
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
4. Emmanuel Bernard
• Hibernate
• JCP
• Ceylon
• Podcasts
• asylum.jboss.org
• lescastcodeurs.com
• The rest is at http://emmanuelbernard.com
• @emmanuelbernard
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
5. (No)SQL tour
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
6. Relational databases
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
7. Relational databases
• Data structure abstraction
• Transaction, referential integrity
• Common query language
• (Simple) type
• Proven usefulness
• tuning, backup, resilience
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
8. Relational databases
• (Some) limitations:
• planning for scale is hard
• data model changes are painful
• New needs
• limitless data for later analysis
• instant fame syndrome
• less query demanding data
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
9. NoSQL is not new
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
10. NoSQL is not new
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
11. NoSQL is not new
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
12. NoSQL alternatives
• Web “giants” needs
• Very different Goals
• data size / availability
• low latency / higher throughput
• Optimize some data access patterns
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
13. NoSQL families
• Graph oriented databases
• Key / value stores
• Document based stores key value
• BigTable-style 123 Address@23
126 “Booya”
A foo B bar C baz
{ "user" : {
1 Things
"id": "124",
2 Things C bam E coh People A Emmanuel "name": "Emmanuel",
"addresses" : [
3 Languages A C B Java C Ceylon { "city": "Paris", "country": "France" },
{ "city": "Atlanta", "country": "USA" }
]
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc. }
jeudi 23 février 2012
14. Flexibility at a cost
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
15. Flexibility at a cost
• Programming model
• no common API :(
• query (Map Reduce, specific DSL, ...)
• no schema => app driven schema
• Physical data structure transpires
• Transaction / durability / consistency
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
16. JPA for NoSQL
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
17. Demo
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
18. Goals
• Encourage new data usage patterns
• volume, types etc
• Familiar environment
• Full JPA support
• easy to jump in (and out!)
• Stop talking, act
• “PaaS on Java EE” initiative
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
19. What it does
• Today
• JPA front end for Infinispan and more
• CRUD support for @Entities
• Full-text queries
• Tomorrow
• JP-QL queries (simple ones)
• Other NoSQL
• The day after
• Complex JP-QL queries
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
20. Not a silver bullet!
• But JPA matches quite nicely
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
21. Domain model
POJO
persists indexes / searches
JPA: programmatic API
Hibernate
Hibernate Core
Search
searches / indexes
stored in
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
22. Domain model
POJO
persists indexes / searches
JPA: programmatic API
enables
Hibernate
Hibernate Core complex joins Teiid
Search and aggregation
searches / indexes
stored in
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
23. Domain model
POJO
persists indexes / searches
Search engine
JPA: programmatic API
enables
Hibernate
Hibernate Core complex joins Teiid
Search and aggregation
searches / indexes
stored in
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
24. Domain model
POJO
persists indexes / searches
Search engine
JPA: programmatic API
enables
Hibernate
Hibernate Core complex joins Teiid
Search and aggregation
delegates delegates
object logic to search to
Hibernate OGM JP-QL searches / indexes
Core converter stored in
persists into
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
25. Domain model
POJO
persists indexes / searches
Search engine
JPA: programmatic API
enables
Hibernate
Hibernate Core complex joins Teiid
Search and aggregation
delegates delegates
object logic to search to
Hibernate OGM JP-QL searches / indexes
Core converter stored in
Object/Grid Mapper
persists into
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
26. Domain model
POJO
NoSQL
persists indexes / searches
Search engine
JPA: programmatic API
enables
Hibernate
Hibernate Core complex joins Teiid
Search and aggregation
delegates delegates
object logic to search to
Hibernate OGM JP-QL searches / indexes
Core converter stored in
Object/Grid Mapper
persists into
distributed
Innispan
key/value store
Innispan
Innispan
Innispan
Innispan
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
27. Concepts
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
28. Schema or no schema?
• Schema-less
• developer friendly
• data structure migration?
• need strict development guidelines
• Schema
• strong documentation
• share with other apps / tooling
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
29. Entities as serialized blobs?
• Store the whole graph?
• Consistency with duplicated objects
• Concurrency / latency
• Structure change and (de)serialization
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
30. OGM’s approach
• Keep what’s best from relational model
• as much as possible
• Decorrelate object and data structure
• object model evolution
• Data stored as (self-described) tuples
• Limited set of core types
• CRUD operations are key lookups
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
31. Infinispan
• In-memory key / value store + cache store
• Data grid
• memory >> network >> local disk access
• Transactional
• JTA / XAResource
• Distributed
• virtual memory =
(sum of servers)/redundancy
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
32. Hibernate OGM’s
data structure
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
33. Storage - Entities
• Each entity in a unique key
• table name
• id column names and values
• Value is Map<String,Object>
• String: column name
• Object: simple type (serializable)
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
34. Storage - Associations
• Cannot store exactly like relational DBs
• Simulate navigation to associations
• one key per navigation
• Value is the list of tuples
• Focus on speedy reads
• writes involve several key lookups
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
35. User
Address
userId n n addressId
name
city
addresses
tbl_user tbl_user_address tbl_address
1 * 1
userId_pk * userId_fk addressId_pk
name addressId_fk city
key value
tbl_user,userId_pk,1 {userId_pk=1,name=””Emmanuel””}
tbl_user,userId_pk,2 {userId_pk=2,name=””Caroline””}
tbl_address,addressId_pk,3 {addressId_pk=3,city=””Paris””}
tbl_address,addressId_pk,5 {addressId_pk=5,city=””Atlanta””}
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,userId_fk,1
{userId_fk=1, addressId_fk=5} }
tbl_user_address,userId_fk,2 { {userId_fk=2, addressId_fk=3} }
tbl_user_address,addressId_fk,5 { {userId_fk=1, addressId_fk=5} }
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,addressId_fk,3
{userId_fk=2, addressId_fk=3} }
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
36. User
Address
userId n n addressId
name
city
addresses
tbl_user tbl_user_address tbl_address
1 * 1
userId_pk * userId_fk addressId_pk
name addressId_fk city
key value
tbl_user,userId_pk,1 {userId_pk=1,name=””Emmanuel””}
tbl_user,userId_pk,2 {userId_pk=2,name=””Caroline””}
tbl_address,addressId_pk,3 {addressId_pk=3,city=””Paris””}
tbl_address,addressId_pk,5 {addressId_pk=5,city=””Atlanta””}
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,userId_fk,1
{userId_fk=1, addressId_fk=5} }
tbl_user_address,userId_fk,2 { {userId_fk=2, addressId_fk=3} }
tbl_user_address,addressId_fk,5 { {userId_fk=1, addressId_fk=5} }
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,addressId_fk,3
{userId_fk=2, addressId_fk=3} }
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
37. User
Address
userId n n addressId
name
city
addresses
tbl_user tbl_user_address tbl_address
1 * 1
userId_pk * userId_fk addressId_pk
name addressId_fk city
key value
tbl_user,userId_pk,1 {userId_pk=1,name=””Emmanuel””}
tbl_user,userId_pk,2 {userId_pk=2,name=””Caroline””}
tbl_address,addressId_pk,3 {addressId_pk=3,city=””Paris””}
tbl_address,addressId_pk,5 {addressId_pk=5,city=””Atlanta””}
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,userId_fk,1
{userId_fk=1, addressId_fk=5} }
tbl_user_address,userId_fk,2 { {userId_fk=2, addressId_fk=3} }
tbl_user_address,addressId_fk,5 { {userId_fk=1, addressId_fk=5} }
{ {userId_fk=1, addressId_fk=3},
tbl_user_address,addressId_fk,3
{userId_fk=2, addressId_fk=3} }
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
38. Queries
• Hibernate Search indexes entities
• Store Lucene indexes in Infinispan
• JP-QL to Lucene query
• Works for simple-ish queries
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
39. select a from Animal a where a.size > 20
> animalQueryBuilder
.range().onField(“size”).above(20).excludeLimit()
.createQuery();
select u from Order o join o.user u
where o.price > 100 and u.city = “Paris”
> orderQB.bool()
.must(
orderQB.range().onField(“price”)
.above(100).excludeLimit().createQuery() )
.must(
orderQB.keyword().onField(“user.city”)
.matching(“Paris”).createQuery() )
.createQuery();
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
40. Future
• More NoSQL families
• More JP-QL support
• JP-QL to “primitives”
• API for operations in bulk
• More denormalization options
• Hybrid deployment options
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
41. Hibernate OGM
• JPA for NoSQL (Infinispan initially)
• Reuse mature projects
• Relational structure
• Does queries too
• Status
• work in progress
• refining the core data structure
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
42. More info
• Documentation
• http://ogm.hibernate.org
• including reference doc
• Any good JPA book ;)
• Code
• come and contribute! It’s fun stuff
• https://github.com/hibernate/hibernate-ogm
• Q&A
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012
43. References
• Pictures under creative commons
• http://www.flickr.com/photos/tomsaint/3415333390/
• http://www.flickr.com/photos/anniewong/26473161/
• http://www.flickr.com/photos/jdhancock/5002736203/
• http://www.flickr.com/photos/liutao/280498401
• http://www.flickr.com/photos/ehw/243631365/
Copyright 2010-2012 Emmanuel Bernard and Red Hat Inc.
jeudi 23 février 2012