I'm very new to studying database systems and am a little stuck on how to properly normalize a database with several multivalued attributes. For example, given the following:
I understand that to normalize into the first form, I must change the structure so that each column only has one attribute. So, there shouldn't be multiple genre, time, or cast attributes in each row.
I noticed that given a Movie, I know the Genre and Cast... so Movie functionally determines Genre and Cast.
Movie -> Genre, Cast
I know there is a lot of redundancy here and I'm not quite sure how to change the database into 2NF or 3NF. Any guidance would be greatly appreciated!
Related
Hello guys! The picture attached is a screenshot of our current database design in MySql Workbench. We presented it into our professor and said that our schema was wrong particularly in the Product Categories (Cakes, Cupcakes, Pies), because it should've been inside the products table.
Can you help me improving this kind of schema by adding more tables and not just 5?
Since your other tables (cakes, pies, etc.) don't add any new attributes, it's hard to envision why you need them. Wouldn't a row in cakes just be an exact duplicate of the row it references in products?
If you need to distinguish between product category, just add a column to your products table for the category.
P.S. Please don't get into the habit of prefixing all your table names with "tbl." This is redundant, because it's obviously a table if you can query from it. Just skip the "tbl." Likewise don't encode the data type in your column names. What if you need to change the data type someday? It would break all your queries.
P.P.S. Don't use FLOAT for currency—use NUMERIC.
See https://twitter.com/billkarwin/status/347561901460447232
Also read What Every Computer Scientist Should Know About Floating-Point Arithmetic.
I am attempting to explain how the mock artist/soundtrack data (first image below) can be normalized from 1NF to 2NF to 3NF, step-by-step to get the result that I think is best for the database. It's almost as if normalization is getting in the way of what I want to do, but am I just not understanding something in the normalization process? I can definitely see how this mock data can be normalized to 1NF by making each row unique and removing duplicates, but at which stage, for example are we told to assign Composer ID as a foreign key for the tracks table or the movie table? Is that just something we do from experience? Is there no right or wrong?
In short, my question is, can anyone show or explain how the mock data here ...
Was turned into this using all the first 3 stages of normalization?
Well your 1NF would be to have a distinct record for each track name so essentially the mock data with the first record split into 2...
2NF is to take out the repeated keys which to my mind is what you've displayed as the 3 separate tables, and potentially that might be as far as you need to go.
You could add a further table to allow for a track to feature in more than one movie ie create a movie tracks table referencing the track id and movie id respectively (and removing movie id from the tracks table).
Similarly, you could go to the extreme of allowing for collaborative compositions by also having a track composers table but that is probably not sufficiently common to make the effort worthwhile
Normalization is something that definitely becomes easier with experience and can be taken as far as suits the purpose of the data as can be seen from the example.
So because I have 4 different product types (books, magazines, gifts, food) I can't just put all products in one "products" table without having a bunch of null values. So I decided to break each product up into their own tables but I know this is just wrong (https://c1.staticflickr.com/1/742/23126857873_438655b10f_b.jpg).
I also tried creating an EAV model for this (https://c2.staticflickr.com/6/5734/23479108770_8ae693053a_b.jpg), but I got stuck as I'm not sure how to link the publishers and authors tables.
I know this question has been asked a lot but I don't understand ANY of the answer's I've seen. I think this is because I'm a very visual learner and this makes it hard to understand what's being talked about when not a lot of information is given.
Your model is on the right track, except that the product name should be sufficient you don't need Gift name, book name etc. What you put in those tables is the information that is specific to the type of product that the other products don't need. The Product table contains all the common fields. I would use productid in the child tables rather than renaming it giftID, magazineID etc. It is easier to remember what things are celled when you are consistent in nameing them.
Now to be practical, you put as much as you can into the product table especially if you are going to do calculations. I prefer the child tables in this specific case to have what is mostly display information. So product contains the product name, the cost, the type of product, the units the product is sold in etc. The stuff that generally is needed to calculate the cost of an order or to have a report of what was ordered. There may be one or two fields that can contain nulls, but it simplifies the calculation type queries so much it might be worth it.
The meat of the descriptive details though would go in the child table for the type of product. These would usually only be referenced when displaying the product in the shopping area and only one at a time, so you can use the product type to let you only join to the one child table you need for display. So while the order cares about the product number and name and cost calculations, it probably doesn't need to go line by line describing the book ISBN number or the megapixels in a camera. But the description page of the product does need those things.
This approach is not purely relational, although it mostly is, but it does group the information by the meanings of the data and how they will be used which will make the database easier to understand and query. I am a big fan of relational tables because database just work better when they hit at least the third normal form but sometimes you can go too far for practicality, so the meaning of the data and the way you are grouping to use the data (and not just for the user interface, but for later reporting as well) is almost always one of my considerations in design.
Breaking each product type into its own table is fine - let the child tables use the same id as the parent Product table, and create views for the child tables that join with Product
Your case is a classic case of types and subtypes. This is often called class/subclass in object modeling and generalization/specialization in ER modeling. It's a well understood pattern. There are known techniques for dealing with this pattern.
Visit the following tabs, and read the description under the info tab (presented as "learn more"). Also look over the questions grouped under these tags.
single-table-inheritance class-table-inheritance shared-primary-key
If you want to rean in more depth use these buzzwords to search for articles on the web.
You've already discovered and discarded single table inheritance on your own. Other answers have pointed you at shared primary key. Class table inheritance involves a single table for generalized data as well as the four specialized tables. Shared primary key is generally used in conjunction with class table inheritance.
Full disclosure...Trying feverishly here to learn more about databases so I am putting in the time and also tried to get this answer from the source to no avail.
Barry Williams from databaseanswers has this schema posted.
Clients and Fees Schema
I am trying to understand the split of address tables in this schema. Its clear to me that the Addresses table contains the details of a given address. The Client_Addresses and Staff_Addresses tables are what gets me.
1) I understand the use of Primary Foreign Keys as shown but I was under the assumption that when these are used you don't have a resident Primary Key in that same table (date_address_from in this case). Can someone explain the reasoning for both and put it into words how this actually works out?
2) Why would you use date_address_from as the primary key instead of something like client_address_id as the PK? What if someone enters two addresses in one day would there be conflicts in his design? If so or if not, what?
3) Along the lines of normalization...Since both date_address_from and date_address_to are the same in the Client_Addresses and Staff_Addresses table should those fields just not be included in the main Address table?
Evaluation
First an Audit, then the specific answers.
This is not a Data Model. This is not a Database. It is a bucket of fish, with each fish drawn as a rectangle, and where the fins of one fish are caught in the the gills of another, there is a line. There are masses of duplication, as well as masses of missing elements. It is completely unworthy of using as an example to learn anything about database design from.
There is no Normalisation at all; the files are very incomplete (see Mike's answer, there are a hundred more problem like that). The other_details and eg.s crack me up. Each element needs to be identified and stored: StreetNo, ApartmentNo, StreetName, StreetType, etc. not line_1_number_street, which is a group.
Customer and Staff should be normalised into a Person table, with all the elements identified.
And yes, if Customer can be either a Person or an Organisation, then a supertype-subtype structure is required to support that correctly.
So what this really is, the technically accurate terms, is a bunch of flat files, with descriptions for groups of fields. Light years distant from a database or a relational one. Not ready for evaluation or inspection, let alone building something with. In a Relational Data Model, that would be approximately 35 normalised tables, with no duplicated columns.
Barry has (wait for it) over 500 "schemas" on the web. The moment you try to use a second "schema", you will find that (a) they are completely different in terms of use and purpose (b) there is no commonality between them (c) let's say there was a customer file in both; they would be different forms of customer files.
He needs to Normalise the entire single "schema" first,
then present the single normlaised data model in 500 sections or subject areas.
I have written to him about it. No response.
It is important to note also, that he has used some unrecognisable diagramming convention. The problem with these nice interesting pictures is that they convey some things but they do not convey the important things about a database or a design. It is no surprise that a learner is confused; it is not clear to experienced database professionals. There is a reason why there is a standard for modelling Relational databases, and for the notation in Data Models: they convey all the details and subtleties of the design.
There is a lot that Barry has not read about yet: naming conventions; relations; cardinality; etc, too many to list.
The web is full of rubbish, anyone can "publish". There are millions of good- and bad-looking "designs" out there, that are not worth looking at. Or worse, if you look, you will learn completely incorrect methods of "design". In terms of learning about databases and database design, you are best advised to find someone qualified, with demonstrated capability, and learn from them.
Answer
He is using composite keys without spelling it out. The PK for client_addresses is client_id, address_id, date_address_from). That is not a bad key, evidently he expects to record addresses forever.
The notion of keeping addresses in a separate file is a good one, but he has not provided any of the fields required to store normalised addresses, so the "schema" will end up with complete duplication of addresses; in which case, he could remove addresses, and put the lines back in the client and staff files, along with their other_details, and remove three files that serve absolutely no purpose other than occupying disk space.
You are thinking about Associative Tables, which resolve the many-to-many relations in Databases. Yes, there, the columns are only the PKs of the two parent tables. These are not Associative Tables or files; they contain data fields.
It is not the PK, it is the third element of the PK.
The notion of a person being registered at more than one address in a single day is not reasonable; just count the one address they slept the most at.
Others have answered that.
Do not expect to identify any evidence of databases or design or Normalisation in this diagram.
1) In each of those tables the primary key is a compound key consisting of three attributes: (staff_id, address_id, date_address_from) and (client_id, address_id, date_address_from). This presumably means that the mapping of clients/staff to addresses is expected to change over time and that the history of those changes is preserved.
2) There's no obvious reason to create a new "id" attribute in those tables. The compound key does the job adequately. Why would you want to create the same address twice for the same client on the same date? If you did then that might be a reason to modify the design but that seems like an unlikely requirement.
3) No. The apparent purpose is that they are the applicable dates for the mapping of address to client/staff - not dates applicable to the address alone.
3) Along the lines of
normalization...Since both
date_address_from and date_address_to
are the same in the Client_Addresses
and Staff_Addresses table should those
fields just not be included in the
main Address table?
No. But you did find a problem.
The designer has decided that clients and staff are two utterly different things. By "utterly different", I mean they have no attributes in common.
That's not true, is it? Both clients and staff have addresses. I'm sure most of them have telephones, too.
Imagine that someone on staff is also a client. How many places is that person's name stored? That person's address? Can you hear Mr. Rogers in the background saying, "Can you spell 'update anomaly'? . . . I knew you could."
The problem is that the designer was thinking of clients and staff as different kinds of people. They're not. "Client" describes a business relationship between a service provider (usually, that is, not a retailer) and a customer, which might be either a person or a company. "Staff" describes a employment relationship between a company and a person. Not different kinds of people--different kinds of relationships.
Can you see how to fix that?
This 2 extra tables enables you to have address history per one person.
You can have them both in one table, but since staff and client are separated, it is better to separate them as well (b/c client id =1 and staff id =1 can't be used on the same table of address).
there is no "single" solution to a design problem, you can use 1 person table and then add a column to different between staff and client. BUT The major Idea is that the DB should be clear, readable and efficient, and not to save tables.
about 2 - the pk is combined, both clientID, AddressID and from.
so if someone lives 6 month in the states, then 6 month in Israel, and then back to the states, to the same address - you need only 2 address in address table, and 3 in the client_address.
The idea of heaving the from_Date as part of the key is right, although it doesn't guaranty data integrity - as you also need manually to check that there isn't overlapping dates between records of the same person.
about 3 - no (look at 2).
Viewing the data model, i think:
1) PF means that the field is both part of the primary key of the table and foreign key with other table.
2) In the same way, the primary key of Staff_Addresses is {staff_id,address_id,date_adderess_from} not just date_adderess_from
3) The same that 2)
In reference to Staff_Addresses table, the Primary Key on date_address_from basically prevents a record with the same staff_id/address_id entered more than once. Now, i'm no DBA, but i like my PKs to be integers or guids for performance reasons/faster indexing. If i were to do this i would make a new column, say, Staff_Address_Id and make it the PK column and put a unique constraint on staff_id/address_id/date_address_from.
As for your last concern, Addresses table is really a generic address storage structure. It shouldn't care about date ranges during which someone resided there. It's better to be left to specific implementations of an address such as Client/Staff addresses.
Hope this helps a little.
I am currently in the process of looking at a restructure our contact management database and I wanted to hear peoples opinions on solving the problem of a number of contact types having shared attributes.
Basically we have 6 contact types which include Person, Company and Position # Company.
In the current structure all of these have an address however in the address table you must store their type in order to join to the contact.
This consistent requirement to join on contact type gets frustrating after a while.
Today I stumbled across a post discussing "Table Inheritance" (http://www.sqlteam.com/article/implementing-table-inheritance-in-sql-server).
Basically you have a parent table and a number of sub tables (in this case each contact type). From there you enforce integrity so that a sub table must have a master equivalent where it's type is defined.
The way I see it, by this method I would no longer need to store the type in tables like address, as the id is unique across all types.
I just wanted to know if anybody had any feelings on this method, whether it is a good way to go, or perhaps alternatives?
I'm using SQL Server 05 & 08 should that make any difference.
Thanks
Ed
I designed a database just like the link you provided suggests. The case was to store the data for many different technical reports. The number of report types is undefined and will probably grow to about 40 different types.
I created one master report table, that has an autoincrement primary key. That table contains all common information like customer, testsite, equipmentid, date etc.
Then I have one table for each report type that contains the spesific information relating to that report type. That table have the same primary key as the master and references the master as well.
My idea for splitting this into different tables with a 1:1 relation (which normally would be a no-no) was to avoid getting one single table with a huge number of columns, that gets very difficult to maintain as your constantly adding columns.
My design with table inheritance gave me segmented data and expandability without beeing difficult to maintain. The only thing I had to do was to write special a special save method to handle writing to two tables automatically. So far I'm very happy with the design and haven't really found any drawbacks, except for a little more complicated save method.
Google on "gen-spec relational modeling". You'll find a lot of articles discussing exactly this pattern. Some of them focus on table design, while others focus on an object oriented approach.
Table inheritance pops up in a few of them.
I know this won't help much now, but initially it may have been better to have an Entity table rather than 6 different contact types. Then each Entity could have as many addresses as necessary and there would be no need for type in the join.
You'll still have the problem that if you want the sub-type fields and you have only the master contact, you'll have to know what table to go looking at - or else join to all of them. But otherwise this is a workable solution to a common problem.
Another possibility (fairly similar in structure, but different in how you think of it) is to simply put all your contacts into one table. Then for the more specific fields (birthday say for people and department for position#company) create separate tables that are associated with that contact.
Contact Table
--------------
Name
Phone Number
Address Table
-------------
Street / state, etc
ContactId
ContactBirthday Table
--------------
Birthday
ContactId
Departments Table
-----------------
Department
ContactId
It requires a different way of thinking of things though - instead of thinking of people vs. companies, you think of the various functional requirements for the task at hand - if you want to send out birthday cards, get all the contacts that have birthdays associated with them, etc..
I'm going to go out on a limb here and suggest you should rethink your normalization strategy (as you seem to be lucky enough to be able to rethink your schema quite fundamentally). If you typically store an address for each contact, then your contact table should have the address fields in it. Alternatively if the address is stored per company then the address should be stored in the company table and your contacts linked to that company.
If your contacts only have one address, or one (or even 3, just not 'many') instance of the other fields, think about rationalizing them into a single table. In my experience having a few null fields is a far better alternative than needing left joins to data you aren't sure exists.
Fortunately for anyone who vehemently disagrees with me you did ask for opinions! :) IMHO you should only normalize when you really need to. Where you are rethinking schemas, denormalization should be considered at every opportunity.
When you have a 7th type, you'll have to create another table.
I'm going to try this approach. Yes, you have to create new tables when you have a new type, but since this table will probably have different columns, you'll end up doing this anyway if you don't use this scheme.
If the tables that inherit the master don't differentiate much from one another, I'd recommend you try another approach.
May I suggest that we just add a Type table. Ie a person has an address, name etc then the student, teacher as each use case presents its self we have a PersonType table that has an entry from the person table to n types and the subsequent new tables teacher, alien, singer as the system eveolves...