I hear a lot about subtyping tables when designing a database, and I'm fully aware of the theory behind them. However, I have never actually seen table subtyping in action. How can you create subtypes of tables? I am using MS Access, and I'm looking for a way of doing it in SQL as well as through the GUI (Access 2003).
Cheers!
An easy example would be to have a Person table with a primary key and some columns in that table. Now you can create another table called Student that has a foreign key to the person table (its supertype). Now the student table has some columns which the supertype doesn't have like GPA, Major, etc. But the name, last name and such would be in the parent table. You can always access the student name back in the Person table through the foreign key in the Student table.
Anyways, just remember the following:
The hierarchy depicts relationship between supertypes and subtypes
Supertypes has common attributes
Subtypes have uniques attributes
Subtypes of tables is a conceptual thing in EER diagrams. I haven't seen an RDBMS (excluding object-relational DBMSs) that supports it directly. They are usually implemented in either
A set of nullable columns for each property of the subtype in a single table
With a table for base type properties and some other tables with at most one row per base table that will contain subtype properties
The notion of table sub-types is useful when using an ORM mapper to produce class sub-type heirarchy that exactly models the domain.
A sub-type table will have both a Foreign Key back to its parent which is also the sub-types table's primary key.
Keep in mind that in designing a bound application, as with an Access application, subtypes impose a heavy cost in terms of joins.
For instance, if you have a supertype table with three subtype tables and you need to display all three in a single form at once (and you need to show not just the supertype date), you end up with a choice of using three outer joins and Nz(), or you need a UNION ALL of three mutually exclusive SELECT statements (one for each subtype). Neither of these will be editable.
I was going to paste some SQL from the first major app where I worked with super/subtype tables, but looking at it, the SQL is so complicated it would just confuse people. That's not so much because my app was complicated, but it's because the nature of the problem is complex -- presenting the full set of data to the user, both super- and subtypes, is by its very nature complex. My conclusion from working with it was that I'd have been better off with only one subtype table.
That's not to say it's not useful in some circumstances, just that Access's bound forms don't necessarily make it easy to present this data to the user.
I have a similar problem I've been working on.
While looking for a repeatable pattern, I wanted to make sure I didn't abandon referential integrity, which meant that I wouldn't use a (TABLE_NAME, PK_ID) solution.
I finally settled on:
Base Type Table: CUSTOMER
Sub Type Tables: PERSON, BUSINESS, GOVT_ENTITY
I put nullable PRERSON_ID, BUSINESS_ID and GOVT_ENTITY_ID fields in CUSTOMER, with foreign keys on each, and a check constraint that only one is not null. It's easy to add new sub types, just need to add the nullable foreign key and modify the check constraint.
Related
Consider the following model where a Customer should have one and only one Address and an Address should belong to one and only one Customer:
To implement it, as almost everybody in DB field says, Shared PK is the solution:
But I think it is a fake one-to-one relationship. Because nothing in terms of database relationship actually prevents deleting any row in table Address. So truely, it is 1..[0..1] not 1..1
Am I right? Is there any other way to implement a true 1..1 relation?
Update:
Why cascade delete is not a solution:
If we consider cascade delete as a solution we should put this on either of the tables. Let's say if a row is deleted from table Address, it causes corresponding row in table Customer to be deleted. it's okay but half of the solution. If a row in Customer is deleted, the corresponding row in Address should be deleted as well. This is the second half of the solution, and it obviously makes a cycle.
Beside my comment
You could implement DELETE CASCADE See HOW
I realize there is also the problem of insert.
You have to insert Customer first and then Address
So I think the best way if you really want a 1:1 is create a single table instead.
Customer
CustomerID
Name
Address
City
Sorry, is this meant to be a real-world database relationship? In all of the many databases I have ever built with customer data, there has always been real cases of either customers with multiple addresses, or more than one organisation at the same address.
I wouldn't want to lead you into a database modelling fallacy by suggesting anything different.
Yes, the "shared PK" idiom you show is for 1-to-0-or-1.
The straightforward way to have a true 1-to-1 correspondence is to have one table with Customer and Address as CKs (candidate keys). (Via UNIQUE NOT NULL and/or PRIMARY KEY.) You could offer the separate tables as views. Unfortunately typical DBMSs have restrictions on what you can do via the views, in particular re updating.
The relational way to have separate CUSTOMER and ADDRESS tables and a third table/association/relationship with Customer and Address columns as CKs plus FKs on Customer to and from CUSTOMER and on Address to and from ADDRESS (or equivalent constraint(s)). Unfortunately most DBMSs needlessly won't let you declare cycles in FKs and you cannot impose the constraints without triggers/complexity. (Ultimately, if you want to have proper integrity in a typical SQL database you need to use triggers and complex idioms.)
Entity-oriented design methods unfortunately artificially distinguish between entities, associations and properties. Here is an example where if you consider the simplest design to simply be the one table with PKs then you don't want to always have to have distinct tables for each entity. Or if you consider the simplest design to be the three tables (or even two) with the PKs and FKs (or some other constraint(s) for 1-to-1) then unfortunately typical DBMSs just don't declaratively/ergonomically support that particular design situation.
(Straightforward relational design is to have values (that are sometimes used as ids) 1-to-1 with application things but then just have whatever relevant application relationships/associations/relations and corresponding/representing tables/relations as needed to describe your application situations.)
It's possible in principle to implement a true 1-1 data structure in some DBMSs. It's very difficult to add data or modify data in such a structure using standard SQL however. Standard SQL only permits one table to be updated at a time and therefore as soon as you insert a row into one or other table the intended constraint is broken.
Here are two examples. First using Tutorial D. Note that the comma between the two INSERT statements ensures that the 1-1 constraint is never broken:
VAR CUSTOMER REAL RELATION {
id INTEGER} KEY{id};
VAR ADDRESS REAL RELATION {
id INTEGER} KEY{id};
CONSTRAINT one_to_one (CUSTOMER{id} = ADDRESS{id});
INSERT CUSTOMER RELATION {
TUPLE {id 1234}
},
INSERT ADDRESS RELATION {
TUPLE {id 1234}
};
Now the same thing in SQL.
CREATE TABLE CUSTOMER (
id INTEGER NOT NULL PRIMARY KEY);
CREATE TABLE ADDRESS (
id INTEGER NOT NULL PRIMARY KEY);
INSERT INTO CUSTOMER (id)
VALUES (1234);
INSERT INTO ADDRESS (id)
VALUES (1234);
ALTER TABLE CUSTOMER ADD CONSTRAINT one_to_one_1
FOREIGN KEY (id) REFERENCES ADDRESS (id);
ALTER TABLE ADDRESS ADD CONSTRAINT one_to_one_2
FOREIGN KEY (id) REFERENCES CUSTOMER (id);
The SQL version uses two foreign key constraints, which is the only kind of multi-table constraint supported by most SQL DBMSs. It requires two INSERT statements which means I could only insert a row before adding the constraints, not after.
A strict one-to-one constraint probably isn't very useful in practice but it's actually just a special case of something more important and interesting: join dependency. A join dependency is effectively an "at least one" constraint between tables rather than "exactly one". In the world outside databases it is common to encounter examples of business rules that ought to be implemented as join dependencies ("each customer must have AT LEAST ONE addresss", "each order must have AT LEAST ONE item in it"). In SQL DBMSs it's hard or impossible to implement join dependencies. The usual solution is simply to ignore such business rules thus weakening the data integrity value of the database.
Yes, what you say is true, the dependent side of a 1:1 relationship may not exist -- if only for the time it takes to create the dependent entity after creating the independent entity. In fact, all relationships may have a zero on one side or the other. You can even turn the relationship into a 1:m by placing the FK of the address in the Customer row and making the field not null. You can still have addresses that aren't referenced by any customer.
At first glance, a m:n may look like an exception. The intersection entry is generally defined so that neither FK can be null. But there can be customers and addresses both that have no entry referring to them. So this is really a 0..m:0..n relationship.
What of it? Everyone I've ever worked with has understood that "one" (as in 1:1) or "many" (as in 1:m or m:n) means "no more than this." There is no "exactly this, no more or less." For example, we can design a 1:3 relationship on paper. We cannot strictly enforce it in any database. We have to use triggers, stored procedures and/or scheduled tasks to seek out and call our attention to deviations. Execute a stored procedure weekly, for instance, that will seek and and flag or delete any such orphaned addresses.
Think of it like a "frictionless surface." It exists only on paper.
I see this question as a conceptual misunderstanding. Relations are between different things. Things with a "true 1-to-1 relation" are by definition aspects or attributes of the same thing, and belong in the same table. No, of course a person and and address are not the same, but if they are inseparable, and must always be inserted, deleted, or otherwise acted upon as a unit, then as data they are "the same thing". This is exactly what is described here.
Yes, and it's actually quite easy: just put both entities in the same table!
OTOH, if you need to keep them in separate tables for some reason, then you need a key in one table referencing1 a key in another, and vice-versa. This, of course, represents a "chicken and egg" problem2 which can be resolved by deferring the enforcement of FKs to the end of the transaction3. This works only on DBMSes that support deferred constraints (such as Oracle and PostgreSQL).
1 Via a foreign key.
2 Inserting a row in the first table is impossible because that would violate the referential integrity towards the second table, but inserting a row in the second table is impossible because that would violate the referential integrity towards the first table, etc... Ditto for deletion.
3 So you simply insert both rows, and then check both FKs.
I'm trying to build a table for an inbox app that stores its messages within inbox table.
The structure of the table is as follows:
inbox_id|sender_id|receiver_id|subject|message
The columns sender_id and receiver_id are FOREIGN KEYS and can reference multiple tables.
There are currently 3 types of users within the database and they all can send messages to each other. A user of type UserType1 can send a message to UserType2 and vice versa, or UserType1 can send messages to UserType1. So receiver and sender can reference one of these 3 tables.
My solution to this problem is to build a inbox_user table containing columns for each user type and to have sender_id and inbox_user reference it.
My main concern is limited flexibility of the solution and wasteful usage of resources. I would, at all times, always have 2 empty columns per row. And that would become even worse if I introduced more user types.
Would this be considered a bad practice? What are some more flexible and intelligent designs?
From your description it sounds like the best practice should be applied to your user table and not this inbox table. Of course, I don't know your constraints, but if you have 2 or 3 types of users with each type of user in its own table, that is a poor design (again, not knowing your constraints). The preference is to store all users in one table with a column to indicate their type. Then the reference to your inbox table becomes straightforward with both sender and receiver FKs pointing back to the same user table.
Otherwise, you're going to end up using multiple columns to reference each table like you said (UserTypeASenderID, UserTypeBSenderID, UserTypeCSenderID, etc). My preference is to have null FK columns and gain the referential integrity than to implement some other solution and lose the constraints.
3 different types of users is a classic type/subtype situation. (or, if you prefer, class/subclass). There are several ways to design for a class/subclass situation. Two that look good to me are "Class Table Inheritance" and "Single Table Inheritance" as explained by Martin fowler. You can find a synopsis online. You can also visit tags by these names in here, read up on the info presented, and look at the tagged questions.
Single table inheritance suffers from a lot of NULLs for fields that are not applicable some of the time, as you pointed out in the Q. This may or may not be a problem for you, depending on your case.
Class table inheritance involves a little programming when a new entry is made in a subclass (subtype). It also involves more joining, but it isn't very expensive joining. Class table inheritance is frequently combined with a technique called shared primary key. In this technique, the subclass tables end up with a primary key that is a duplicate of the primary key in the superclass table. It's also a foreign key to the superclass table. This makes joining subclass data and superclass data simple, easy, and fast.
Shared primary key resolves the quandary you stated in your Q, namely how to reference more than one table with one foreign key. A foreign key reference in some other table to the superclass table will also be a reference to at least one of the subclass tables. This seems like magic. Try it, see if you like it.
In my example, I have a watch, which is an indication a user wants notifications about events on a different item, say a group and an organization.
I see two ways to do this:
Have a groupwatch resource, with a groupwatch table, with id,user,group (group FK to group resource and table); and a orgwatch resource, with a orgwatch table, with id,user,organization (org FK to organization resource and table)
Have a generic watch resource, with a watch table, with id,user,type,typeid. type is one of group or organization, and typeid is the ID of the group or organization being watched.
Since both of them are watches, it seems a waste to have two different tables and resources to watch 2 different objects. It gets worse if I start watching 4, 5, 6, 20, 50 different types of resources.
On the other hand, a foreign key relationship appears impossible if I just have a generic typeid, which means that my database (if relational) and my framework (activerecord or anything else) cannot enforce it correctly.
How do I best implement this type of "association to different types of record/table for each record in my table"?
UPDATE:
Are my only choices for doing this:
separate tables/resources for each watch type, which enables the database to enforce relational integrity and do joins
single table for all watches, but I will have to enforce relational integrity and do joins at the app level?
If you add a new type of resource once every six months, you may want to define your tables in such a way that adding new resources involves changing data definitions. If you add a new resource type every week, you may want to make your data definitions stay the same when you add new types. There's a downside to either choice.
If you do choose to define table in such a way that the types are visible in the table structure, there are two patterns often used with type/subtype (aka class/subclass) situations.
One pattern has been called "single table inheritance". Put data about all the types in a single table, and leave some columns NULL wherever they do not apply.
Another pattern has been called "class table inheritance". Define one table for the superclass, with all the data that is common to all the types. Then define tables for each subtype (subclass) to contain class specific data. Make the primary key of the subtype tables a duplicate of the primary key in the supertype table, and also declare it as a foreign key that references the primary key of the supertype table. It's going to be up to the app, at insert time, to replicate the value of the primary key in the supertype table over in the subtype table.
I like Fowlers' treatment of these two patterns.
http://martinfowler.com/eaaCatalog/classTableInheritance.html
http://www.martinfowler.com/eaaCatalog/singleTableInheritance.html
This matter of sharing primary keys has a few beneficial effects.
First, it enforces the one-to-one nature of the ISa relationships.
Second, it makes it easy to find out whether a given entry belongs to a desired subtype, by just joining with the subtype table. You don't really need an extra type field.
Third, it speeds up the joins, because of the index that gets built when you declare a primary key.
If you want a structure that can adapt to new attributes without changing data definitions, you can look into E-A-V design. Be careful, though. Sometimes this results in data that is nearly impossible to use, because the logical structure is so obscure. I usually think of E-A-V as an anti-pattern for this reason, although there are some who really like the results they get from it.
I have a table that will contain information for 3 other tables. The design I have is that this table will have a column that will tell the objects's ID and another column will tell the objects's type (and thus the table that that row refers to).
Two questions:
a) Is that the best design or is there something else more widely accepted?
b) What is the recommend procedure to assure that IDs are valid for the given objects's type?
If I understood your question correctly, each row in your table links to exactly one of the three other tables.
Your approach (type field + one foreign key field) is a valid design, and it's useful if you want to create a general-purpose table that contains meta-information about your data (e.g. a list of records that should be retransmitted for replication).
Another approach, which might be more suitable for real application-level data, would be to have three columns, each being a foreign key to one of the three tables, and to add a constraint that requires exactly two of those fields to be null. The has the following advantages:
The three FKs do not need to have the same data type.
The JOIN syntax becomes more natural (not involving the type field).
You can add referential integrity constraints on those FK columns.
You don't need to ensure correctness of the type field -- in fact, you don't need the type field at all. The type is determined implicitly by the one FK column which is not null.
a) I'm supposing you have a relationship one to many between objects and object types. In a normal design you'd have a reference from the objecttype column in the objects table to the primary key of the object types table
b) I would enforce referential integrity in the relationship properties (this depends on the dbms you are using). It's also up to you to use cascading on updates and deletes. This way, an update or a delete of the primary key on object types table would be reflected on the objects one, updating its foreign key column (object type column) or deleting the registers that have that object type.
The basics of DB schema design are easy, but more complicated situations can be really complicated to figure out what's best. There is a lot of personal subjectivity that can come into play here, and even performance can be a factor in denormalizing a design.
Disclaimer aside, my personal recommendation is to never use a column to store more than one kind of FK, i.e. a column for FKs should store FKs that point only to a single table. If you don't do this, you have to map the cascade of that column's data into multiple sub-select queries inside your code, and it can begin to get more messy than you expected. Your given "Problem No. 2, ensuring validity between type and FK" is just the beginning of a whole world of pain that will cascade throughout your source code.
Assuming you change the design to use one field per FK reference, I would also check whether each FK field in your main "information-holding table" will be fully valid for each record. If not, I would move out the FK columns that will only be applicable some of the time to a separate table.
I have to add functionality to an existing application and I've run into a data situation that I'm not sure how to model. I am being restricted to the creation of new tables and code. If I need to alter the existing structure I think my client may reject the proposal.. although if its the only way to get it right this is what I will have to do.
I have an Item table that can me link to any number of tables, and these tables may increase over time. The Item can only me linked to one other table, but the record in the other table may have many items linked to it.
Examples of the tables/entities being linked to are Person, Vehicle, Building, Office. These are all separate tables.
Example of Items are Pen, Stapler, Cushion, Tyre, A4 Paper, Plastic Bag, Poster, Decoration"
For instance a Poster may be allocated to a Person or Office or Building. In the future if they add a Conference Room table it may also be added to that.
My intital thoughts are:
Item
{
ID,
Name
}
LinkedItem
{
ItemID,
LinkedToTableName,
LinkedToID
}
The LinkedToTableName field will then allow me to identify the correct table to link to in my code.
I'm not overly happy with this solution, but I can't quite think of anything else. Please help! :)
Thanks!
It is not a good practice to store table names as column values. This is a bad hack.
There are two standard ways of doing what you are trying to do. The first is called single-table inheritance. This is easily understood by ORM tools but trades off some normalization. The idea is, that all of these entities - Person, Vehicle, whatever - are stored in the same table, often with several unused columns per entry, along with a discriminator field that identifies what type the entity is.
The discriminator field is usually an integer type, that is mapped to some enumeration in your code. It may also be a foreign key to some lookup table in your database, identifying which numbers correspond to which types (not table names, just descriptions).
The other way to do this is multiple-table inheritance, which is better for your database but not as easy to map in code. You do this by having a base table which defines some common properties of all the objects - perhaps just an ID and a name - and all of your "specific" tables (Person etc.) use the base ID as a unique foreign key (usually also the primary key).
In the first case, the exclusivity is implicit, since all entities are in one table. In the second case, the relationship is between the Item and the base entity ID, which also guarantees uniqueness.
Note that with multiple-table inheritance, you have a different problem - you can't guarantee that a base ID is used by exactly one inheritance table. It could be used by several, or not used at all. That is why multiple-table inheritance schemes usually also have a discriminator column, to identify which table is "expected." Again, this discriminator doesn't hold a table name, it holds a lookup value which the consumer may (or may not) use to determine which other table to join to.
Multiple-table inheritance is a closer match to your current schema, so I would recommend going with that unless you need to use this with Linq to SQL or a similar ORM.
See here for a good detailed tutorial: Implementing Table Inheritance in SQL Server.
Find something common to Person, Vehicle, Building, Office. For the lack of a better term I have used Entity. Then implement super-type/sub-type relationship between the Entity and its sub-types. Note that the EntityID is a PK and a FK in all sub-type tables. Now, you can link the Item table to the Entity (owner).
In this model, one item can belong to only one Entity; one Entity can have (own) many items.
your link table is ok.
the trouble you will have is that you will need to generate dynamic sql at runtime. parameterized sql does not typically allow the objects inthe FROM list to be parameters.
i fyou want to avoid this, you may be able to denormalize a little - say by creating a table to hold the id (assuming the ids are unique across the other tables) and the type_id representing which table is the source, and a generated description - e.g. the name value from the inital record.
you would trigger the creation of this denormalized list when the base info is modified, and you could use that for generalized queries - and then resort to your dynamic queries when needed at runtime.