Geek Sync | Azure Cloud & You: First Steps for the DBAIDERA Software
You can watch the replay for this Geek Sync webcast, Azure Cloud & You: First Steps for the DBA, in the IDERA Resource Center, http://ow.ly/68S750A4rtU.
It's not a question of whether or not the landscape for the common DBA is changing. Without a doubt, it is. Azure offers up a new world of possibilities for DBA's and we should all strive to learn it. In this session, we'll cover some basic knowledge and terminology of Azure as well as how easy it is to incorporate Azure into your environment. We will stand up a new Azure virtual machine as well as a setup SQL DB. You will see how easy it is to accomplish this. This new-found knowledge will help propel your career into the new landscape.
Speaker: John Morehouse is currently a Consultant with Denny Cherry & Associates living in Louisville, Kentucky. John led the Omaha SQL Server user group for 7 years and is now a leader of the Louisville SQL Server/Power BI user group. He is a Microsoft Data Platform MVP, 2016 IDERA ACE, blogger, avid tweeter, and a frequent speaker at SQL Saturday's as well as other conferences. In his spare time, you can usually find John on Twitter (@sqlrus) as well as chasing his two young sons around the house.
Presentation at the Percona-Live event in San Francisco from Tamar Bercovici and me about the big scaling project of the MySQL database we did at Box in 2012.
How to design software and APIs for parallelism on modern hardware
- Richard Parker, mathematician and freelance computer programmer in Cambridge, England
I see only three techniques capable of speeding up well written but old software by a factor of ten or more, namely
- Using multiple cores
- Making good use of cache memory
- Using the full power of a single processor.
So far, commercial software seems to have ignored recent changes in hardware. Often, performance does not really matter, but when it does matter, it requires changes to the design and coding of the computer software.
I have been looking into the changes needed for several years now, and it is gradually emerging that one aspect sticks out as being more important than all the others.
If functions, subroutines, methods etc. do a large number of whatever they do, rather than just one, it becomes possible to write clever implementations that run much faster. Several examples of this will be discussed.
I suggest that software designed and written today should take this into account, making it easier to speed it up if and when it becomes necessary to do so.
Geek Sync | Azure Cloud & You: First Steps for the DBAIDERA Software
You can watch the replay for this Geek Sync webcast, Azure Cloud & You: First Steps for the DBA, in the IDERA Resource Center, http://ow.ly/68S750A4rtU.
It's not a question of whether or not the landscape for the common DBA is changing. Without a doubt, it is. Azure offers up a new world of possibilities for DBA's and we should all strive to learn it. In this session, we'll cover some basic knowledge and terminology of Azure as well as how easy it is to incorporate Azure into your environment. We will stand up a new Azure virtual machine as well as a setup SQL DB. You will see how easy it is to accomplish this. This new-found knowledge will help propel your career into the new landscape.
Speaker: John Morehouse is currently a Consultant with Denny Cherry & Associates living in Louisville, Kentucky. John led the Omaha SQL Server user group for 7 years and is now a leader of the Louisville SQL Server/Power BI user group. He is a Microsoft Data Platform MVP, 2016 IDERA ACE, blogger, avid tweeter, and a frequent speaker at SQL Saturday's as well as other conferences. In his spare time, you can usually find John on Twitter (@sqlrus) as well as chasing his two young sons around the house.
Presentation at the Percona-Live event in San Francisco from Tamar Bercovici and me about the big scaling project of the MySQL database we did at Box in 2012.
How to design software and APIs for parallelism on modern hardware
- Richard Parker, mathematician and freelance computer programmer in Cambridge, England
I see only three techniques capable of speeding up well written but old software by a factor of ten or more, namely
- Using multiple cores
- Making good use of cache memory
- Using the full power of a single processor.
So far, commercial software seems to have ignored recent changes in hardware. Often, performance does not really matter, but when it does matter, it requires changes to the design and coding of the computer software.
I have been looking into the changes needed for several years now, and it is gradually emerging that one aspect sticks out as being more important than all the others.
If functions, subroutines, methods etc. do a large number of whatever they do, rather than just one, it becomes possible to write clever implementations that run much faster. Several examples of this will be discussed.
I suggest that software designed and written today should take this into account, making it easier to speed it up if and when it becomes necessary to do so.
Basic performance application optimization techniques that can be applied to any application, from web to desktop or mobile, but with focus on php/mysql stack. How to identify bottlenecks and resolve them and what strategies to choose to avoid them upfront.
Live presentation:
https://www.youtube.com/watch?v=aas8oM7CLjk
How MySQL become an Internet standard? based on a presentation I gave at the Database2011 conference: Who uses MySQL? (everyone inc. Facebook, Twitter and Google), What are MySQL limitations? (multi threading, INSERTS, SELECTS), How the big boys solved these issues? (Sharding, Partitioning), What are the pros and cons for each Sharding strategy? (Vertical, Horizonal: directory based, static hashing, signature based), How to implement Sharding from an applicative view? How to take care of reporting? What are the emerging solutions in this field? (Gizzard, ScaleBase, Xeround and Akibian)
Data Science Salon: A Journey of Deploying a Data Science Engine to ProductionFormulatedby
Presented by Mostafa Madjipour., Senior Data Scientist at Time Inc.
Next DSS NYC Event 👉 https://datascience.salon/newyork/
Next DSS LA Event 👉 https://datascience.salon/la/
Reducing the gap between R&D and production is still a challenge for data science/ machine learning engineering groups in many companies. Typically, data scientists develop the data-driven models in a research-oriented programming environment (such as R and python). Next, the data/machine learning engineers rewrite the code (typically in another programming language) in a way that is easy to integrate with production services.
This process has some disadvantages: 1) It is time consuming; 2) slows the impact of data science team on business; 3) code rewriting is prone to errors.
A possible solution to overcome the aforementioned disadvantages would be to implement a deployment strategy that easily embeds/transforms the model created by data scientists. Packages such as jPMML, MLeap, PFA, and PMML among others are developed for this purpose.
In this talk we review some of the mentioned packages, motivated by a project at Time Inc. The project involves development of a near real-time recommender system, which includes a predictor engine, paired with a set of business rules.
PHPID - Code Factory Online Meetup, Supporting COVID-19 with Rumah Komunitas. Silakan kunjungi laman ini untuk rekaman meetup https://youtu.be/pACuwalpQpk
Basic performance application optimization techniques that can be applied to any application, from web to desktop or mobile, but with focus on php/mysql stack. How to identify bottlenecks and resolve them and what strategies to choose to avoid them upfront.
Live presentation:
https://www.youtube.com/watch?v=aas8oM7CLjk
How MySQL become an Internet standard? based on a presentation I gave at the Database2011 conference: Who uses MySQL? (everyone inc. Facebook, Twitter and Google), What are MySQL limitations? (multi threading, INSERTS, SELECTS), How the big boys solved these issues? (Sharding, Partitioning), What are the pros and cons for each Sharding strategy? (Vertical, Horizonal: directory based, static hashing, signature based), How to implement Sharding from an applicative view? How to take care of reporting? What are the emerging solutions in this field? (Gizzard, ScaleBase, Xeround and Akibian)
Data Science Salon: A Journey of Deploying a Data Science Engine to ProductionFormulatedby
Presented by Mostafa Madjipour., Senior Data Scientist at Time Inc.
Next DSS NYC Event 👉 https://datascience.salon/newyork/
Next DSS LA Event 👉 https://datascience.salon/la/
Reducing the gap between R&D and production is still a challenge for data science/ machine learning engineering groups in many companies. Typically, data scientists develop the data-driven models in a research-oriented programming environment (such as R and python). Next, the data/machine learning engineers rewrite the code (typically in another programming language) in a way that is easy to integrate with production services.
This process has some disadvantages: 1) It is time consuming; 2) slows the impact of data science team on business; 3) code rewriting is prone to errors.
A possible solution to overcome the aforementioned disadvantages would be to implement a deployment strategy that easily embeds/transforms the model created by data scientists. Packages such as jPMML, MLeap, PFA, and PMML among others are developed for this purpose.
In this talk we review some of the mentioned packages, motivated by a project at Time Inc. The project involves development of a near real-time recommender system, which includes a predictor engine, paired with a set of business rules.
PHPID - Code Factory Online Meetup, Supporting COVID-19 with Rumah Komunitas. Silakan kunjungi laman ini untuk rekaman meetup https://youtu.be/pACuwalpQpk
NoSQL is not a buzzword anymore. The array of non- relational technologies have found wide-scale adoption even in non-Internet scale focus areas. With the advent of the Cloud...the churn has increased even more yet there is no crystal clear guidance on adoption techniques and architectural choices surrounding the plethora of options available. This session initiates you into the whys & wherefores, architectural patterns, caveats and techniques that will augment your decision making process & boost your perception of architecting scalable, fault-tolerant & distributed solutions.
An overview of various database technologies and their underlying mechanisms over time.
Presentation delivered at Alliander internally to inspire the use of and forster the interest in new (NOSQL) technologies. 18 September 2012
When things can't be done in such a way that a small change to the db causes many changes and recompilation of your app is this really agile? Do you really believe it or had sworn to it? I use my own technique to minimize or completety eliminate this common problem. Come to see what you might never heard of.
Cassandra Community Webinar: From Mongo to Cassandra, Architectural LessonsDataStax
We'll be covering some aspects of our architecture, highlighting differences between MongoDB and Cassandra. We'll go in depth to explain why Cassandra is a better choice for our general purpose Application Platform (SHIFT) as well as our Media Buying Analytics tool (the SHIFT Media Manager). We'll be going over common design patterns people might be familiar with coming from a background with MongoDB and highlight how Cassandra would be used as a better alternative. We'll also touch more on cqlengine which is nearing feature completeness as the Cassandra object mapper for Python.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
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
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
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.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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.
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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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
2. OUTLINES
1. What is ORM ?!
2. Why ORM ?!
3. What is CORBA ?
4. Problem: Object-relational impedance mismatch
5. ORM Components and Architecture
6. Disadvantages of ORM
7. Comparison
8. Choosing an ORM tool
9. Demonstration of ORM using Micro ORM
10. What Next ?!
11. Q & A
12. References
3. WHAT IS ORM ?!
in computer science is a programming technique for converting data between incompatible type
systems in object-oriented programming languages. This creates, in effect, a "virtual object database" that
can be used from within the programming language.
4. WHY ORM ?!
• Speeds-up Development - eliminates the need for repetitive SQL code.
• Reduces Development Time.
• Reduces Development Costs.
• Overcomes vendor specific SQL differences - the ORM knows how to write vendor specific SQL so you
don't have to.
• Rich query capability. ORM tools provide an object oriented query language.
5. WHAT IS CORBA ?!
• Common Object Request Broker Architecture (CORBA)
• A standard defined by the Object Management Group (OMG)
designed to facilitate the communication of systems that are
deployed on diverse platforms.
• Enables collaboration between systems on different operating
systems, programming languages, and computing hardware.
• CORBA has many of the same design goals as object-oriented
programming: encapsulation and reuse.
• CORBA uses an object-oriented model although the systems that
utilize CORBA do not have to be object-oriented.
6. OBJECT-RELATIONAL IMPEDANCE MISMATCH
The object-relational impedance mismatch is a set of conceptual and technical difficulties that are often
encountered when a relational database management system (RDBMS) is being used by a program written
in an object-oriented programming language or style; particularly when objects or class definitions are
mapped in a straightforward way to database tables or relational schema.
7. OBJECT-RELATIONAL IMPEDANCE MISMATCH
'Object-Relational Impedance Mismatch' is just a fancy way of saying that object models and relational
models do not work very well together. RDBMSs represent data in a tabular format , whereas object-
oriented languages, such as Java, C# represent it as an interconnected graph of objects. Loading and
storing graphs of objects using a tabular relational database exposes us to 5 mismatch problems
• Granularity
• Subtypes (inheritance)
• Identity
• Associations
• Data Types
8. GRANULARITY
Sometimes you will have an object model which has more classes than the number of corresponding
tables in the database
public class Teacher{
}
public class School{
}
9. SUBTYPES (INHERITANCE)
• Inheritance is a natural paradigm in object-oriented programming languages. However, RDBMSs do not
define anything similar to Inheritance
Human
Man Woman
Inheritance
10. IDENTITY
• A RDBMS defines exactly one notion of 'sameness‘
• Java, however, defines both object identity a==b and object equality a. equals(b) .
11. ASSOCIATIONS & DATA NAVIGATION
• Associations are represented as unidirectional references in Object Oriented languages whereas
RDBMSs use the notion of foreign keys. If you need bidirectional relationships in C#, you must define
the association twice
• The way you access data in Java or C# is fundamentally different than the way you do it in a relational
database. In Java or C# you navigate from one association to an other walking the object network.
Class user_main {
Teacher teacher;
}
Class Teacher {
}
12. DATA TYPES
• When we consider about data types there a mismatches, simply String might have limited size than a
varchar data type
• String Varchar(150)
• Mismatches Between Date and time in the object world and the relational world
17. FETCHING
• Basically when you think about it, a class is just another data type.
• However unlike say an int, we really don't want to load it when the rest of the class is loaded.
• we might end up loading our entire database or even end up in an endless loop of loading.
• So what most ORM do to combat this is use something called lazy loading.
• Lazy loading is simply a design pattern where you load/initialize an object only when it is needed.
• Lazy loading Levels
• for the data through relations
• for some columns. When we want to display just a list of names, we don't need all the columns of a table to be
loaded. We may need the blob fields only at certain point, under certain conditions, and so it's better to load
them only at that time.
18. ORM COMPONENTS : CACHING AND OPTIMIZATIONS
• Lazy loading (the loading of some data is deferred until it's needed)
• for the data through relations
• for some columns. When we want to display just a list of names, we don't need all the columns of a table to be loaded. We may need the blob fields
only at certain point, under certain conditions, and so it's better to load them only at that time.
• Cache dynamically generated queries, so that they don't get rebuilt at each call.
• Cache some data to avoid too many calls to the data source.
• Optimized queries (update only the modified columns; detect situations where the number of executed queries can be reduced; ...)
• Handle circular references without duplication of objects ("account == account.Client.Account")
• Handle cascade updates. Deleting a master record should delete the linked details if wished so.
• Bulk updates or deletions. When we want to update or delete thousands of records at a time, it's not possible to load all the objects
in memory, while this can be easily and quickly done with a SQL query (DELETE FROM Customer WHERE Balance < 0). Support from
the tool is welcome to handle such massive operations without having to deal with SQL. Hibernate is not very good on this point for
example.
20. DISADVANTAGES OF ORM
• ORM adds a least one small layer of application code, potentially increasing processing overhead.
• ORM can load related business objects on demand.
• An ORM system's design might dictate certain database design decisions.
22. CHOOSING AN ORM TOOL• Be able to use inheritance
• Handle any type of relations (1-1, 1-n, n-n)
• Aggregates (equivalent to SQL's SUM, AVG, MIN, MAX, COUNT)
• Support for grouping (SQL's GROUP BY)
• Support for transactions
• Supported databases.
• Query language (OQL - Object Query Language, OPath).
• Support for DataBinding
• Customization of queries.
• Support any type of SQL joins (inner join, outer join)
• Concurrency management (support for optimistic and pessimistic approaches)
• Support for the data types specific to the database management system (identity columns, sequences,
GUIDs, autoincrements)
• Be able to map a single object to data coming from multiple tables (joins, views).
• Be able to dispatch the data from a single table to multiple objects.
What is ORM ?!
Many object-oriented applications created today, use relational databases for persistence.
There is a straight forward correspondence between database tables and application classes.
Developers usually write a great deal of code to connect to and query the database
When we work with an object-oriented systems, there's a mismatch between the object model and the relational database.
RDBMSs represent data in a tabular format whereas object-oriented languages (Java or C#) represent it as an interconnected graph of objects.
Granularity
Sometimes you will have an object model which has more classes than the number of corresponding tables in the
database (we say the object model is more granular than the relational model). Take for example the notion of an
Address…
Subtypes (inheritance)
Inheritance is a natural paradigm in object-oriented programming languages. However, RDBMSs do not define
anything similar on the whole (yes some databases do have subtype support but it is completely no standardized)…
Identity
A RDBMS defines exactly one notion of sameness: the primary key. Java, however, defines both object identity
a==b and object equality a. equals(b) .
Associations
Associations are represented as unidirectional references in Object Oriented languages whereas RDBMSs use
the notion of foreign keys. If you need bidirectional relationships in Java, you must define the association twice.
Likewise, you cannot determine the multiplicity of a relationship by looking at the object domain model.
Data navigation
The way you access data in Java is fundamentally different than the way you do it in a relational database. In
Java, you navigate from one association to an other walking the object network.
Granularity
Sometimes you will have an object model which has more classes than the number of corresponding tables in the
database (we say the object model is more granular than the relational model). Take for example the notion of an
Address…
Subtypes (inheritance)
Inheritance is a natural paradigm in object-oriented programming languages. However, RDBMSs do not define
anything similar on the whole (yes some databases do have subtype support but it is completely no standardized)…
Identity
A RDBMS defines exactly one notion of sameness: the primary key. Java, however, defines both object identity
a==b and object equality a. equals(b) .
Associations
Associations are represented as unidirectional references in Object Oriented languages whereas RDBMSs use
the notion of foreign keys. If you need bidirectional relationships in Java, you must define the association twice.
Likewise, you cannot determine the multiplicity of a relationship by looking at the object domain model.
Data navigation
The way you access data in Java is fundamentally different than the way you do it in a relational database. In
Java, you navigate from one association to an other walking the object network.
Granularity
Sometimes you will have an object model which has more classes than the number of corresponding tables in the
database (we say the object model is more granular than the relational model). Take for example the notion of an
Subtypes (inheritance)
Inheritance is a natural paradigm in object-oriented programming languages. However, RDBMSs do not define
anything similar on the whole (yes some databases do have subtype support but it is completely no standardized)…
A RDBMS defines exactly one notion of sameness: the primary key. Java, however, defines both object identity
a==b and object equality a. equals(b) .
Associations
Associations are represented as unidirectional references in Object Oriented languages whereas RDBMSs use
the notion of foreign keys. If you need bidirectional relationships in Java, you must define the association twice.
Likewise, you cannot determine the multiplicity of a relationship by looking at the object domain model.
Data navigation
The way you access data in Java is fundamentally different than the way you do it in a relational database. In
Java, you navigate from one association to an other walking the object network.
There are two sections that check if the attribute type is a mapping.
The first section defines an ID field (the ID of the mapped class will go there when we load it).
The second section is the actual code for getting the object.
It checks whether the object is null, if it is null it loads the object and saves it for later (by creating a session object and simply calling Select), however if it is still null it creates a default object.
All of these O/R mappings usually live and die by whether they are flexible enough in their caching policies, and most of them are not. We've actually tried hard in .NET to make sure that the caching policy can be entirely under your control, or entirely non-existent.
In many cases, you just want to fire up a query and suck down the results. You'd like to use the results as objects, but you don't want the infrastructure to try to cache them so that if you ask for that object again you get the same exact object.
A lot of systems can only operate that way, and as a result, they have horrible performance overheads that you often just don't need. On a middle-tier, for example, you quite often don't care about caching, because you're just serving some incoming HTTP request that's immediately going to go away thereafter. So why cache?