I have a table say Table1 which has following columns
1. Id
2. Name
3. TransportModeId
4. ParkingId
5. ActivityId
Column 3,4,5 are the foreign keys and all three are simple list tables which has following columns
1. Id
2. Item
For simplicity I have shown 3 tables otherwise my actual schema contains almost 25 List table.
What should be the best Practice
Option 1.
Keep all list table separate which will create 25 tables but on the other hand i will have a clean modular schema
Option 2.
Make a table with self join and add all the items in that table in which ParentId null will represent the name of the table and it can have more than one references in other tables as described above and it has to be kept in some kind of common module
thanks
Option 1 is the way how it is normally done when designing a system that is not supposed to be very configurable by end user/implementator. It has several important advantages, two of them:
when you need to add an extra attribute to any of the enumerations (e.g. parking location to the Parking enumeration), it is quite simple and does not produce extra problems.
It is optimized for speed using relation database engine's native algorithms for linking records.
As for Option 2:
It is something called Generalization. You take more types with similar attributes (methods) and create a class/table with a structure that fits different purposes.
The self reference, as you speak about it, is not a good idea for Option 2, rather make a reference to another EnumerationType table containing type names like Parking, Activity etc. with id.
Using this approach could make sense in case you need to enable end user to configure the attributes himself within your app. But otherwise it could cause you problems when you find out, that different enumeration tables need to have different structures.
I have been asked to add a new address book table to our database (SQL Server 2012).
To simplify the related part of the database, there are three tables each linked to each other in a one to many fashion: Company (has many) Products (has many) Projects and the idea is that one or many addresses will be able to exist at any one of these levels. The thinking is that in the front-end system, a user will be able to view and select specific addresses for the project they specify and more generic addresses relating to its parent product and company.
The issue now if how best to model this in the database.
I have thought of two possible ideas so far so wonder if anyone has had a similar type of relationship to model themselves and how they implemented it?
Idea one:
The new address table will additionally contain three fields: companyID, productID and projectID. These fields will be related to the relevant tables and be nullable to represent company and product level addresses. e.g. companyID 2, productID 1, projectID NULL is a product level address.
My issue with this is that I am storing the relationship information in the table so if a project is ever changed to be related to a different product, the data in this table will be incorrect. I could potentially NULL all but the level I am interested in but this will make getting parent addresses a little harder to get
Idea two:
On the address table have a typeID and a genericID. genericID could contain the IDs from the Company, Product and Project tables with the typeID determining which table it came from. I am a little stuck how to set up the necessary constraints to do this though and wonder if this is going to get tricky to deal with in the future
Many thanks,
I will suggest using Idea one and preventing Idea two.
Second Idea is called Polymorphic Association anti pattern
Objective: Reference Multiple Parents
Resulting side effect: Using dual-purpose foreign key will violating first normal form (atomic issue), loosing referential integrity
Solution: Simplify the Relationship
The simplification of the relationship could be obtained in two ways:
Having multiple null-able forging keys (idea number 1): That will be
simple and applicable if the tables(product, project,...) that using
the relation are limited. (think about when they grow up to more)
Another more generic solution will be using inheritance. Defining a
new entity as the base table for (product, project,...) to satisfy
Addressable. May naming it organization-unit be more rational. Primary key of this organization_unit table will be the primary key of (product, project,...). Other collections like Address, Image, Contract ... tables will have a relation to this base table.
It sounds like you could use Junction tables http://en.wikipedia.org/wiki/Junction_table.
They will give you the flexibility you need to maintain your foreign key restraints, as well as share addresses between levels or entities if that is desired.
One for Company_Address, Product_Address, and Project_Address
OK, I don't know whether this question belong to this place, but you will suggest me if I'm wrong.
I have some entities which has almost same attributes, differences is in maybe 2-3 columns.
Because of those different columns, I can't create one table with columns that are union of attributes of every entity, because new entity type will require changing table design adding new columns specific to that entity type.
Instead, currently working design is that every specific entity has own table.
But, if new type of entity come on scene, I must create new table, which is totally bad idea.
How can I create one table which consists shared attributes for each type of entity, and some additional mechanism to evidence entity-unique attributes?
So, idea is to easy add new types of objects, without changing database design, configuring only part that deal with unique columns.
P.S. Maybe I'm not clear, but I will add more description if is it needed.
I had a design like that once. What I did was I created a table that housed all the shared properties. Then, I had separate tables for the distinct values. I used joins to match a specific entity to its shared table row. I had less than 10, so my views that used unions I just updated when I added a new entity. But, if you used a naming convention, you could write stored procs that find the table names dynamically and do the unions and joins on the fly. In my case, I used a base class and specific classes to make a custom data layer.
Another possibility is to have a generic table that's basically name/value pairs and a table the represents your shared properties. By joining the tables together, you could have any number of entity specific properties for your entities. It's not very efficient and the SQL would get weird, but I've seen it done.
One solution is to store the common parts in one table, and the specific parts in tables specific to that entity.
eg: To have a set of people, some of whom are managers...
Person Table
PersonID
PersonName
Manager Table
ManagerID
PersonID
DepartmentManaged
As soon as you go down the path of having one table with variable field meanings - effectively an Entity Attribute Value design - you find yourself in querying hell.
Perhaps not the best or most academic, but what about this kind of "open structure" ?
MainTable: all common fields
SpecialProperties: extra properties, as required
- MainRecordId (P, F->MainTable)
- PropertyName (P)
- PropertyText
- PropertyValue (for numeric values)
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
Consider we have a database that has a table, which is a record of a sale. You sell both products and services, so you also have a product and service table.
Each sale can either be a product or a service, which leaves the options for designing the database to be something like the following:
Add columns for each type, ie. add Service_id and Product_id to Invoice_Row, both columns of which are nullable. If they're both null, it's an ad-hoc charge not relating to anything, but if one of them is satisfied then it is a row relating to that type.
Add a weird string/id based system, for instance: Type_table, Type_id. This would be a string/varchar and integer respectively, the former would contain for example 'Service', and the latter the id within the Service table. This is obviously loose coupling and horrible, but is a way of solving it so long as you're only accessing the DB from code, as such.
Abstract out the concept of "something that is chargeable" for with new tables, of which Product and Service now are an abstraction of, and on the Invoice_Row table you would link to something like ChargeableEntity_id. However, the ChargeableEntity table here would essentially be redundant as it too would need some way to link to an abstract "backend" table, which brings us all the way back around to the same problem.
Which way would you choose, or what are the other alternatives to solving this problem?
What you are essentially asking is how to achieve polymorphism in a relational database. There are many approaches (as you yourself demonstrate) to this problem. One solution is to use "table per class" inheritance. In this setup, there will be a parent table (akin to your "chargeable item") that contains a unique identifier and the fields that are common to both products and services. There will be two child tables, products and goods: Each will contain the unique identifier for that entity and the fields specific to it.
One benefit to this approach over others is you don't end up with one table with many nullable columns that essentially becomes a dumping ground to describe anything ("schema-less").
One downside is as your inheritance hierarchy grows, the number of joins needed to grab all the data for an entity also grows.
I believe it depends on use case(s).
You could put the common columns in one table and put product and service specific columns in its own tables.Here the deal is that you need to join stuff.
Else if you maintain two separate tables, one for Product and another for Sale. You use application logic to determine which table to insert into. And getting all sales will essentially mean , union of getting all products and getting all sale.
I would go for approach 2 personally to avoid joins and inserting into two tables whenever a sale is made.