I am attempting to merge data from various sources into an existing data model. Each source uses different types of IDs (such as GUID, Salesforce IDs, etc.). For example, if I were to merge data from two different sources, the table may look like the following (where the first two SalesPersonIDs are GUID IDs and the second two are Salesforce IDs):
Is this a bad practice? I could also imagine a table where each ID type was its own column and could be left blank if it was not applicable. Something like the following:
I apologize, I am a bit new to this. Thanks in advance for any insight, I greatly appreciate it!
The big roles of an ID column are to act as a key connecting data in different tables, and to help indexing - quickly find rows so your queries run fast.
The second solution wouldn't work well for these purposes, and will lead to big headaches in queries: every time you want to group by the ID, you'll have to combine the info from 2 columns in some way, hopefully getting a correct unique result every time.
On the one hand, all you might ever need from an ID is for it to be unique. The first solution might be fine this respect - but are you sure you'll never, ever get data about one SalesPerson from more than one source?
I'd suggest keeping all the IDs in one column, and adding a column to say what kind of ID this is. At least this way, you won't lose any information and can do other things in the future.
One thing you might consider is making a separate table of SalesPerson with all their possible IDs, and have this keyed to other (Sales?) data by a unique ID used only in your database.
Related
Suppose reviews can have zero or more tags.
One could implement this using three tables, Review/Tag/ReviewTagRelation.
ReviewTagRelation would have foreign key to Review and Tag table.
Or using two tables Review/Tag. Review has a json field to hold the list of tag ids.
Traditional approach seems to be the one using the three tables.
I wonder if it is ok to use the two tables approach when there's no need to reference reviews from tags.
i.e. I only need to know what tags are associated with a given review.
In my experience it is always best to keep the data in your database normalized, unless there is a clean and clear cut reason for not doing so that makes sense as per your business requirements.
With normalized data, you know that no matter what, you will always be able to write a query to receive exactly what you are looking for, and if for some reason you want to return data as json, you can do so in your select query.
In our database design we have a couple of tables that describe different objects but which are of the same basic type. As describing the actual tables and what each column is doing would take a long time I'm going to try to simplify it by using a similar structured example based on a job database.
So say we have following tables:
These tables have no connections between each other but share identical columns. So the first step was to unify the identical columns and introduce a unique personId:
Now we have the "header" columns in person that are then linked to the more specific job tables using a 1 to 1 relation using the personId PK as the FK. In our use case a person can only ever have one job so the personId is also unique across the Taxi driver, Programmer and Construction worker tables.
While this structure works we now have the use case where in our application we get the personId and want to get the data of the respective job table. This gets us to the problem that we can't immediately know what kind of job the person with this personId is doing.
A few options we came up with to solve this issue:
Deal with it in the backend
This means just leaving the architecture as it is and look for the right table in the backend code. This could mean looking through every table present and/or construct a semi-complicated join select in which we have to sift through all columns to find the ones which are filled.
All in all: Possible but means a lot of unecessary selects. We also would like to keep such database oriented logic in the actual database.
Using a Type Field
This means adding a field column in the Person table filled for example with numbers to determine the correct child table like:
So you could add a 0 in Type if it's a taxi driver, a 1 if it's a programmer and so on...
While this greatly reduced the amount of backend logic we then have to make sure that the numbers we use in the Type field are known in the backend and don't ever change.
Use separate IDs for each table
That means every job gets its own ID (has to be nullable) in Person like:
Now it's easy to find out which job each person has due to the others having an empty ID.
So my question is: Which one of these designs is the best practice? Am i missing an obvious solution here?
Bill Karwin made a good explanation on a problem similar to this one. https://stackoverflow.com/a/695860/7451039
We've now decided to go with the second option because it seem to come with the least drawbacks as described by the other commenters and posters. As there was no actual answer portraying the second option as a solution i will try to summarize our reasoning:
Against Option 1:
There is no way to distinguish the type from looking at the parent table. As a result the backend would have to include all logic which includes scanning all tables for the that contains the id. While you can compress most of the logic into a single big Join select it would still be a lot more logic as opposed to the other options.
Against Option 3:
As #yuri-g said this one is technically not possible as the separate IDs could not setup as primary keys. They would have to be nullable and as a result can't be indexed, essentially rendering the parent table useless as one of the reasons for it was to have a unique personID across the tables.
Against a single table containing all columns:
For smaller use cases as the one i described in the question this might me viable but we are talking about a bunch of tables with each having roughly 2-6 columns. This would make this option turn into a column-mess really quickly.
Against a flat design with a key-value table:
Our properties have completly different data types, different constraints and foreign key relations. All of this would not be possible/difficult in this design.
Against custom database objects containt the child specific properties:
While this option that #Matthew McPeak suggested might be a viable option for a lot of people our database design never really used objects so introducing them to the mix would likely cause confusion more than it would help us.
In favor of the second option:
This option is easy to use in our table oriented database structure, makes it easy to distinguish the proper child table and does not need a lot of reworking to introduce. Especially since we already have something similar to a Type table that we can easily use for this purpose.
Third option, as you describe it, is impossible: no RDBMS (at least, of I personally know about) would allow you to use NULLs in PK (even composite).
Second is realistic.
And yes, first would take up to N queries to poll relatives in order to determine the actual type (where N is the number of types).
Although you won't escape with one query in second case either: there would always be two of them, because you cant JOIN unless you know what exactly you should be joining.
So basically there are flaws in your design, and you should consider other options there.
Like, denormalization: line non-shared attributes into the parent table anyway, then fields become nulls for non-correpondent types.
Or flexible, flat list of attribute-value pairs related through primary key (yes, schema enforcement is a trade-off).
Or switch to column-oriented DB: that's a case for it.
So I've done extensive searching on this and I can't seem to find a good solution that actually applies to my situation.
I have a list of projects in a table, then a list of people. I want to assign multiple people to one project. Seems pretty common. Obviously, I can't make multiple columns on my projects table for each person, as the people will change fairly frequently.
I need to display this information very quickly in a continuous list of projects (the ultimate way would be a multiple-select combobox as a listbox is too tall, but they don't exist outside of the dreaded lookup fields)
I can think of two ways:
- Store multiple employee IDs delimited by commas in one field in my projects table (I know this goes against good database design). Would require some code to store and retrieve the data.
- Have a separate table for employees assigned to projects (ID, ProjectID, EmployeeID). One to many relationship between projects table and this new table. One to many relationship between employees table and this new table. If a project has 3 employees assigned, it would store 3 records in this table. It seems a bit odd joining both tables in this way, and would also require code to get it to store and retrieve into a control like the one mentioned above).
Does anyone know if there is a better way (including displaying in an easy control) or how you usually tackle this problem?
The usual way to tackle this problem would be with a Junction Table. This is what you describe where you have a separate table maybe called EmployeeProject which has an EmployeeProjectID(PK), EmployeeID(FK) and ProjectID(FK).
In this way you model a Many-to-Many relationship where each project can have many employees involved and each employee can be involved in many projects. It's not actually all that difficult to do the SQL etc. required to pull the information back together again for display.
I would definitely stay away from storing comma-delimited values as this becomes significantly more complicated when you want to display or manipulate the data.
There's a good guide here: http://en.tekstenuitleg.net/articles/software/create-a-many-to-many-relationship-in-access but if you google "many to many junction table" or similar, there are thousands of pages/articles about implementation.
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.
I am putting together a schema for a database. The goal of the database is to track applications in our department. I have a repeated problem that I am trying to solve.
For example, I have an "Applications" table. I want to keep track if any application uses a database or a bug tracking system so right now I have fields in the Applications table called
Table: Applications
UsesDatabase (bit)
Database_ID (int)
UsesBugTracking (bit)
BugTracking_ID (int)
Table: Databases:
id
name
Table: BugTracking:
id
name
Should I consolidate the "uses" column with the respective ID columns so there is only one bug tracking column and only one database column in the applications table?
Any best practice here for database design?
NOTE: I would like to run reports like "Percent of Application that use bug tracking" (although I guess either approach could generate this data.)
You could remove the "uses" fields and make the id columns nullable, and let a null value mean that it doesn't use the feature. This is a common way of representing a missing value.
Edit:
To answer your note, you can easily get that statistics like this:
select
count(*) as TotalApplications,
count(Database_ID) as UsesDatabase,
count(BugTracking_ID) as UsesBugTracking
from
Applications
Why not get rid of the two Use fields and simply let a NULL value in the _ID fields indicate that the record does not use that application (bug tracking or database)
Either solution works. However, if you think you may want to occasionally just get a list of applications which do / do not have databases / bugtracking consider that having the flag fields reduces the query by one (or two) joins.
Having the bit fields is slightly denormalized, as you have to keep two fields in sync to keep one piece of data updated, but I tend to prefer them for cases like this for the reason I gave in the prior paragraph.
Another option would be to have the field nullable, and put null in it for those entries which do not have DBs / etc, but then you run into problems with foreign key constraints.
I don't think there is any one supreme right way, just consider the tradeoffs and go with what makes sense for your application.
I would use 3 tables for the objects: Application, Database, and BugTracking. Then I would use 2 join tables to do 1-to-many joins: ApplicationDatabases, and ApplicationBugTracking.
The 2 join tables would have both an application_id and the id of the other table. If an application used a single database, it would have a single ApplicationDatabases record joining them together. Using this setup, an application could have 0 database (no records for this app in the ApplicationDatabases table), or many databases (multiple records for this app in the ApplicationDatabases table).
"Should i consolidate the "uses" column"
If I look at your problem statement, then there either is no "uses" column at all, or there are two. In either case, it is wrong of you to speak of "THE" uses column.
May I politely suggest that you learn to be PRECISE when asking questions ?
Yes using null in the foreign key fields should be fine - it seems superfluous to have the bit fields.
Another way of doing it (though it might be considered evil by database people ^^) is to default them to 0 and add in an ID 0 data row in both bugtrack and database tables with a name of "None"... when you do the reports, you'll have to do some more work unless you present the "None" values as they are as well with a neat percentage...
To answer the edited question-
Yes, the fields should be combined, with NULL meaning that the application doesn't have a database (or bug tracker).