I need to have a lot of user data in the database. Now, I've been thinking about having two tables, users that would have only the id, username and password and another table userData that would have everything else like name, lastname etc.
Is this a prefered method?
The simplest design would put all the fields in one table. From that point, though, there are a bunch of reasons you might want to consider splitting that information up into multiple tables. From your description, I cant' tell whether there are any valid reasons to do so.
If you start with one table, you might find it advantageous to split the data for reasons such as:
Normalization.
Reducing contention (different parts of the app update different information)
Truly huge column lists (look into the limit for your DB)
Other?? (how you're going to maintain your app, maybe?)
In short, I'd try to start simple and have a reason to pick the more complex design if you go that route.
There is nothing wrong with that design IMHO. You can have a users table and link it to a users_custom table that has additional information. Just be consistant with your design. Just remember that in order to get any additional user information you will always have to JOIN to that data.
To me this is a matter of preference, if you feel that this table will grow over time, consider your design, if not just keep it all in one table and properly index columns that you deem necessary.
You can go further by having a UserLog table to build a historical view of values as they change.
Yes it is :) In theory there are this so called "normal forms" (3NF BCnF, etc...). Using them, means seperating table into smaller ones :)
I think it might be better for you to keep it all in one table. Assuming you will be enforcing unique usernames, all the fields (password, first_name, and last_name) have a functional dependency on username. Therefore, you can put them all in the same table and still have a normalized database.
Although you can certainly separate first_name and last_name into their own table, queries will get a lot easier (fewer JOINs) if you keep all those fields in one table.
Related
Today I was designing a database for a potential personal project of mine. Since I couldn't decide what would be a better option I asked my teacher Databases, unfortunately he couldn't tell me which of the two options is better than the other and why.
I designed the database for a dummy data generator. Since I want to generate multilangual data I thought of these tables. (But its a simplification of the tables).
(first and last)names: id, name
streets: id, name
languages: id, name
Each names.name and streets.name originates from a language, sometimes a name can have multiple origins (ex: Nick is both a Dutch as an English name).
Each language has multiple names and streets.
These two rules result in a Many-to-Many relationship. At the moment I've got only two tables, but I know I will get between 10 and 20 of these kind of tables.
The regular way one would do this is just make 10 to 20 Many-to-Many relationship tables.
Another idea I came up with was just one Many-to-Many table with a third column which specifies which table the id relates to.
At the moment I've got the design on my other PC so I will update it with my ideas visualized after dinner (2 hours or so).
Which idea is better and why?
To make the project idea a bit clearer:
It is always a hassle to create good and enough realistic looking working data for projects. This application will generate this data for you and return the needed SQL so you only have to run the queries.
The user comes to the site to get the data. He states his tablename, his columnnames and then he can link the columnnames to types of data, think of:
* Firstname
* Lastname
* Email adress (which will be randomly generated from the name of the person)
* Adress details (street, housenumber, zipcode, place, country)
* A lot more
Then, after linking columns with the types the user can set the number of rows he wants to make. The application will then choose a country at random and generate realistic looking data according to the country they live in.
That's actually an excellent question. This sort of thing leads to a genuine problem in database design and there is a real tradeoff. I don't know what rdbms you are using but....
Basically you have four choices, all of them with serious downsides:
1. One M-M table with check constraints that only one fkey can be filled in besides language and one column per potential table. Ick....
2. One M-M table per relationship. This makes things quite hard to manage over time especially if you need to change something from an int to a bigint at some point.
3. One M-M table with a polymorphic relationship. You lose a lot of referential integrity checks when you do this and to make it safe, have fun coding (and testing!) triggers.
4. Look carefully at the advanced features in your rdbms for a solution. For example in postgresql this can be solved with table inheritance. The downside is that you lose portability and end up in advanced territory.
Unfortunately there is no single definite answer. You need to consider the tradeoffs carefully and decide what makes sense for your project. If I was just working with one RDBMS, I would do the last one. But if not, I would probably do one table per relationship and focus on tooling to manage the problems that come up. But the former preference is about my level of knowledge and confidence, and the latter is a bit more of a personal opinion.
So I hope this helps you look at the tradeoffs and select what is right for you.
I have to implement a testing platform. My database needs the following tables: Students, Teachers, Admins, Personnel and others. I would like to know if it's more efficient to have the FirstName and LastName in each of these tables, or to have another table, Persons, and each of the other table to be linked to this one with PersonID.
Personally, I like it this way, although trickier to implement, because I think it's cleaner, especially if you look at it from the object-oriented point of view. Would this add an unnecessary overhead to the database?
Don't know if it helps to mention I would like to use SQL Server and ADO.NET Entity Framework.
As you've explicitly mentioned OO and that you're using EntityFramework, perhaps its worth approaching the problem instead from how the framework is intended to work - rather than just building a database structure and then trying to model it?
Entity Framework Code First Inheritance : Table Per Hierarchy and Table Per Type is a nice introduction to the various strategies that you could pick from.
As for the note on adding unnecessary overhead to the database - I wouldn't worry about it just yet. EF is generally about getting a product built more rapidly and as it has to cope with a more general case, doesn't always produce the most efficient SQL. If the performance is a problem after your application is built, working and correct you can revisit and fix up the most inefficient stuff then.
If there is a person overlap between the mentioned tables, then yes, you should separate them out into a Persons table.
If you are only tracking what role each Person has (i.e. Student vs. Teacher etc) then you might consider just having the following three tables: Persons, Roles, and a bridge table PersonRoles.
On the other hand, if each role has it's own unique fields, then you should carry on as you are and leave each of these tables separate with a foreign key of PersonID.
If the attributes (i.e. First Name, Last Name, Gender etc) of these entities (i.e. Students, Teachers, Admins and Personnel) are exactly the same then you could just make a single table for all the entities with PersonType or Role attribute added to distinguish each person's role. However, if the entities has a lot of different attributes then it would be better that you create separate tables otherwise you will have normalization problem.
Yes that is a very bad way of structuring a DB. The DB structure should be designed based on the Normalizations.
Please check the normalization forms.
U should avoid the duplicate data as much as possible, else the queries will become slower.
And the main problem is when u r trying to get data that is associated with more than one or two tables.
I have an ERP application with about 50 small lookup tables containing non-transactional data. Examples are ItemTypes, SalesOrderStatuses etc. There are so many different types and categories and statuses and with every new module new lookup tables are being added. I have a service to provide List objects out of these tables. These tables usually contain only two columns, (Id and Description). They have only a couple of rows, 8 - 10 rows at max.
I am thinking about putting all of them in one table with ID, Description and LookupTypeID. With this one table I will be able to get rid of 50 tables. Is it good idea? Bad Idea? Very bad idea?
Are there any standards/best-practices for managing small lookup tables?
Among some professionals, the single common lookup table is a design error you should avoid. At the very least, it will slow down performance. The reason is that you will have to have a compound primary key for the common table, and lookups via a compound key will take longer than lookups via a simple key.
According to Anith Sen, this is the first of five design errors you should avoid. See this article: Five Simple Design Errors
Merging lookup tables is a bad idea if you care about integrity of your data (and you should!):
It would allow "client" tables to reference the data they were not meant to reference. E.g. the DBMS will not protect you from referencing SalesOrderStatuses where only ItemTypes should be allowed - they are now in the same table and you cannot (easily) separate the corresponding FKs.
It would force all lookup data to share the same columns and types.
Unless you have a performance problems due to excessive JOINs, I recommend you stay with your current design.
If you do, then you could consider using natural instead of surrogate keys in the lookup tables. This way, the natural keys gets "propagated" through foreign keys to the "client" tables, resulting in less need for JOINing, at the price of increased storage space. For example, instead of having ItemTypes {Id PK, Description AK}, only have ItemTypes {Description PK}, and you no longer have to JOIN with ItemTypes just to get the Description - it was automatically propagated down the FK.
You can store them in a text search (ie nosql) database like Lucene. They are ridiculously fast.
I have implemented this to great effect. Note though that there is some initial setup to overcome, but not much. Lucene queries on ids are a snap to write.
The "one big lookup table" approach has the problem of allowing for silly values -- for example "color: yellow" for trucks in the inventory when you only have cars with "color: yellow". One Big Lookup Table: Just Say No.
Off-hand, I would go with the natural keys for the lookup tables unless you would have cases like "the 2012 model CX300R was red but the 2010-2011 models CX300R were blue (and model ID also denotes color)".
Traditionally if you ask a DBA they will say you should have separate tables. If you asked a programmer they would say using the single table is easier. (Makes making a Edit Status webpage very easy you just make one webpage and pass it a different LookupTypeID instead of lots of similar pages)
However now with ORM the SQL and Code to access different status tables is not really any extra effort.
I have used both method and both work fine. I must admit using a single status table is easiest. I have done this for small apps and also enterprise apps and have noticed no performance impacts.
Finally the other field I normally like to add on these generic status tables is a OrderBy field so you can sort the status in your UI by something other than the description if needed.
Sounds like a good idea to me. You can have the ID and LookupTypeID as a multi-attribute primary key. You just need to know what all of the different LookupTypeIDs represent and you should be good as gold.
EDIT: As for the standards/best-practices, I honestly don't have an answer for you. I've only had one semester of SQL/database design so I haven't been all too exposed to the matter.
I have a table that has a bunch of fields. The fields can be broken into logical groups - like a job's project manager info. The groupings themselves aren't really entity candidates as they don't and shouldn't have their own PKs.
For now, to group them, the fields have prefixes (PmFirstName for example) but I'm considering breaking them out into multiple tables with 1:1 relations on the main table.
Is there anything I should watch out for when I do this? Is this just a poor choice?
I can see that maybe my queries will get more complicated with all the extra joins but that can be mitigated with views right? If we're talking about a table with less than 100k records is this going to have a noticeable effect on performance?
Edit: I'll justify the non-entity candidate thoughts a little further. This information is entered by our user base. They don't know/care about each other. So its possible that the same user will submit the same "projectManager name" or whatever which, at this point, wouldn't be violating any constraint. Its for us to determine later on down the pipeline if we wanna correlate entries from separate users. If I were to give these things their own key they would grow at the same rate the main table grows - since they are essentially part of the same entity. At no pt is a user picking from a list of available "project managers".
So, given the above, I don't think they are entities. But maybe not - if you have further thoughts please post.
I don't usually use 1 to 1 relations unless there is a specific performance reason for it. For example storing an infrequently used large text or BLOB type field in a separate table.
I would suspect that there is something else going on here though. In the example you give - PmFirstName - it seems like maybe there should be a single pm_id relating to a "ProjectManagers" or "Employees" table. Are you sure none of those groupings are really entity candidates?
To me, they smell unless for some rows or queries you won't be interested in the extra columns. e.g. if for a large portion of your queries you are not selecting the PmFirstName columns, or if for a large subset of rows those columns are NULL.
I like the smells tag.
I use 1 to 1 relationships for inheritance-like constructs.
For example, all bonds have some basic information like CUSIP, Coupon, DatedDate, and MaturityDate. This all goes in the main table.
Now each type of bond (Treasury, Corporate, Muni, Agency, etc.) also has its own set of columns unique to it.
In the past we would just have one incredibly wide table with all that information. Now we break out the type-specific info into separate tables, which gives us much better performance.
For now, to group them, the fields have prefixes (PmFirstName for example) but I'm considering breaking them out into multiple tables with 1:1 relations on the main table.
Create a person table, every database needs this. Then in your project table have a column called PMKey which points to the person table.
Why do you feel that the group of fields are not an entity candidates? If they are not then why try to identify them with a prefix?
Either drop the prefixes or extract them into their own table.
It is valuable splitting them up into separate tables if they are separate logical entities that could be used elsewhere.
So a "Project Manager" could be 1:1 with all the projects currently, but it makes sense that later you might want to be able to have a Project Manager have more than one project.
So having the extra table is good.
If you have a PrimaryFirstName,PrimaryLastName,PrimaryPhone, SecondaryFirstName,SecondaryLastName,SEcondaryPhone
You could just have a "Person" table with FirstName, LastName, Phone
Then your original Table only needs "PrimaryId" and "SecondaryId" columns to replace the 6 columns you previously had.
Also, using SQL you can split up filegroups and tables across physical locations.
So you could have a POST table, and a COMMENT Table, that have a 1:1 relationship, but the COMMENT table is located on a different filegroup, and on a different physical drive with more memory.
1:1 does not always smell. Unless it has no purpose.
I've done many web apps where the first thing you do is make a user table with usernames, passwords, names, e-mails and all of the other usual flotsam. My current project presents a situation where non-users records need to function similarly to users, but do not need to the ability to be a first order user.
Is it reasonable to create a second table, people_tb, that is the main relational table and data store, and only use the users_tb for authentication? Does separating user_tb from people_tb present any problems? If this is commonly done, what are some strategies and solutions as well as drawbacks?
This is certainly a good idea, as you are normalizing the database. I have done a similar design in an app that I am writing, where I have an employee table and a user table. Users may a from an external company or an employee, so I have separate tables because an employee is always a user, but a user may not be an employee.
The issues that you'll run into is that whenever you use the user table, you'll nearly always want the person table to get the name or other common attributes you would want to show up.
From a coding standpoint, if you're using straight SQL, it will take a little more effort to mentally parse the select statement. It may be a little more complicated if you're using an ORM library. I don't have enough experience with those.
In my application, I'm writing it in Ruby on Rails, so I'm constantly doing things like employee.user.name, where if I kept them together, it would be just employee.name or user.name.
From a performance standpoint, you are hitting two tables instead of one, but given proper indexes, it should be negligible. If you had an index that contained the primary key and the person name, for instance, the database would hit the user table, then the index for the person table (with a nearly direct hit), so the performance would be nearly the same as having one table.
You could also create a view in the database to keep both tables joined together to give you additional performance enhancements. I know in the later versions of Oracle you can even put an index on a view if needed to increase performance.
I routinely do that because for me the concept of "user" (username, password, create date, last login date) is different from "person" (name, address, phone, email). One of the drawbacks that you may find is that your queries will often require more joins to get the info you're looking for. If all you have is a login name, you'll need to join the "people" table to get the first and last name for example. If you base everything around the user id primary key, this is mitigated a bit, but still pops up.
If user_tb has auth info, I would very much keep it separate from people_tb. I would however keep a relationship between the two, and most of users' info would be stored in people_tb except all of the info needed for auth (which i guess will not be used for much else) Its a nice tradeoff between design and efficiency i think.
That is definitely what we do as we have millions of people records and only thousands of users. We also separate address, phones and emails into relational tables as many people have more than one of each of these things. Critial is to not rely on name as the identifier as name is not unique. Make sure the tables are joined through some type of surrogate key (an integer or a GUID is preferable) not name.
I always try to avoid as much data repetition as possible. If not all people need to login, you can have a generic people table with the information that applies to both people and users (eg. firstname, lastname, etc).
Then for people that login, you can have a users table that has a 1~1 relationship with people. This table can store the username and password.
I'd say go for the normalized design (two tables) and only denormalize (go down to one user/person table) if it will really make your life easier down the line. If however practically all people are also users it may be simpler to denormalize up front. Its up to you; I have used the normalized approach without problems.
Very reasonable.
As an example, take a look at the aspnet_* services tables here.
Their built in schema has a aspnet_Users and aspnet_Membership with the later table having more extended information about a given user (hashed passwords, etc) but the aspnet_User.UserID is used in the other portions of the schema for referential integrity etc.
Bottom line, it's very common, and good design, to have attributes in a separate table if they are different entities, as in your case.