Problem description
I am currently working on a project which requires a relational database for storage.
After thinking about the data and its relations for a while I ran into a quite repetitive problem:
I encountered a common data schema for entity A which contains some fields e.g. name, description, value. This entity is connected with entity B in multiple n-1 relations. So entity B has n entities A in relation rel1 and n entities A in relation rel2.
Now I am trying to break down this datamodel into a schema for a relational database (e.g. Postgres, MySQL).
After some research, I have not really found "the best" solution for this particular problem.
Some similar questions I have found so far:
Stackoverflow
DBA Stackexchange
My ideas
So I have thought about possible solutions which I am going to present here:
1. Duplicate table
The relationship from entity B to entity A has a certain meaning to it. So it is possible to create multiple tables (1 per relationship). This would solve all immediate problems but essentially duplicate the tables which means that changes now have to be reflected to multiple tables (e.g. a new column).
2. Introduce a type column
Instead of multiple relationships, I could just say "Entity B is connected with n entity A". Additionally, I would add a type column that then tells me to which relation entity A belongs. I am not exactly sure how this is represented with common ORMs like Spring-Hibernate and if this introduces additional problems that I am currently unaware of.
3. Abstract the common attributes of entity A
Another option is to create a ADetails entity, which bundles all attributes of entity A.
Then I would create two entities that represent each relationship and which are connected to the ADetails entity in a 1-to-1 relationship. This would solve the interpretation problem of the foreign key but might be too much overhead.
My Question
In the context of a medium-large-sized project, are any of these solutions viable?
Are there certain Cons that rule out one particular approach?
Are there other (better) options I haven't thought about?
I appreciate any help on this matter.
Edit 1 - PPR (Person-Party-Role)
Thanks for the suggestion from AntC. PPR Description
I think the described situation matches my problem.
Let's break it down:
Entity B is an event. There exists only one event for the given participants to make this easier. So the relationship from event to participant is 1-n.
Entity A can be described as Groups, People, Organization but given my situation they all have the same attributes. Hence, splitting them up into separate tables felt like the wrong idea.
To explain the situation with the class diagram:
An Event (Entity B) has a collection of n Groups (Entity A), n People (Entity A) and n Organizations (Entity A).
If I understand correctly the suggestion is the following:
In my case the relationship between Event and Participant is 1-n
The RefRoles table represents the ParticipantType column that descibes to which relationship the Participant belongs (is it a customer or part of the service for the event for example)
Because all my Groups, People and Organizations have the same attributes the only table required at this point is the Participant table
If there are individual attributes in the future I would introduce a new table (e.g. People) that references the Participant in a 1-1 relationship.
If there are multiple tables going to be added, the foreign key of the multiple 1-1 relationship is mutually exclusive (so there can only be one Group/Person/Organization for a participant)
Solution suggested by AntC and Christian Beikov
Splitting up the tables does make sense while keeping the common attributes in one table.
At the moment there are no individual attributes but the type column is not required anymore because the foreign keys can be used to see which relationship the entity belongs to.
I have created a small example for this:
There exist 3 types (previously type column) of people for an event: Staff, VIP, Visitor
The common attributes are mapped in a 1-1-relationship to the person table.
To make it simple: Each Person (Staff, VIP, Visitor) can only participate in one event. (Would be n-m-relationship in a more advanced example)
The database schema would be the following:
This approach is better than the type column in my opinion.
It also solves having to interprete the entity based on its type in the application later on. It is also possible to resolve a type column in an ORM (see this question) but this approach avoids the struggle if the ORM you are using does not support resolving it.
IMO since you already use dedicated terms for these objects, they probably will diverge and splitting up a table afterwards is quite some work, also on the code side, so I would suggest you map dedicated entities/tables from the beginning.
I have the following ERD:
ER Diagram
I need to convert this into relational schema but I have some doubts on where the attribute "since" would belong. I know how 1-M relationships work but I am confused by the attribute since. Does a new table Company-Employee need to be created where it would hold the Company id, emp id and since?
Please let me know thank you.
As you have diagrammed it, the Since attribute describes the relationship, not the employee or the company. There's nothing wrong with that, although some experts maintain that attributes must describe entities and not relationships.
When you go to design a relational schema, both entities and relationships become relations (or, as I prefer, "tables"). Your only question seems to be whether there has to be a junction table between the Employee table and the Company table.
You can get away with just two tables. You can stuff both the CompanyId and the Since columns into the Employee table, because they will be single valued. There may be other considerations that lead you to decompose the two tables, but you don't have to do it just to represent the data.
Sorry for that noob question but is there any real needs to use one-to-one relationship with tables in your database? You can implement all necessary fields inside one table. Even if data becomes very large you can enumerate column names that you need in SELECT statement instead of using SELECT *. When do you really need this separation?
1 to 0..1
The "1 to 0..1" between super and sub-classes is used as a part of "all classes in separate tables" strategy for implementing inheritance.
A "1 to 0..1" can be represented in a single table with "0..1" portion covered by NULL-able fields. However, if the relationship is mostly "1 to 0" with only a few "1 to 1" rows, splitting-off the "0..1" portion into a separate table might save some storage (and cache performance) benefits. Some databases are thriftier at storing NULLs than others, so a "cut-off point" where this strategy becomes viable can vary considerably.
1 to 1
The real "1 to 1" vertically partitions the data, which may have implications for caching. Databases typically implement caches at the page level, not at the level of individual fields, so even if you select only a few fields from a row, typically the whole page that row belongs to will be cached. If a row is very wide and the selected fields relatively narrow, you'll end-up caching a lot of information you don't actually need. In a situation like that, it may be useful to vertically partition the data, so only the narrower, more frequently used portion or rows gets cached, so more of them can fit into the cache, making the cache effectively "larger".
Another use of vertical partitioning is to change the locking behavior: databases typically cannot lock at the level of individual fields, only the whole rows. By splitting the row, you are allowing a lock to take place on only one of its halfs.
Triggers are also typically table-specific. While you can theoretically have just one table and have the trigger ignore the "wrong half" of the row, some databases may impose additional limits on what a trigger can and cannot do that could make this impractical. For example, Oracle doesn't let you modify the mutating table - by having separate tables, only one of them may be mutating so you can still modify the other one from your trigger.
Separate tables may allow more granular security.
These considerations are irrelevant in most cases, so in most cases you should consider merging the "1 to 1" tables into a single table.
See also: Why use a 1-to-1 relationship in database design?
My 2 cents.
I work in a place where we all develop in a large application, and everything is a module. For example, we have a users table, and we have a module that adds facebook details for a user, another module that adds twitter details to a user. We could decide to unplug one of those modules and remove all its functionality from our application. In this case, every module adds their own table with 1:1 relationships to the global users table, like this:
create table users ( id int primary key, ...);
create table users_fbdata ( id int primary key, ..., constraint users foreign key ...)
create table users_twdata ( id int primary key, ..., constraint users foreign key ...)
If you place two one-to-one tables in one, its likely you'll have semantics issue. For example, if every device has one remote controller, it doesn't sound quite good to place the device and the remote controller with their bunch of characteristics in one table. You might even have to spend time figuring out if a certain attribute belongs to the device or the remote controller.
There might be cases, when half of your columns will stay empty for a long while, or will not ever be filled in. For example, a car could have one trailer with a bunch of characteristics, or might have none. So you'll have lots of unused attributes.
If your table has 20 attributes, and only 4 of them are used occasionally, it makes sense to break the table into 2 tables for performance issues.
In such cases it isn't good to have everything in one table. Besides, it isn't easy to deal with a table that has 45 columns!
If data in one table is related to, but does not 'belong' to the entity described by the other, then that's a candidate to keep it separate.
This could provide advantages in future, if the separate data needs to be related to some other entity, also.
The most sensible time to use this would be if there were two separate concepts that would only ever relate in this way. For example, a Car can only have one current Driver, and the Driver can only drive one car at a time - so the relationship between the concepts of Car and Driver would be 1 to 1. I accept that this is contrived example to demonstrate the point.
Another reason is that you want to specialize a concept in different ways. If you have a Person table and want to add the concept of different types of Person, such as Employee, Customer, Shareholder - each one of these would need different sets of data. The data that is similar between them would be on the Person table, the specialist information would be on the specific tables for Customer, Shareholder, Employee.
Some database engines struggle to efficiently add a new column to a very large table (many rows) and I have seen extension-tables used to contain the new column, rather than the new column being added to the original table. This is one of the more suspect uses of additional tables.
You may also decide to divide the data for a single concept between two different tables for performance or readability issues, but this is a reasonably special case if you are starting from scratch - these issues will show themselves later.
First, I think it is a question of modelling and defining what consist a separate entity. Suppose you have customers with one and only one single address. Of course you could implement everything in a single table customer, but if, in the future you allow him to have 2 or more addresses, then you will need to refactor that (not a problem, but take a conscious decision).
I can also think of an interesting case not mentioned in other answers where splitting the table could be useful:
Imagine, again, you have customers with a single address each, but this time it is optional to have an address. Of course you could implement that as a bunch of NULL-able columns such as ZIP,state,street. But suppose that given that you do have an address the state is not optional, but the ZIP is. How to model that in a single table? You could use a constraint on the customer table, but it is much easier to divide in another table and make the foreign_key NULLable. That way your model is much more explicit in saying that the entity address is optional, and that ZIP is an optional attribute of that entity.
not very often.
you may find some benefit if you need to implement some security - so some users can see some of the columns (table1) but not others (table2)..
of course some databases (Oracle) allow you to do this kind of security in the same table, but some others may not.
You are referring to database normalization. One example that I can think of in an application that I maintain is Items. The application allows the user to sell many different types of items (i.e. InventoryItems, NonInventoryItems, ServiceItems, etc...). While I could store all of the fields required by every item in one Items table, it is much easier to maintain to have a base Item table that contains fields common to all items and then separate tables for each item type (i.e. Inventory, NonInventory, etc..) which contain fields specific to only that item type. Then, the item table would have a foreign key to the specific item type that it represents. The relationship between the specific item tables and the base item table would be one-to-one.
Below, is an article on normalization.
http://support.microsoft.com/kb/283878
As with all design questions the answer is "it depends."
There are few considerations:
how large will the table get (both in terms of fields and rows)? It can be inconvenient to house your users' name, password with other less commonly used data both from a maintenance and programming perspective
fields in the combined table which have constraints could become cumbersome to manage over time. for example, if a trigger needs to fire for a specific field, that's going to happen for every update to the table regardless of whether that field was affected.
how certain are you that the relationship will be 1:1? As This question points out, things get can complicated quickly.
Another use case can be the following: you might import data from some source and update it daily, e.g. information about books. Then, you add data yourself about some books. Then it makes sense to put the imported data in another table than your own data.
I normally encounter two general kinds of 1:1 relationship in practice:
IS-A relationships, also known as supertype/subtype relationships. This is when one kind of entity is actually a type of another entity (EntityA IS A EntityB). Examples:
Person entity, with separate entities for Accountant, Engineer, Salesperson, within the same company.
Item entity, with separate entities for Widget, RawMaterial, FinishedGood, etc.
Car entity, with separate entities for Truck, Sedan, etc.
In all these situations, the supertype entity (e.g. Person, Item or Car) would have the attributes common to all subtypes, and the subtype entities would have attributes unique to each subtype. The primary key of the subtype would be the same as that of the supertype.
"Boss" relationships. This is when a person is the unique boss or manager or supervisor of an organizational unit (department, company, etc.). When there is only one boss allowed for an organizational unit, then there is a 1:1 relationship between the person entity that represents the boss and the organizational unit entity.
The main time to use a one-to-one relationship is when inheritance is involved.
Below, a person can be a staff and/or a customer. The staff and customer inherit the person attributes. The advantage being if a person is a staff AND a customer their details are stored only once, in the generic person table. The child tables have details specific to staff and customers.
In my time of programming i encountered this only in one situation. Which is when there is a 1-to-many and an 1-to-1 relationship between the same 2 entities ("Entity A" and "Entity B").
When "Entity A" has multiple "Entity B" and "Entity B" has only 1 "Entity A"
and
"Entity A" has only 1 current "Entity B" and "Entity B" has only 1 "Entity A".
For example, a Car can only have one current Driver, and the Driver can only drive one car at a time - so the relationship between the concepts of Car and Driver would be 1 to 1. - I borrowed this example from #Steve Fenton's answer
Where a Driver can drive multiple Cars, just not at the same time. So the Car and Driver entities are 1-to-many or many-to-many. But if we need to know who the current driver is, then we also need the 1-to-1 relation.
Another use case might be if the maximum number of columns in the database table is exceeded. Then you could join another table using OneToOne
I am designing a database and as i do not have much experience in this subject, i am faced with a problem which i do not know how to go about solving.
In my conceptual model i have an object known as "Vehicle" which the customer orders and the stock system monitors. This supertype has two subtypes "Motorcar" and "Motorcycle". The user can order one or the other or even both.
Now that i am at the logical design stage, i need to know how i can have the system allow for two different types of products. The problem i have is that if i put each of the objects separate attributes into the same relation, then i will have columns that are of no use to some objects.
For example, if i just have a generic table holding both "Motorcars" and "Motorcycles" which i call "Vehicles" and all of their attributes, the cars will not need some of the motorcycle attributes and the motorcycle will not need all of the car attributes.
Is there a way to solve this issue?
The decision will need to be guided by the amount of shared information. I would start by identifying all the attributes and the rules about them.
If the majority of information is shared, you might not split into multiple tables. On the other hand, you can always split tables and then join into a view for ease of use.
For instance, you might have a vehicle table with only share information, and then a motorcar table with a foreign key to the vehicles table and a motorcycle table with a foreign key to the vehicles table. There is a certain difficulty ensuring that you don't have a motorocar row AND a motorcycle row referring to the same vehicle, and so there are other possibilities to mitigate that - but all that is unnecessary if the majority of information is common, you just have unused columns in a single vehicles table. You can even enforce with constraints to ensure that columns are NULL for types where they should not be filled in.
There are couples of questions around asking for difference / explanation on identifying and non-identifying relationship in relationship database.
My question is, can you think of a simpler term for these jargons? I understand that technical terms have to be specific and unambiguous though. But having an 'alternative name' might help students relate more easily to the concept behind.
We actually want to use a more layman term in our own database modeling tool, so that first-time users without much computer science background could learn faster.
cheers!
I often see child table or dependent table used as a lay term. You could use either of those terms for a table with an identifying relationship
Then say a referencing table is a table with a non-identifying relationship.
For example, PhoneNumbers is a child of Users, because a phone number has an identifying relationship with its user (i.e. the primary key of PhoneNumbers includes a foreign key to the primary key of Users).
Whereas the Users table has a state column that is a foreign key to the States table, making it a non-identifying relationship. So you could say Users references States, but is not a child of it per se.
I think belongs to would be a good name for the identifying relationship.
A "weak entity type" does not have its own key, just a "partial key", so each entity instance of this weak entity type has to belong to some other entity instance so it can be identified, and this is an "identifying relationship". For example, a landlord could have a database with apartments and rooms. A room can be called kitchen or bathroom, and while that name is unique within an apartment, there will be many rooms in the database with the name kitchen, so it is just a partial key. To uniquely identify a room in the database, you need to say that it is the kitchen in this particular apartment. In other words, the rooms belong to apartments.
I'm going to recommend the term "weak entity" from ER modeling.
Some modelers conceptualize the subject matter as being made up of entities and relationships among entities. This gives rise to Entity-Relationship Modeling (ER Modeling). An attribute can be tied to an entity or a relationship, and values stored in the database are instances of attributes.
If you do ER modeling, there is a kind of entity called a "weak entity". Part of the identity of a weak entity is the identity of a stronger entity, to which the weak one belongs.
An example might be an order in an order processing system. Orders are made up of line items, and each line item contains a product-id, a unit-price, and a quantity. But line items don't have an identifying number across all orders. Instead, a line item is identified by {item number, order number}. In other words, a line item can't exist unless it's part of exactly one order. Item number 1 is the first item in whatever order it belongs to, but you need both numbers to identify an item.
It's easy to turn an ER model into a relational model. It's also easy for people who are experts in the data but know nothing about databases to get used to an ER model of the data they understand.
There are other modelers who argue vehemently against the need for ER modeling. I'm not one of them.
Nothing, absolutely nothing in the kind of modeling where one encounters things such as "relationships" (ER, I presume) is "technical", "precise" or "unambiguous". Nor can it be.
A) ER modeling is always and by necessity informal, because it can never be sufficient to capture/express the entire definition of a database.
B) There are so many different ER dialects out there that it is just impossible for all of them to use exactly the same terms with exactly the same meaning. Recently, I even discovered that some UK university that teaches ER modeling, uses the term "entity subtype" for the very same thing that I always used to name "entity supertype", and vice-versa !
One could use connection.
You have Connection between two tables, where the IDs are the same.
That type of thing.
how about
Association
Link
Correlation