I have several objects, like products, order, etc. When I get information from my database I take a row and create one of the types of objects. I then work with that object created. I read this is called a factory.
Is there some advantage to doing this? Especially in a loosely typed language like PHP?
Thanks
edit: is this where I get database agnosticity? Is this what an ORM essentially does?
By creating your objects from the database queries, you are defining the mapping between your objects and the relational database. This is exactly what ORM software does.
By doing so and ensuring that your objects never directly access the database, but instead use your database-access functions/objects, you are protecting your code from changes in two ways:
Changes to your database schema will not ripple through your code. Instead, the code changes will be located only in your database access objects.
You can switch to a different DBMS by implementing a new database layer that follows the same interface as the original. Your other objects will not require changes.
I guess in that sense, you gain some database-agnosticity, but you'll probably be better off using a database library that provides that agnosticity out of the box.
In my opinion, the advantage is you are working with objects and gain all of the advantages that an object-oriented language offers. You can then read the domain logic at a higher level (in terms of the objects you have defined) without sifting through database queries. Writing the ORM yourself can be tough, but there are tools out there that help with that.
This is the route I normally take, but I don't do any PHP development, so I can't say how well it applies to that language.
What you're describing is an implementation of a Data Access Layer - it doesn't sound like an example of the Factory Method pattern, nor the Abstract Factory pattern.
Yes, ORMs bridge the gap from objects to relational databases, and can serve as your Data Access Layer. Bear in mind, any ORM you use has certain pros/cons/limitations. Depending on your experience and requirements, writing your own data access layer is sometimes a good idea; don't feel like you HAVE to use a 3rd-party ORM.
Yes, a good data access layer makes it easy to swap out your storage mechanism (different database, XML, flat files, whatever) without changing your business logic, UI, or other code.
Regardless of loose-typed or strong-typed languages, if you're working in an OO language, it will be much easier to write code using data objects (provided by an ORM or homegrown data access layer). I'm sure it's possible to write a system with no data access layer, where your business layer works directly with the database. But it will likely be more challenging to implement and maintain.
Related
I am learning some patterns, Unity of work / repository... There are some examples on web, but no one connects to more than one database.
In my applications almost always I have the need to get some object from a database (for example users) and some other object from another, how can I use the patterns ? (Since I am a novice on this subject an explicit example is a must)
Thank you!
As a general reference I advise you and anyone interested to visit http://martinfowler.com/eaaCatalog/index.html
which has a collection of UML and explanation over the most common Design Pattern for enterprises software
In your specific case Unity of work is particularly suited to work along with Data Mapper and Identity Map. I guess to understand 100% unity of work one must master also the other 2 pattern.
To answer your question I think you can create a unity of work and save it in a registry, so it is available all over the application. The unity must be a singleton since you need to ensure a central gateway to communicate with the database. Inside your unity of work you will have an identity map which is a collection of valued Objects in memory representing your model which is responsible to maintain the object states during all the application's operations. The unity will be used by your service layer to perform CRUD operations over the model and commit these changes.
To work with more databases I guess you need to leverage some sort of namespaced access to the object stored in the Identity map. You have the choice where to namespace: unity of work or identity map. The decision is really up to your application and use cases. You might need to connect to different DBs for splitting responsibilities between read and write or trying to integrate heterogeneous data sources.
An alternative would be to inject the DB object into the unity of work methods, in this case the application has 100% control over which database is used.
The repository pattern as far as I understand helps you to abstract to the storage of you model and it is particularly useful when you are working with heterogeneous data sources of you must provide such a flexibility to your application. Therefore I guess it is quite different from unity of work and Data Mapper layer.
I created for a project a single class, that contains all access code to the database.
Is this a good practice , under the assumption that this class doesn't contain any logic, or should i use several classes? If yes, how should i partition my code? I use C# .Net.
Actually Under the concept of MVC framework, it is a good practice to create a different class for database access, seperate class for logic and seperate class for your views.
You are doing good if you are writing a seperate class for database access under the assumption that it does not contain any logic.
In Agile Developement there is a term named as Database Encapsulation Layers.
A database encapsulation layer hides the implementation details of your database, including their physical schemas, from your business code. In effect this layer provides your business objects with persistence services – the ability to read data from, write data to, and delete data from – data sources. Ideally your business objects should know nothing about how they are persisted, it just happens. Database encapsulation layers aren’t magic and they aren’t academic theories; database encapsulation layers are commonly used practice by both large and small applications as well as in both simple and complex applications. Database encapsulation layers are an important technique that every agile software developer should be aware of and be prepared to use.
An effective database encapsulation layer will provide several benefits:
-> It reduces the coupling between your object schema and your data schema, increasing your ability to evolve either one.
-> It implements all database-related code in one place.
-> It simplifies the job of application programmers.
-> It allows application programmers to focus on the business problem and Agile DBA(s) can focus on the database.
-> It gives you a common place to implement data-oriented business rules and logic.
-> It takes advantage of specific database features, increasing application performance.
Hope this helps.
If your database is quite small, say, only a couple of tables, you could write all your queries in one class. otherwise I would suggest that per Entity/Table one class. for example, StudentDao.class will only focus on the queries to database table "STUDENT", and TeacherDao.class will only contain queries to table "TEACHER". if you are gonna implement a complex business logic, you may want to have a service class, to weave StudentDao and TeacherDao together.
Unless your data access is very simple, probably not.
you probably shouldn't need to write this code yourself. Take a look at some Object Relational Mapping tools. NHibernate is a popular .Net solution. http://en.wikipedia.org/wiki/NHibernate
If you really do want to write it yourself look up design patterns in this area, like the Data Transfer Object pattern. http://martinfowler.com/eaaCatalog/dataTransferObject.html
These are some of the suggestions while accessing database.
1.) Always keep your database access parameters in a properties file. Use a handler to get those data. Because when you change your database then you need not change your code just make a change in the properties file it's enough.
-- So here you need a handler class.
2.) Never create a single class (a god class) which performs all the actions. Disperse your behaviour in to different classes depending on the intent. For example Keep all read behavior in one class, Write behavior in another class ... so on.
3.) You can create a class which deals with connection creations and pooling stuff...
Hope this helps.
I'm working on an application for one of our departments that contains medical data. It interfaces with a third party system that we have here.
The object itself (a claim) isn't terribly complex, but due to the nature of the data and the organization of the database, retrieving the claim data is very complex. I cannot simply join all the tables together and get the data. I need to do a "base" query to get the basics of the claim, and then piece together supplemental data about the claim based on various issues.
Would it be better to when working with this data:
Generate the object in a stored procedure, where all of the relevant data is readily available, and iterate through a table variable (using SQL Server 2005) to piece together all the supplemental information.
Generate the object in the data access layer, where I have a little more powerful data manipulation at my disposal, and make a bunch of quick and simple calls to retrieve the lookup data.
Use an OR/M tool and map out all the complex situations to generate the object.
Something else.
EDIT: Just to clarify some of the issues listed below. The complexity really isn't a business issue. If a claim as a type code of "UB", then I have to pull some of the supplemental data from Table X. If the claim has a type code of "HCFA", then I have to pull some of the data from Table Y. It is those types of things. I hope this helps.
One more vote for stored procedures in this case.
What you are trying to model is a very specific piece of business logic ("what is a claim") that needs to be consistent across any application that deals with the concept of a claim.
If you only ever have one application, or multiple applications using the same middleware, you can put that in the client code; however, practice shows that databases tend to outlive software that accesses them.
You do not want to wind up in a situation where subtle bugs and corner cases in redundant implementations make different applications see the data in slightly different ways. DRY, and all that.
I would use a stored procedure for security reasons. You don't have to give SELECT privileges to the claims tables that you are using, which sound somewhat important. You only have to give the user access to that stored procedure. If the database user already has SELECT privileges on the tables, I don't see anything wrong with generating the object in the data access layer either. Just be consistent with whatever option you choose. If you are using stored procedures elsewhere, continue to use them here. The same applies to generating the objects in the data access layer.
Push decisions/business logic as high up in your applications code hierarchy as possible. ORMs/stored procedures are fine but cannot be as efficient as hand written queries. The higher up in your code you go the more you know what the data will be used for and have the information to intelligently get it.
I'm not a fan of pushing business logic down to the persistence layer, so I wouldn't recommend option 1. The approach I'd take involves having a well-defined program object that models the underlying database entity, so ORM oriented, but your option 3 sounds like you're thinking of it as an onerous mapping task, which I really don't. I'd just have the logic necessary for loading up whatever you're concerned about with this object set up in methods on the program object modeling it.
As a general rule, I use a data access layer just to retrieve data (possibly from different sources) and return it in a meaningful manner.
Anything that requires business rules or logic (decisions) goes in my business layer.
I do not deviate from that choice lightly*.
It sounds like the claim you are generating is really a view of data stored in various places, without any decisions or business logic. If that's the case, I would tend to manage access to that data in the data layer.
**I'll never forget one huge system I worked on that got very over-complicated because the only person available to work on a central piece was an expert at stored procedures... so lots of the business logic ended up there.*
Think of the different ways you're planning to consume the data. The whole purpose of an application layer is to make your life easier. If it doesn't, I agree with #hoffmandirt that it's safer in the database.
Stored procedures are bad, m'kay?
It sounds like views would be better than stored procedures in this case.
If you are using .NET, I would highly recommend going with an ORM to get support for Linq.
In general, spreading business logic between the database and application code is not a good idea.
In the end, any solution will likely work. You aren't facing a make or break type decision. Just get moving, don't get hung up on this kind of issue.
What is the best practice of introducing custom (typically volatile) data into entity model classes? This may sound like a bad practice first, but it seems to be quite a common scenario. In our recent web application we have developed a proper model and in most cases we are fine with loading model entities. But there are cases where we cannot afford loading an entire hierarchy of entities; we need to load, say, results of a couple of SQL COUNT’s or possibly some additional information alongside (or embedded inside) the model entities. So basically, the requirements and conditions are:
It’s a web application where 99.9999999999% of all operations are read operations.
They don’t need to process or do any complicated business logic. We just need to get data quickly to HTML.
In several performance critical cases, we need to load results of SQL aggregates which don’t fit any model properties.
We need an extensible way to introduce any new custom data if needed.
How do you usually solve this issue without working too much around your ORM (for instance raw data from db)? I’m sure this has been discussed many times, but I cannot figure out a good Google query to find anything useful.
Edit: Since I later realized the question was not very well formed, I decided to reformulate it and start a new one.
If you're just getting relational data to and from a browser, with little or no behavior in between, it sounds like your trying to solve a relational problem with an OO paradigm.
I might be inclined to dispense with the Object Oriented approach altogether.
Me team recently rewrote an application by asking "What is the simplest thing that can possibly work?" and "What is the closest language to the problem?". Our new app, replacing an OO one, ended up being 10 times smaller, faster, and cheaper.
We used SQL, stored procedures, XML libraries on the DB server, XSLT (to get the HTML), and javascript.
OOP purist like myself would go to the Decorator pattern.
http://en.wikipedia.org/wiki/Decorator_pattern
But the thing is, some people may not need the flexibility it offers. Plus, creating new classes for each distinct operation may seem overkill, but it provide good compile type checking.
The best practice in my view is that your application consumes data using the Domain Model pattern. The Domain Model can offer business-logic methods for doing the type of queries that make sense and are relevant to your application needs.
These can fetch "live" results that map directly to database rows and can therefore be edited and "saved."
But additionally, the Domain Model can provide methods that fetch read-only results that are too complex to be easily saved back to the database. This includes your example of grouped aggregate query results, and also includes joined query result sets, expressions as columns, etc.
The Domain Model pattern offers a way to decouple the OO design of an application from the design of the physical database.
Is LINQ a kind of Object-Relational Mapper?
LINQ in itself is a set of language extensions to aid querying, readability and reduce code. LINQ to SQL is a kind of OR Mapper, but it isn't particularly powerful. The Entity Framework is often referred to as an OR Mapper, but it does quite a lot more.
There are several other LINQ to X implementations around, including LINQ to NHibernate and LINQ to LLBLGenPro that offer OR Mapping and supporting frameworks in a broadly similar fashion to the Entity Framework.
If you are just learning LINQ though, I'd recommend you stick to LINQ to Objects to get a feel for it, rather than diving into one of the more complicated flavours :-)
LINQ is not an ORM at all. LINQ is a way of querying "stuff", and can be more or less seen as a SQL-like language extension for different things (IEnumerables).
There are various types of "stuff" that can be queried, among them SQL Server databases. This is called LINQ-to-SQL. The way it works is that it generates (implicit) classes based on the structure of the DB and your query. In this sense it works much more like a code generator.
LINQ-to-SQL is not an ORM because it doesn't try at all to solve the object-relational impedance mismatch. In an ORM you design the classes and then either map them manually to tables or let the ORM generate the database. If you then change the database for whatever reason (typically refactoring, renormalization, denormalization), many times you are able to keep the classes as they are by changing the mapping.
LINQ-to-SQL does nothing of the sort. Your LINQ queries will be tightly coupled to the database structure. If you change the DB, you will probably have to change the LINQ as well.
LINQ to SQL (part of Visual Studio 2008) is an OR Mapper.
LINQ is a new query language that can be used to query many different types of sources.
LINQ itself is not a ORM. LINQ is the language features and methods that exist in allowing you to query objects like SQL.
"LINQ to SQL" is a provider that allows us to use LINQ against SQL strongly-typed objects.
I think a good test to ascertain whether a platform or code block displays the characteristics of an O/R-M is simply:
With his solution hat on, does the developer(s) (or his/her code generator) have any direct, unabstracted knowledge of what's inside the database?
With this criterion, the answer for differing LINQ implementations can be
Yes, knowledge of the database schema is entirely contained within the roll-your-own, LINQ utilizing O/R-M code layerorNo, knowledge of the database schema is scattered throughout the application
Further, I'd extend this characterization to three simple levels of O/R-M.
1. Abandonment.
It's a small app w/ a couple of developers and the object/data model isn't that complex and doesn't change very often. The small dev team can stay on top of it.
2. Roll your own in the data access layer.
With some managable refactoring in a data access layer, the desired O/R-M functionality can be effected in an intermediate layer by the relatively small dev team. Enough to keep the entire team on the same page.
3. Enterprise-level O/R-M specification defining/overhead introducing tools.
At some level of complexity, the need to keep all devs on the same page just swamps any overhead introduced by the formality. No need to reinvent the wheel at this level of complexity. N-hibernate or the (rough) V1.0 Entity Framework are examples of this scale.
For a richer classification, from which I borrowed and simplified, see Ted Neward's classic post at
http://blogs.tedneward.com/2006/06/26/The+Vietnam+Of+Computer+Science.aspx
where he classifies O/R-M treatments (or abdications) as
1. Abandonment. Developers simply give up on objects entirely, and return to a programming model that doesn't create the object/relational impedance mismatch. While distasteful, in certain scenarios an object-oriented approach creates more overhead than it saves, and the ROI simply isn't there to justify the cost of creating a rich domain model. ([Fowler] talks about this to some depth.) This eliminates the problem quite neatly, because if there are no objects, there is no impedance mismatch.
2. Wholehearted acceptance. Developers simply give up on relational storage entirely, and use a storage model that fits the way their languages of choice look at the world. Object-storage systems, such as the db4o project, solve the problem neatly by storing objects directly to disk, eliminating many (but not all) of the aforementioned issues; there is no "second schema", for example, because the only schema used is that of the object definitions themselves. While many DBAs will faint dead away at the thought, in an increasingly service-oriented world, which eschews the idea of direct data access but instead requires all access go through the service gateway thus encapsulating the storage mechanism away from prying eyes, it becomes entirely feasible to imagine developers storing data in a form that's much easier for them to use, rather than DBAs.
3. Manual mapping. Developers simply accept that it's not such a hard problem to solve manually after all, and write straight relational-access code to return relations to the language, access the tuples, and populate objects as necessary. In many cases, this code might even be automatically generated by a tool examining database metadata, eliminating some of the principal criticism of this approach (that being, "It's too much code to write and maintain").
4. Acceptance of O/R-M limitations. Developers simply accept that there is no way to efficiently and easily close the loop on the O/R mismatch, and use an O/R-M to solve 80% (or 50% or 95%, or whatever percentage seems appropriate) of the problem and make use of SQL and relational-based access (such as "raw" JDBC or ADO.NET) to carry them past those areas where an O/R-M would create problems. Doing so carries its own fair share of risks, however, as developers using an O/R-M must be aware of any caching the O/R-M solution does within it, because the "raw" relational access will clearly not be able to take advantage of that caching layer.
5. Integration of relational concepts into the languages. Developers simply accept that this is a problem that should be solved by the language, not by a library or framework. For the last decade or more, the emphasis on solutions to the O/R problem have focused on trying to bring objects closer to the database, so that developers can focus exclusively on programming in a single paradigm (that paradigm being, of course, objects). Over the last several years, however, interest in "scripting" languages with far stronger set and list support, like Ruby, has sparked the idea that perhaps another solution is appropriate: bring relational concepts (which, at heart, are set-based) into mainstream programming languages, making it easier to bridge the gap between "sets" and "objects". Work in this space has thus far been limited, constrained mostly to research projects and/or "fringe" languages, but several interesting efforts are gaining visibility within the community, such as functional/object hybrid languages like Scala or F#, as well as direct integration into traditional O-O languages, such as the LINQ project from Microsoft for C# and Visual Basic. One such effort that failed, unfortunately, was the SQL/J strategy; even there, the approach was limited, not seeking to incorporate sets into Java, but simply allow for embedded SQL calls to be preprocessed and translated into JDBC code by a translator.
6. Integration of relational concepts into frameworks. Developers simply accept that this problem is solvable, but only with a change of perspective. Instead of relying on language or library designers to solve this problem, developers take a different view of "objects" that is more relational in nature, building domain frameworks that are more directly built around relational constructs. For example, instead of creating a Person class that holds its instance data directly in fields inside the object, developers create a Person class that holds its instance data in a RowSet (Java) or DataSet (C#) instance, which can be assembled with other RowSets/DataSets into an easy-to-ship block of data for update against the database, or unpacked from the database into the individual objects.
Linq To SQL using the dbml designer yes, otherwise Linq is just a set of extension methods for Enumerables.