I'm searching for a solution to model a "can-be" relationship.
E.g.: A User can be Special User.
Any suggestions?
Types for entities can be viewed (results) as one of the following two things:
Relationships
Fields
The types that results in fields are usually seen as functional redundancy, where different rows/records in a table can have the same type. For example, the sex/gender of a user, or access privileges or permission level from a user as well.
If, however, this field has attributes/properties, so we have a new entity. In this case, users would be relating to, for example, address, which may have the street name, house number, among other things. Or, in your case, if Special User has attributes/properties, we have a "Special Users" entity. The cardinality here depends on how many types a user can have, and that takes into account the problem context.
As you say that a user "can be", it means it "can not be" too. You could:
Set a nullable functional redundancy field in Users entity or,
Set an entity "Types of Users" and create a relationship N-N for
"Users". In this case, you would have an intermediate table that
would allow or not the connection between the two entities.
In both approaches you have the ability to add new types of users in the future without effort.
There is a third case, however, referred to as partitioning, where we have types and subtypes of entities. In this case, entities subtypes inherit fields of their super entities. I believe this is not your case here.
If you have any questions, please comment and I will answer.
Related
I am learning about ER modelling about Database systems. My problem is that there is a entity called books,enitity named user and I want to create a borrows relationship between user and book with attribute issue date. I modelled it as described but it was pointed that borrows cannot be a relationship because a same user can borrow a book twice. Can anybody explain me what this is as I am using issue data as an attribute so records in borrows relationship would not collide as I will use PK as userid,bookid and issue date. How can I model this accurately? I am a little confused in this.
In the ER model, entity relations consist of attributes of a single entity set, in which the PK identifies only one entity set. Relationship relations have a composite PK that represents two or more entity sets.
Your question uses a composite PK that represents two entity sets (userid and bookid) and a value set (issue date). Strictly speaking, it's neither an entity relation nor a relationship relation. It's a combination of a relationship relation (two entity keys) and a weak entity set (issue date functions similar to a weak key). If we want to be creative, we might call it a weak relationship.
If I was forced to draw an ER diagram for this, I might present it like this:
The ER model isn't a complete logical model (unlike the relational model) and there are some situations which aren't handled well or at all. This is one of those situations.
As per description, User and Book are the entities.
One user can borrow an instance of book.
Similary, one user can borrow multiple instances of book, whether It can be same
instance or various instances.
So every transaction between the User and Book has the Issue Date.
Neither the user nor the book has the Issue Date.
Here, the relationship between User and Book are Many to Many.
The Bridge table is Transaction. We can name it as Borrow also as per your interest.
Now, The user has one to many transactions.
Every Book has one to many transactions.
Every transaction is a combination of a User and Book.
Note: Since every user can have the same book multiple times and at the same day. So we can have a composite primary key of user_id, book_id and Issue_timestamp as there is a chance of redundancy in the Issue Date in the same combination.
As i know optionality means the minimum cardinality of a relationship which is denoted as optional to optional, mandatory to optional, mandatory to mandatory..
And Participation denoted as bold line and a normal line.
In the Internet some refer participation as the dependency of the entity to the relationship which is also looks like identifying and non identifying relationship.
and some refer it as the minimum cardinality
What is the correct definitions of those relationships and what is the difference..
Let's start with definitions and examples of each of the concepts:
Total and partial participation:
Total participation (indicated by a double or thick association line) means that all the entities in an entity set must participate in the relationship. Partial participation (indicated by a single thin line) means that there can be entities in the entity set that don't participate in the relationship.
Medicine participates totally in the Produce relationship, meaning that Medicine can't exist unless Produced by a Laboratory. In contrast, a Laboratory can exist without Producing Medicine - Laboratory participates partially in the Produce relationsip.
Mandatory and optional roles:
In a relationship, roles can be optional or mandatory. This affects whether a relationship instance can exist without an entity in a given role. Mandatory roles are indicated with a solid association line, optional roles are indicated with a dotted line.
Roles aren't often talked about in database tutorials, but they're an important concept. Consider a marriage - a relationship with two mandatory roles filled by the same entity set. In most relationships, the entity sets also define the roles, but when an entity set appears multiple times in a single relationship, we distinguish them in different roles.
In the example above, a Patient can Purchase Medicine with or without a Prescription. A Purchase can't exist without a Patient and Medicine, but a Prescription is optional (overall, though it may be required in specific cases).
Identifying relationship / weak entity:
A weak entity is an entity that can't be identified by its own attributes and therefore has another entity's key as part of its own. An identifying relationship is the relationship between a weak entity and its parent entity. Both the identifying relationship and the weak entity are indicated with double borders. Weak entity sets must necessarily participate totally in their identifying relationship.
In this example, a Prescription contains LineItems which are identified by the Prescription's key and a line number. In other words, the LineItems table will have a composite key (Prescription_ID, Line_Number).
For examples of non-identifying relationships, see the previous examples. While Medicine participates totally in the Produce relationship, it has its own identity (e.g. a surrogate key, though I didn't indicate it). Note that surrogate keys always imply regular entities.
Mandatory/optional vs total/partial participation
Mandatory or optional roles indicate whether a certain role (with its associated entity set) is required for the relationship to exist. Total or partial participation indicate whether a certain relationship is required for an entity to exist.
Mandatory partial participation: See above: A Laboratory can exist without producing any medicine, but Medicine can't be Produced without a Laboratory.
Mandatory total participation: See above: Medicine can't exist without being Produced, and a Laboratory can't Produce something unspecified.
Optional partial participation: See above: A Prescription can exist without being Purchased, and a Purchase can exist without a Prescription.
That leaves optional total participation, which I had to think about a bit to find an example:
Some Patients Die of an unknown Cause, but a Cause of death can't exist without a Patient Dying of it.
Total/partial participation vs identifying/non-identifying relationships
As I said before, weak entity sets always participate totally in their identifying relationship. See above: a LineItem must be Contained in a Prescription, it's identity and existence depends on that. Partial participation in an identifying relationship isn't possible.
Total participation doesn't imply an identifying relationship - Medicine can't exist without being Produced by a Laboratory but Medicine is identified by its own attributes.
Partial participation in a non-identifying relationship is very common. For example, Medicine can exist without being Purchased, and Medicine is identified by its own attributes.
Mandatory/optional vs identifying/non-identifying relationships
It's unusual for a relationship to have less than two mandatory roles. Identifying relationships are binary relationships, so the parent and child roles will be mandatory - the Contain relationship between Prescription and LineItem can't exist without both entities.
Optional roles are usually only found on ternary and higher relationships (though see the example of patients dying of causes), and aren't involved in identification. An alternative to an optional role is a relationship on a relationship:
By turning Purchase into an associative entity, we can have it participate in a Fill relationship with Prescription. To maintain the same semantics as above I specified that a Purchase can only Fill one Prescription.
Physical modeling
If we translate from conceptual to physical model (skipping logical modeling / further normalization), making separate tables for each entity and relationship, things look pretty similar, though you have to know how to read the cardinality indicators on the foreign key lines to recover the ER semantics.
However, it's common to denormalize tables with the same primary keys, meaning one-to-many relationships are combined with the entity table on the many side:
A relationship is physically represented as two or more entity keys in a table. In this case, the entity keys - patient_id and cause_of_death_id are both found in the Patient table. Many people think the foreign key line represents the relationship, but this comes from confusing the entity-relationship model with the old network data model.
This is a crucial point - in order to understand different kinds of relationships and constraints on relationships, it's essential to understand what relationships are first. Relationships in ER are associations between keys, not between tables. A relationship can have any number of roles of different entity sets, while foreign key constraints enforce a subset constraint between two columns of one entity set. Now, armed with this knowledge, read my whole answer again. ;)
I hope this helps. Feel free to ask questions.
I’m working with Ruby on Rails, but this question applies to application/database model design in general. I want to model many types of people such as User (someone who can log in), Employee, and Customer. Each of these has common attributes like name and email that should be part of a Person superclass. Each type also has other more specific attributes. A Person can be one or more of these roles (someone can be both an employee and a customer).
In code, the appropriate structure seems like a superclass/subclass relationship, but from a database normalization perspective, there should be a Customer table that references the Person table for its common attributes.
I need to decide how to combine these two approaches.
For example, I want to be able to create a Customer by Customer.create(name: “Johnny Appleseed”, favorite_product: widget) and query Employee.where(email: “someone#company.com”), and avoid duplicating Person fields on every role model. That way I can change the way I model a Person without needing to update all the other tables with the same changes.
It would be better if you use Single Table Inheritance.
You can start from this tutorial https://samurails.com/tutorial/single-table-inheritance-with-rails-4-part-1/
Is it possible to have a Unidirectional M:M in Gorm?
e.g.
I have a Person object and I have TravelDestionion object.
A person can have been to many travel destination and some of these travel destinations have of course had many people. But, I never want to navigate from TravelDestination to Person.
Any tips?
You can technically just not access the other side, but Grails is too helpful in this regard. For example when you want to associate a new TravelDestination instance with a Person, you add it to the person's destinations collection (or whatever you named it). But to ensure that both sides are in sync with what the database will look like after calling save, Grails adds the Person to the TravelDestination's persons collection.
This can obviously be very expensive, e.g. with a User <-> Role relationship where 1,000,000 users have ROLE_USER, and one more gets that role, and that user becomes element #1,000,001 in the role's users collection, which gets loaded into memory by Hibernate to ensure uniqueness.
Check out this presentation where I discuss this and provide some performant options for reconfiguring the relationship without the potentially huge overhead of using collections to represent 1-many and many-many in GORM: http://www.infoq.com/presentations/GORM-Performance
I'm attempting to implement DDD for the first time with a ASP.NET MVC project and I'm struggling with a few things.
I have 2 related entities, a Company and a Supplier. My initial thought was that Company was an aggregate root and that Supplier was a value object for Company. So I have a Repository for company and none for Supplier.
But as I have started to build out my app, I ended up needing separate list, create, and update forms for the Supplier. The list was easy I could call Company.Suppliers, and create was horrible I could do Company.Suppliers.Add(supplier), but update is giving me a headache. Since I need just one entity and I can't exactly stick it in memory between forms, I ended up needing to refetch the company and all of the suppliers and find the one I needed to bind to it and again to modified it and persist it back to the db.
I really just needed to do a GetOne if I had a repository for Supplier. I could add some work arounds by adding a GetOneSupplier to my Company or CompanyRepository, but that seems junky.
So, I'm really wondering if it's actually a Value Object, and not a full domain entity itself.
tldr;
Is needing separate list/create/update view/pages a sign that an entity should be it's own root?
Based on your terminology I assume you are performing DDD based on Eric Evans' book. It sounds like you have already identified a problem with your initial go at modeling and you are right on.
You mention you thought of supplier as a Value Object... I suggest it is not. A Value Object is something primarily identified by its properties. For example, the date "September 30th, 2009" is a value object. Why? Because all date instances with a different month/day/year combo are different dates. All date instances with the same month/day/year combo are considered identical. We would never argue over swapping my "September 30th, 2009" for yours because they are the same :-)
An Entity on the other hand is primarily identified by its "ID". For example, bank accounts have IDs - they all have account numbers. If there are two accounts at a bank, each with $500, if their account numbers are different, so are they. Their properties (in this example, their balance) do not identify them or imply equality. I bet we would argue over swapping bank accounts even if their balances were the same :-)
So, in your example, I would consider a supplier an Entity, as I would presume each supplier is primarily identified by its ID rather than its properties. My own company shares its name with two others in the world - yet we are not all interchangeable.
I think your suggestion that if you need views for CRUDing an object then it is an Entity probably holds true as a rule of thumb, but you should focus more on what makes one object different from others: properties or ID.
Now as far as Aggregate Roots go, you want to focus on the lifecycle and access control of the objects. Consider that I have a blog with many posts each with many comments - where is/are the Aggregate Root(s)? Let's start with comments. Does it make sense to have a comment without a post? Would you create a comment, then go find a post and attach it to it? If you delete a post, would you keep its comments around? I suggest a post is an Aggregate Root with one "leaf" - comments. Now consider the blog itself - its relationship with its posts is similar to that between posts and comments. It too in my opinion is an Aggregate Root with one "leaf" - posts.
So in your example, is there a strong relationship between company and supplier whereby if you delete a company (I know... you probably only have one instance of company) you would also delete its suppliers? If you delete "Starbucks" (a coffee company in the US) do all its coffee bean suppliers cease to exist? This all depends on your domain and application, but I suggest more than likely neither of your Entities are Aggregate Roots, or perhaps a better way to think about them is that they are Aggregate Roots each with no "leaves" (nothing to aggregate). In other words, company does not control access to or control the lifecycle of suppliers. It simply has a one-to-many relationship with suppliers (or perhaps many-to-many).
This brings us to Repositories. A Repository is for storing and retrieving Aggregate Roots. You have two (technically they are not aggregating anything but its easier than saying "repositories store aggregate roots or entities that are not leaves in an aggregate"), therefore you need two Repositories. One for company and one for suppliers.
I hope this helps. Perhaps Eric Evans lurks around here and will tell me where I deviated from his paradigm.
Sounds like a no-brainer to me - Supplier should have its own repository. If there is any logical possibility that an entity could exist independently in the model then it should be a root entity, otherwise you'll just end up refactoring later on anyway, which is redundant work.
Root entities are always more flexible than value objects, despite the extra implementation work up front. I find that value objects in a model become rarer over time as the model evolves, and entities that remain value objects were usually the ones that you could logically constrain that way from day one.
If companies share suppliers then having supplier as a root entity removes data redundancy as well, as you do not duplicate the supplier definition per company but share the reference instead, and the association between Company and Supplier can be bi-directional as well, which may yield more benefits.