I am using spring data JDBC.
I normally use the specific repository object as auto-wired and perform the necessary operation.
Let us consider, I have employees who belong to a specific continent.
We have a repository for each continent.
After retrieving data from employee table, based on his continent value, need to initialize the specific continent reporisotory.
Can you please guide me on how to create a repository object dynamically?
To at least hint to an answer for the verbatim question:
Take a look at JdbcRepositoryFactoryBean and JdbcRepositoryFactoryBeanUnitTest.
But I don't think this would solve your problem nor would anything in that direction.
What you might find helpful though is JdbcAggregateTemplate. It is hard to tell since you share very little about what you actually want to achieve.
In general Spring Data is not build for data models that are self referencing, i.e. where you obtain table or column names from the data model itself at runtime. In such cases it is probably better to create your own repository implementation, which takes your special use case into account but is limited to the exact features you need which very often is sufficiently limited to be maintainable.
Related
Just curious if anyone knows why Room requires you to list out each entity. Why can't it automatically find all of your entities with the #Entity annotation?
Since you can have more than a single database in a project, Room needs to know which classes are used by which DB.
By declaring the Entities in the DB class you are actually building a hierarchy that informs the compiler which classes to use to produce the wanted result from the DAO.
In theory, your argument does have a point as in cases of a single DB or where there are multi DB but no overlaps there should not be a problem but to prevent overlaps and for clarity sake, they demand that you declare everything.
What I see a lot is that people use a Object Relational Mapper (ORM) for doing SQL stuff when working in a MVC environment. But if i really have complex queries I would like to write this whole query myself. What is the best practice for this kind of situation?
Having a Abstraction Layer between your model and the database with the complex queries
Still using the model with creating specific methodes that handle the queries
Or is there any other way that might be better? please tell me :)
Consider the Single Responsibility Principle. Specifically, the question would be...
"If I put data access logic in my model, what will that mean when I need to change something?"
Any time you need to change business logic, you're also changing the objects which maintain data access logic. So the data access logic also needs to be re-tested. Conversely, any time you need to change data access logic, you're also changing the objects which maintain business logic. So the business logic also needs to be re-tested.
As the logic expands, this becomes more difficult very quickly.
The idea behind the Single Responsibility Principle is to separate the dependencies of different roles which can enact changes to the application. (Keep in mind that "roles" doesn't map 1-to-1 with "people." One person may have multiple roles, but it's still important to separate those roles.) It's a matter of simpler support. If you want to make a change to a database query (say, for performance reasons) which shouldn't have any visible affect on anything else in the system, then there's no reason to be changing objects which contain business logic.
1. Having a Abstraction Layer between your model and the database with the complex queries
Yes, you should have a persistence abstraction that sits between storage (database or any other data source) and you business logic. Your business logic should not depend on "where", "how" and even "if" the data is actually stored.
Basically, your code should (at least - try to) adhere to SOLID principles, but as #david already pointed out: you are already violating the first on on that list.
Also, you should consider using a service layer which would be responsible for dealing with interaction between implementation of domain model and your persistence abstraction (doesn't matter whether you are using custom written data mappers or some 3rd party ORM).
In the article (more like excerpt, actually) the "MVC model" is actually all three concentric circles together. Domain model is not code. It actually is trm that describs the accumulated knowledge about the project. Most of domain model gets turned into pieces of code. Those pieces are referred to as domain objects.
2. Still using the model with creating specific methodes that handle the queries
This would imply implementation of active record. It is useful, but mostly misused pattern, for cases when your objects have no (or almost none) business logic. Basically - you should use active record only if all you need are glorified setter an getters, that talk to database.
Active record pattern is a very good choice when you need to quickly prototype something, but it should not be used, when you are attempting to implement fully realized model layer.
ORM's in general do not specifically have any drawbacks versus using direct SQL to fetch data from the database. ORM's as the name implies help in keeping your Relational model (designed using your SQL DDL's or using JPA annotations) and OO model in sync and help them integrate well together.
When using a ORM, you can write your queries in JPQL which is Object oriented SQL. So instead of writing queries that manipulate tables, you are writing queries that manipulate objects. You use the relationships between these objects to get your desired result. Now I understand that sometimes its easier to just write Native SQL, so the JPA specification allows you to run native sql! This just returns you list of "Generic Objects" which you can organize any way you like. When you choose to go this route and actually pick a JPA provider, like Hibernate, these providers have extended functionalities. So if you do have complex relationships you can use libraries like Hibernate Criteria Builder to help you create queries for those complex relationships.
So, if building a large MVC application, it would generally be a good idea to have this abstraction layer in the middle - handling all these relationships. It makes it easier on you the developer to just look at the big picture and the business side of the application.
Imho, no. I think, even the ORM layer adds often more complexity as needed. The databases have very good and sophisticated mechanisms for high-level data manipulation. Triggers, views, constraints, complex keying-indexing, (sub)transactions, stored procedures, and procedural extensions of the query language were normally much more as enough for everything.
The ORMs can't give, because of their structural barriers, a real interface to this feature set.
And the common practice is that the applications use practically only a nosql record service from all of this, and implement in an unneeded "middleware" which were the mission of the database.
Which I see really interesting, if the feature set of the databases got some OO-like interface (see "sql abstract types"), and the client-side logic went in the application (see "REST"). This practically eliminated the need of the middle layer.
In our project we're trying to apply the Bounded Context ideology and we've faced kind of obvious problem of performance. E.g., we have different classes (in different contexts) for representing a user in the system: Person in our core domain's context and User in security context. So, we have two different repositories for each of the aggregate, but they are using the same table in DB and sometimes accessing the same data.
Is there common solution to minimize db roundtrips in this case? Are there ORM's which deals with it, or should we code some caching system by ourselves?
upd: the db is from legacy app, and we'll have to use it "as is"
So, we have two different repositories for each of the aggregate, but
they are using the same table in DB and sometimes accessing the same
data.
The fact that you have two aggregates stored in the same table is an indication of a problem with the design. In this case, it seems you have two bounded contexts - a BC for the core domain (Person is here) and an identity/access BC (User is here). The BCs are related and the latter can be seen as upstream from the former. A Person in the core domain has a corresponding User in the identity BC, but they are not exactly the same thing.
Beyond this relationship between the BCs there are questions regarding ownership of behavior. For example, both a Person and a User may have a name and what is to be determined is who own's the behavior of changing a name. This can be implemented in several ways. Person may have its own name and changes should be propagated to the identity BC. Similarly, User may own changes to name, in which case they must be propagated to Person via a synchronization mechanism.
Overall, your problem could be addressed in two ways. First, you can store Person and User aggregates in different tables. Any given query should only use one of these tables and they can be synchronized in an eventually consistent matter. Another approach is to decouple the behavioral domain model from a model designed for queries (read-model). This way, you can create a read-model designed to serve a specific screen(s) and have a customized query, perhaps even outside of an ORM.
If all the Users are Person too (sometimes external services are modeled as special users too), the only data that User and Person should share on the database are their identifiers.
Indeed each entity in a domain model should hold references only to the data that they need to ensure their invariants.
Moreover I guess that Users are identified by Username and Persons are identified by something else (VAT code or so..).
Thus, the simplest optimization technique is to avoid to encapsulate in an entity those informations that are not required to ensure its invariants.
Furthermore you simply need an effective context mapping technique to easily pass from User to Person when needed. I use shared identifiers for this.
As an example you can expose the Person's identifier in the User class, so that a simple query to the Person's repository can provide you the data you need.
Finally I suggest you the Vaughn Vernon series on Aggregate Root Design.
For application developers, I suppose the traditional paradigm for writing an application with domain objects that can be persisted to an underlying data store (SQL database for arguments sake), is to write the domain objects and then write (or generate) the table structure. There is a tight coupling between what the domain object looks like and what the structure of underlying data store looks like. So if you want to add a piece of information to your domain object, you add the field to your code and then add a column to the appropriate database table. All familiar?
This is all well and good for data stores that have a well defined structure (I'm mainly talking about SQL databases whereby the tables and columns are pre-defined and fixed), but now a number of alternatives to the ubiquitous SQL database exist and these often do not constrain the data in this way. For instance, MongoDB is a NoSQL database whereby you divide data into collections but aside from that there is no structuring of the data. You don't define new columns when you want to add a new field.
Now to the question: given the flexibility of a data store like MongoDB, how would one go about achieving a similar kind of flexibility in the domain objects that represent this data? So for instance if I'm using Spring and creating my own domain obejcts, when I add a "middleName" field to my data, how can I avoid having to add a "middleName" field to my domain object? I'm looking for some kind of mechanism/approach/framework to dynamically inspect the data and have access to it in my domain object without having to make a code change every time. All ideas welcome.
I think you have a couple of choices:
You can use a dynamic programming language and not have domain objects (clojure for example)
If you're fixed on using java, the mongo java driver returns data in DBObject which is essentially a Map. So the default behavior already provides what you want. It's only when you map the DBObject into domain objects, using a library like morphia (or spring-data), that you even have to worry about domain objects at all.
But, if I was using java, I would stick with the standard convention of domain objects mapped via morphia, because I think adding a field is a very minor inconvenience when compared against the benefits.
I think the question is inherintly paradoxical-
On one hand, you want to have domain objects, i.e. objects that represent the data (and behaviour) of your problem domain.
On the other hand, you say that you don't want your domain objects to be explicitly influenced by changes to the data.
But when you have objects that represent your problem domain, you want to do just that- to represent your problem domain.
So that if, for example, middle name is added, then your representation of the real-life 'User' entity should change to accomodate this change to the real-life user; perhaps not only by adding this piece of data to your object, but also adding some related behaviour (validation of middle name, or some functionality related to it).
In essense, what I'm trying to say here is that when you have (classic OO) domain objects, you may need to change your behaviour / functionality along with your data, and since you don't have any automatic way of changing your behaviour, the question of automatically changing your data becomes irrelevant.
If you don't want behaviour associated with your data, then you essentialy have DTOs, and #Kevin's answer is what you're looking for.
Honestly, it sounds more like you're looking for some kind of blackbox DTO where, like you describe, fields are added or removed "arbitrarily" depending on the data. This makes me inclined to suggest a simple Map to do the job. You can't really have a domain-driven design if your domain model is constantly changing.
I am building a DataAccess layer to a DB, what data structure is recommended to use to pass and return a collection?
I use a list of data access objects mapped to the db tables.
I'm not sure what language you're using, but in general, there are tradeoffs of simplicity vs extensibility.
If you return the DataSet directly, you have now coupled yourself to database specific classes. This leaves little room for extension - what if you allow access to files or to other types of data sources? But, it is also very simple. This is the recordset pattern and C#/VB provide a lot of built-in support for this. The GUI layer can access the recordset and easily manipulate the data. This works well for simple applications.
On the other hand, you can wrap the datasets in a custom object, and provide gateway methods (see the Gateway pattern http://martinfowler.com/eaaCatalog/gateway.html). This method is more complex, but provides a lot more extensibility. In a larger application when you need to separate the the business logic, data logic, and GUI logic, this is a more robust way to go.
For larger enterprise applications, you can look into using Object Relational Mapping tools (ORM). They help to automatically map java objects to database tables. They hide a lot of the painful SQL details. Frameworks such as Spring provide excellent support for ORMs.
I tend to use arrays of objects, so that I can disconnect the DAO from the business logic.
You can store the data in the DAO as a dataset, for example, and give them an easy way to add to the database before doing an update, so they can pass in information to do modification operations, and then when they want to commit the changes they can do it in one shot.
I prefer that the user can't add/modify the structure themselves, as it makes it harder to determine what must be changed in the database.
By initially returning an array they can then display what is in the database.
Then, as the presentation layer makes changes, the DAO can be updated by the controller. By having a loose coupling the entire system becomes more flexible, as you can change the DAO from a dataset to something else, and the rest of the application doesn't care.
There are two choices that are the most generic.
The first way to look at a ResultSet is as a List of Maps, where each Map represents a row in the ResultSet. The keys are the columns listed in the FROM clause; the values are the database values.
The second way to look at a ResultSet is as a Map of Lists, where each List represents a column in the ResultSet. The Map keys are the columns listed in the FROM clause; the values are the List of database values.
If you don't want to do full-blown ORM, these can carry you a long way.