I'm currently porting a massive, ancient, Oracle Forms app over to JSF & I need to make decisions on the domain model.
I'm locked in to using the Spring JDBC templates(no ORM) and utilizing a DAO layer to deal with baffling legacy database schema, which must have been desined by 1st year co-ops. For the domain model I would really like to make things highly OO, for instance: presume there is a domain object Plan. The goal would be too OO-ify it be able to do PlanInstance.load(byId("12345")), PlanInstance.save(), .delete(), .create(), etc etc. But then the situation arises; because these domain objects contain references to stateful beans(like Repositories for instance), then they can't be Serialized. How does one overcome this?
Initially I started splitting things up like: PlanData(Statefull, SessionScoped) which is used by PlanManager(Stateless, Singleton). This way the common controller code is extracted and is prevented from being duplicated in each session scoped bean, and most importantly allows the session scoped beans to be serialized.
At this point I really need to structure it OO style to minimize complexity, but I just don't know how I can have an object in session scope when it has references to stateful objects(due to serialization errors).
The only possibility I can think of is makeing the stateful refs transient & devising some sort of mechanism to re-inject the dependancies when a bean is un-serialized. Can any one provide me with any insight into solutions to this dilemma? There must be some sort of pattern/practice that solves which I am probably just missing.
I would keep the state and management of that state separate (i.e. Plan vs PlanManager.) By using the data access pattern (PlanManager), you keep the door open to using ORM later, (say) should the db schema be reworked in future. Putting state and state management together in the same class (PlanInstance) goes against the OO principle of single responsibility.
The stateful session scoped beans are not themselves serialized (at least not to store in your persistent store - but you might serialize them to support session fail over). The controller and session beans maintain references to your data beans.
The stateful beans decide when to load, invoking logic, change state and save your data objects. They provide the context for your domain objects. In some designs (often cited as the Anemic Domain Model) the domain objects have no behaviour, and all the logic exists in stateless services. If I understand correctly, you want encapsulation of state and behaviour in your domain objects, and that the domain objects need to use stateful session beans to perform their work. Where possible, try to factor the functionality in the domain objects to not rely upon session state (will make testing simpler), or to push that functionality out into a service bean that is invoked with the appropriate session state. If you have no choice but to use references to stateful beans from your domain model behaviour, the stateful beans can provide the necessary state/repository references as parameters to method calls on your domain objects. That way, the domain objects are still stateless, but can implement domain logic using stateful beans.
All the while, consider the single responsibility of the domain object. At some point it may become clear that the domain logic can be split into layers (say, low-level and higher-level logic) which may make the need for stateful beans in the domain objects unnecessary.
Related
In my limited experience, I've been told repeatedly that you should not pass around entities to the front end or via rest, but instead to use a DTO.
Doesn't Spring Data Rest do exactly this? I've looked briefly into projections, but those seem to just limit the data that is being returned, and still expecting an entity as a parameter to a post method to save to the database. Am I missing something here, or am I (and my coworkers) incorrect in that you should never pass around and entity?
tl;dr
No. DTOs are just one means to decouple the server side domain model from the representation exposed in HTTP resources. You can also use other means of decoupling, which is what Spring Data REST does.
Details
Yes, Spring Data REST inspects the domain model you have on the server side to reason about the way the representations for the resources it exposes will look like. However it applies a couple of crucial concepts that mitigate the problems a naive exposure of domain objects would bring.
Spring Data REST looks for aggregates and by default shapes the representations accordingly.
The fundamental problem with the naive "I throw my domain objects in front of Jackson" is that from the plain entity model, it's very hard to reason about reasonable representation boundaries. Especially entity models derived from database tables have the habit to connect virtually everything to everything. This stems from the fact that important domain concepts like aggregates are simply not present in most persistence technologies (read: especially in relational databases).
However, I'd argue that in this case the "Don't expose your domain model" is more acting on the symptoms of that than the core of the problem. If you design your domain model properly there's a huge overlap between what's beneficial in the domain model and what a good representation looks like to effectively drive that model through state changes. A couple of simple rules:
For every relationship to another entity, ask yourself: couldn't this rather be an id reference. By using an object reference you pull a lot of semantics of the other side of the relationship into your entity. Getting this wrong usually leads entities referring to entities referring to entities, which is a problem on a deeper level. On the representation level this allows you to cut off data, cater consistency scopes etc.
Avoid bi-directional relationships as they're notoriously hard to get right on the update side of things.
Spring Data REST does quite a few things to actually transfer those entity relationships into the proper mechanisms on the HTTP level: links in general and more importantly links to dedicated resources managing those relationships. It does so by inspecting the repositories declared for entities and basically replaces an otherwise necessary inlining of the related entity with a link to an association resource that allows you to manage that relationship explicitly.
That approach usually plays nicely with the consistency guarantees described by DDD aggregates on the HTTP level. PUT requests don't span multiple aggregates by default, which is a good thing as it implies a scope of consistency of the resource matching the concepts of your domain.
There's no point in forcing users into DTOs if that DTO just duplicates the fields of the domain object.
You can introduce as many DTOs for your domain objects as you like. In most of the cases, the fields captured in the domain object will reflect into the representation in some way. I have yet to see the entity Customer containing a firstname, lastname and emailAddress property, and those being completely irrelevant in the representation.
The introduction of DTOs doesn't guarantee a decoupling by no means. I've seen way too many projects where they where introduced for cargo-culting reasons, simply duplicated all fields of the entity backing them and by that just caused additional effort because every new field had to be added to the DTOs as well. But hey, decoupling! Not. ¯\_(ツ)_/¯
That said, there are of course situations where you'd want to slightly tweak the representation of those properties, especially if you use strongly typed value objects for e.g. an EmailAddress (good!) but still want to render this as a plain String in JSON. But by no means is that a problem: Spring Data REST uses Jackson under the covers which offers you a wide variety of means to tweak the representation — annotations, mixins to keep the annotations outside your domain types, custom serializers etc. So there is a mapping layer in between.
Not using DTOs by default is not a bad thing per se. Just imagine the outcry by users about the amount of boilerplate necessary if we required DTOs to be written for everything! A DTO is just one means to an end. If that end can be achieved in a different way (and it usually can), why insist on DTOs?
Just don't use Spring Data REST where it doesn't fit your requirements.
Continuing on the customization efforts it's worth noticing that Spring Data REST exists to cover exactly the parts of the API, that just follow the basic REST API implementation patterns it implements. And that functionality is in place to give you more time to think about
How to shape your domain model
Which parts of your API are better expressed through hypermedia driven interactions.
Here's a slide from the talk I gave at SpringOne Platform 2016 that summarizes the situation.
The complete slide deck can be found here. There's also a recording of the talk available on InfoQ.
Spring Data REST exists for you to be able to focus on the underlined circles. By no means we think you can build a great really API solely by switching Spring Data REST on. We just want to reduce the amount of boilerplate for you to have more time to think about the interesting bits.
Just like Spring Data in general reduces the amount of boilerplate code to be written for standard persistence operations. Nobody would argue you can actually build a real world app from only CRUD operations. But taking the effort out of the boring bits, we allow you to think more intensively about the real domain challenges (and you should actually do that :)).
You can be very selective in overriding certain resources to completely take control of their behavior, including manually mapping the domain types to DTOs if you want. You can also place custom functionality next to what Spring Data REST provides and just hook the two together. Be selective about what you use.
A sample
You can find a slightly advanced example of what I described in Spring RESTBucks, a Spring (Data REST) based implementation of the RESTBucks example in the RESTful Web Services book. It uses Spring Data REST to manage Order instances but tweaks its handling to introduce custom requirements and completely implement the payment part of the story manually.
Spring Data REST enables a very fast way to prototype and create a REST API based on a database structure. We're talking about minutes vs days, when comparing with other programming technologies.
The price you pay for that, is that your REST API is tightly coupled to your database structure. Sometimes, that's a big problem. Sometimes it's not. It depends basically on the quality of your database design and your ability to change it to suit the API user needs.
In short, I consider Spring Data REST as a tool that can save you a lot of time under certain special circumstances. Not as a silver bullet that can be applied to any problem.
We used to use DTOs including the fully traditional layering ( Database, DTO, Repository, Service, Controllers,...) for every entity in our projects. Hopping the DTOs will some day save our life :)
So for a simple City entity which has id,name,country,state we did as below:
City table with id,name,county,.... columns
CityDTO with id,name,county,.... properties ( exactly same as database)
CityRepository with a findCity(id),....
CityService with findCity(id) { CityRepository.findCity(id) }
CityController with findCity(id) { ConvertToJson( CityService.findCity(id)) }
Too many boilerplate codes just to expose a city information to client. As this is a simple entity no business is done at all along these layers, just the objects is passing by.
A change in City entity was starting from database and changed all layers. (For example adding a location property, well because at the end the location property should be exposed to user as json). Adding a findByNameAndCountryAllIgnoringCase method needs all layers be changed changed ( Each layer needs to have new method).
Considering Spring Data Rest ( of course with Spring Data) this is beyond simple!
public interface CityRepository extends CRUDRepository<City, Long> {
City findByNameAndCountryAllIgnoringCase(String name, String country);
}
The city entity is exposed to client with minimum code and still you have control on how the city is exposed. Validation, Security, Object Mapping ... is all there. So you can tweak every thing.
For example, if I want to keep client unaware on city entity property name change (layer separation), well I can use custom Object mapper mentioned https://docs.spring.io/spring-data/rest/docs/3.0.2.RELEASE/reference/html/#customizing-sdr.custom-jackson-deserialization
To summarize
We use the Spring Data Rest as much as possible, in complicated use cases we still can go for traditional layering and let the Service and Controller do some business.
A client/server release is going to publish at least two artifacts. This already decouples client from server. When the server's API is changed, applications do not immediately change. Even if the applications are consuming the JSON directly, they continue to consume the legacy API.
So, the decoupling is already there. The important thing is to think about the various ways a server's API is likely to evolve after it is released.
I primarily work with projects which use DTOs and numerous rigid layers of boilerplate between the server's SQL and the consuming application. Rigid coupling is just as likely in these applications. Often, changing anything in the DB schema requires us to implement a new set of endpoints. Then, we support both sets of endpoints along with the accompanying boilerplate in each layer (Client, DTO, POJO, DTO <-> POJO conversions, Controller, Service, Repository, DAO, JDBC <-> POJO conversion, and SQL).
I'll admit that there is a cost to dynamic code (like spring-data-rest) when doing anything not supported by the framework. For example, our servers need to support a lot of batch insert/update operations. If we only need that custom behavior in a single case, it's certainly easier to implement it without spring-data-rest. In fact, it may be too easy. Those single cases tend to multiply. As the number of DTOs and accompanying code grows, the inconsistencies eventually become extremely burdensome to maintain. In some non-dynamic server implementations, we have hundreds of DTOs and POJOs that are likely no longer used by anything. But, we are forced to continue supporting them as their number grows each month.
With spring-data-rest, we pay the cost of customization early. With our multi-layer hard-coded implementations, we pay it later. Which one is preferred depends on a lot of factors (including the team's knowledge and the expected lifetime of the project). Both types of project can collapse under their own weight. But, over time, I've become more comfortable with implementations (like spring-data-rest without DTOs) that are more dynamic. This is especially true when the project lacks good specifications. Over time, such a project can easily drown in the inconsistencies buried within its sea of boilerplate.
From the Spring documentation I don't see Spring data REST exposes entities, you are the one doing it.
Spring Data projects intend to ease the process of accessing different data sources, but you are the one deciding which layer to expose on Spring Data Rest.
Reorganizing your project will help to solve your issue.
Every #Repository that you create with Spring data represents more a DAO in the sense of design than a Repository. Each one is tightly coupled with a particular Data source you want to reach out to. Say JPA, Mongo, Redis, Cassandra,...
Those layers are meant to return entity representations or projections.
However if you check out the Repository pattern from a design perspective you should have a higher layer of abstraction from those specific DAOs where your app use those DAOs to get info from as many different sources it needs, and builds business specific objects for your app (Those might looks more like your DTOs).
That is probably the layer you want to expose on your Spring Data Rest.
NOTE: I see an answer recommending to return Entity instances only because they have the same properties as the DTO. This is normally a bad practice and in particular is a bad idea in Spring and many other frameworks because they do not return your actual classes, they return proxy wrappers so that they can work some magic like lazy loading of values and the likes.
I need to learn the difference between the type of methods (in term of business logic) that should be inside the Domain, DAO and Service layers objects.
For example, if I am building a small web application to create, edit and delete customers data, as far as I understand inside Domain layer object I should add methods that Get/Set Customers object properties, for example (getName, getDOB, setAddress, setPhone...etc).
Now what I am trying to learn is what methods shall I put in DAO and Service layers objects.
Thanks in advance for your time and efforts.
Speaking generally (not Hibernate or Spring specific):
The DAO layer contains queries and updates to save your domain layer into your datastore (usually a relational DB but doesn't have to be). Use interfaces to abstract your DAO away from the actual datastore. It doesn't happen often, but sometimes you want to change datastores (or use mocks to test your logic), and interfaces make that easier. This would have methods like "save", "getById", etc.
The Service layer typically contains your business logic and orchestrates the interaction between the domain layer and the DAOs. It would have whatever methods make sense for your particular domain, like "verifyBalance", or "calculateTotalMileage".
DAO: "wrapper" methods for "wrapping" JPA or JDBC or SQL or noSQL calls or whatever for accessing DB systems.
Domain: Business logic calls correlated to a single type of entities (domain objects).
Service: Business logic calls correlated to a group of type of entities or to a group of several entities of the same type.
(I'm not sure about English, sorry.......)
It means:
Service layer is "bigger" than Domain layer, is often close to front-end, often calls or uses several domain objects.
Domain objects encapsulate most stuff for one part of the domain (that's why they are called D.O.)
DAO is just sth technical, sometimes needed, sometimes not.
When real domain objects are used, then often "repositories" are used to hide access to database systems, or adding special db functionality or whatever.
front-end --> service method 1 --> d.o. A of type X, d.o. B of type X, List
When you develop an ASP.NET application using the repository pattern, do each of your methods create a new entity container instance (context) with a using block for each method, or do you create a class-level/private instance of the container for use by any of the repository methods until the repository itself is disposed? Other than what I note below, what are the advantages/disadvantages? Is there a way to combine the benefits of each of these that I'm just not seeing? Does your repository implement IDisposable, allowing you to create using blocks for instances of your repo?
Multiple containers (vs. single)
Advantages:
Preventing connections from being auto-closed/disposed (will be closed at the end of the using block).
Helps force you to only pull into memory what you need for a particular view/viewmodel, and in less round-trips (you will get a connection error for anything you attempt to lazy load).
Disadvantages:
Access of child entities within the Controller/View is limited to what you called with Include()
For pages like a dashboard index that shows information gathered from many tables (many different repository method calls), we will add the overhead of creating and disposing many entity containers.
If you are instantiating your context in your repository, then you should always do it locally, and wrap it in a using statement.
If you're using Dependency Injection to inject the context, then let your DI container handle calling dispose on the context when the request is done.
Don't instantiate your context directly as a class member, since this will not dispose of the contexts resources until garbage collection occurs. If you do, then you will need to implement IDipsosable to dispose the context, and make sure that whatever is using your repository properly disposes of your repository.
I, personally, put my context at the class level in my repository. My primary reason for doing so is because a distinct advantage of the repository pattern is that I can easily swap repositories and take advantage of a different backend. Remember - the purpose of the repository pattern is that you provide an interface that provides back data to some client. If you ever switch your data source, or just want to provide a new data source on the fly (via dependency injection), you've created a much more difficult problem if you do this on a per-method level.
Microsoft's MSDN site has good information the repository pattern. Hopefully this helps clarify some things.
I disagree with all four points:
Preventing connections from being auto-closed/disposed (will be closed
at the end of the using block).
In my opinion it doesn't matter if you dispose the context on method level, repository instance level or request level. (You have to dispose the context of course at the end of a single request - either by wrapping the repository method in a using statement or by implementing IDisposable on the repository class (as you proposed) and wrapping the repository instance in a using statement in the controller action or by instantiating the repository in the controller constructor and dispose it in the Dispose override of the controller class - or by instantiating the context when the request begins and diposing it when the request ends (some Dependency Injection containers will help to do this work).) Why should the context be "auto-disposed"? In desktop application it is possible and common to have a context per window/view which might be open for hours.
Helps force you to only pull into memory what you need for a
particular view/viewmodel, and in less round-trips (you will get a
connection error for anything you attempt to lazy load).
Honestly I would enforce this by disabling lazy loading altogether. I don't see any benefit of lazy loading in a web application where the client is disconnected from the server anyway. In your controller actions you always know what you need to load and can use eager or explicit loading. To avoid memory overhead and improve performance, you can always disable change tracking for GET requests because EF can't track changes on a client's web page anyway.
Access of child entities within the Controller/View is limited to what
you called with Include()
Which is rather an advantage than a disadvantage because you don't have the unwished surprises of lazy loading. If you need to populate child entities later in the controller actions, depending on some condition, you could load them through additional repository methods (LoadNavigationProperty or something) with the same or even a new context.
For pages like a dashboard index that shows information gathered from
many tables (many different repository method calls), we will add the
overhead of creating and disposing many entity containers.
Creating contexts - and I don't think we are talking about hundreds or thousands of instances - is a cheap operation. I would call this a very theoretical overhead which doesn't play a role in practice.
I've used both approaches you mentioned in web applications and also the third option, namely to create a single context per request and inject this same context into every repository/service I need in a controller action. They all three worked for me.
Of course if you use multiple contexts you have to be careful to do all the work in the same unit of work to avoid attaching entities to multiple contexts which will lead to well know exceptions. It's usually not a problem to avoid this situations but requires a bit more attention, especially when processing POST requests.
I lately use contexts per request, because it is easier and I just don't see the benefit of having very narrow contexts and I see no reason to use more than one single unit of work for the whole request processing. If I would need multiple contexts - for whatever reason - I could always create specialized methods which act with their own context instead of the "default context" of the request.
In most cases only service classes are managed by spring and are singletons. In some situations, domain code needs injection which won't work unless its managed by spring. That being said, it is advisable and non performance intensive to have all your domain classes as #bean with scope as prototype and anytime you want to do
Person p = new Person();
just do
Person p = ctx.getBean("person");
Any help on the pros and cons would be appreciated.
There is obviously more overhead in obtaining a prototype bean than simply instantiating directly via the new keyword (any dependency injection, lifecycle callbacks, etc. performed by the Spring IoC container). While likely not significant for a single instantiation, if you performed this in a loop, you could see performance issues.
If, however, you need any singleton beans (typically services) or resources (such as a DataSource), then you will prefer to use the prototype bean. Any additional dependencies will be wired in automatically.
Apart from performance considerations, your choice may also depend on your design. If you follow a "traditional" architecture with a service tier and data access objects that perist domain objects, then everything from a Spring point of view is generally stateless. Your services and data access objects are singletons using domain objects that are POJO's. Here you will rarely need a prototype bean.
If on the other hand you follow a more object-oriented approach where an object has a stateless factory (to allow instances to be fetched or created) and the object is then able to persist itself (say with a 'save' method), then nearly all your domain objects may be prototype beans.
As in nearly all decisions, there will be trade-offs and no one right answer.
Im currently trying to design an architecture for my new webapp project that has this kind of concept :
consists of several big modules that are independent from one another, but can still communicate and affecting one another.
For example, i could enable the purchasing module along with production module in my webapp, and let's assume the modules could communicate with one another.
But then i could activate only the purchasing module, but disabling production module in the webapp, just from configuring it, without changing any of the code., and the purchasing module will still work fine (independent from the production module)
Here's what i've been thinking about for the architectural layers to support this kind of application :
The UI Layer
JSF 2.0 + Primefaces widgets
Requestscoped ManagedBean + Flash object to transfer data between pages
The ManagedBean will deal with the UI states, UI validations, but not with the business logic operations
The ManagedBean also has access to the service layer, injected by Spring
ManagedBean could have simple fields (like string, integer, etc), or view models (to encapsulate some related fields), or even the Entity models, which should be a transient object in the beginning, and becoming a detached object once having get in and persisted and get out of a transaction.
These fields combinations could be used based on the situation, and the validations, for example, like the #Required, will be placed in the ManageBean's setter method. The Entity model could have #NotNull or #Size within the fields.
The entities in my thinking is only JPA POJOs with the JPA annotations defining the relationships between the entities, without any behaviours, except those validations defined by the the annotations also.
The Service Layer
This layer will handle the business logic validations and operations
Modularity : Could also call other service layer for other modules where he other modules could be non-existent, if disabled via configuration. Perhaps this can be achieved via nother layer for the communication between modules, or perhaps i could use Spring to inject empty implementations for the disabled modules ?
Input : It can accept Entity models, or plain variables, or view models
Output : The return value could vary from void, Entity, a list of Entities (to be displayed later in a datatable in JSF), and could be plain variables like boolean, string, integer, etc.
In the future, this layer will also provide web services for mobile devices or other kind of language that support web service (i still dont know how, but i think this is possible, even if the method accept objects or entities as the parameters)
Each service object will have DAO instance injected by Spring, and will call the DAO for data operations, like CRUD operations, querying, etc
The DAO Layer
Will have the data operations like CRUD operations, querying (jpql, named query, criteria query, native sql query, stored proecure calls) etc
Input : It can accept Entity models, or plain variables, or view models
Output : The return value could vary from void, Entity, a list of Entities (to be displayed later in a datatable in JSF), and could be plain variables like boolean, string, integer, etc.
Having one DAO for each entity is the norm, but when dealing with multiple tables in a single data operation, i'd have to introduce new DAOs.
Will have the EntityManager injected by Spring
These are the things i have in mind, and with this, i tried doing some googling around these topics, and found out many other stuffs like :
Doman Driven Design (DDD), where the entities could have persisting logics in them ? I think this is also the active record pattern ? Spring roo seems to be generating this kind of model also. It seems to be the opposite of Anemic Domain Model.
The data transfer object (DTO), encapsulating the communication data between layers, avoiding the lazy initialization problems with the unloaded fetchtype lazy hierarchies when using JPA ? Open Session in the View seems to be have it's own PROs and CONs also in solving the lazy exception.
And some would say you dont need the DAO anymore, as described in the spring roo documentation
And with all these matters, please share your thinking my current design when it comes to these :
Speed of development, with me thinking about having less boilerplate because being able to make use of the Entities, converting to-and-from DTOs
Ease of maintenance, with me thinking about having clear separation between ui state/logic, business process logic, data operations layer
Support for the modularization, perhaps using maven with each module as one artifact, depending one another as needed ? <-- this is where it's all very foggy for me
Webservice in the future. I have never tried webservices before, but i can just assume, public methods in the service layers could be exported as webservices, so they could be called from mobile devices, or any other platforms that support webservice call ?
Could you please share your experience in this matter ?
Find an OR Mapper you like and don't devote any more attention to the data layer. That is mostly a solved problem, and most of the attention you devote to that will be reinventing the wheel. Very people write applications whose CRUD needs are so unique that they obviate ORM use these days.
Some of the same advice for the UI - find tools and frameworks rather than spending too much time on all of that, there's a lot of good development wealth in place there.
So, concentrate on the service layer, where the unique nature of your application is really expressed. But we can't really validate or critique your service layer because we don't know anything about the problem you're trying to solve. All of the things you've listed are certainly good approaches for certain problems, certain sets of trade-offs, etc. Without knowing more about what matters (performance / development time / configurability / robustness / clarity), nobody can tell you what the right set of choices is.
On your "output" item - other devices can support communication with your app as long as everything serializes down to a common format, usually XML. Then you just send it over the wire, and rehydrate it on the other end.
Software development, when it is non-trivial is a Wicked Problem. It is likely that much advice that you get would need to be thrown out halfway through your project. I don't generally believe in grand architectures - focus on solving particular problems as well as you can, and if you're lucky, a pattern will emerge that you can take advantage. Anything more is generally hubris.