I have the following partial database design:
All the tables are dependent on each other so the table bvd_docflow_subdocuments is dependent on the table bdd_docflow_subsets
and the table bvd_docflow_subdocuments is dependent on bvd_docflow_subsets. So I thought I could me smart and use foreign keys on every table (and ON DELETE CASCADE). However the FK are being drilldown how further I go in to the tables.
The problem is the table bvd_docflow_documents has no point having a reference to the 1docflow_documentset_id` PK / FK. Is there a way (and maybe my design is crappy) that only the table standing above it has an FK relationship between the tables and not all the tables above it.
Edit:
More explanation:
In the bvd_docflow_subsets table information is stored about objects to create documents. There is an relation between that table and bvd_docflow_subdocuments table (This table stores master data about all the documents for an subset. (docflow_subset_id is in both tables). This is the link between those to tables.
Going further down we also got the table bvd_docflow_documents this table contains the actual document data. The link between bvd_docflow_documents and bvd_docflow_subdocuments is bvd_docflow_subdocument_id.
On every table I got an foreign key defined so when data is removed on a table all the data linked to that data is also removed.
However when we look to the bvd_docflow_documents table it has all the foreign keys from the other tables (docflow_subset_id and docflow_documentset_id) and there is the problem. The only foreign key needed for that bvd_docflow_documents table is docflow_subdocument_id and no other.
Edit 2
I have changed my design further and removed information that I don't need after initial import of the data.
See the following link for the (total) databse design:
https://sqldbm.com/Project/SQLServer/Share/_AUedvNutCEV2DGLJleUWA
The tables subsets, subdocuments and documents have a many to many relationship so I thought a table in between those 3 documents_subdocuments is the way to go were I define all the different keys for those tables.
I am not used to the database design first and then build it. But, for everything there is a first time, and I try to do make a database that is using standards and is using the power of SQL Server the correct way.
I'll address the bottom-most table and ignore the rest for the most part.
But first some comments. Your schema is simply a model of a system. To provide feedback, one must understand this "system" and how it actually works to evaluate your model. In addition, it is important to understand your entities and your reasons for choosing them and modelling them in the specified manner. Without that understanding all of this guessing based on experience.
And another comment. Slapping an identity column into every table is just lazy modelling IMO. Others will disagree, but you need to also enforce all natural keys. Do you have natural keys? It is rare not to have any. Enforce those that do exist.
And one last comment. Stop the ridiculous pattern of prepending the column names with the table names. And you should really think long and hard about using very long table names. Given what you have, I sense you need a schema for your docflow stuff.
For the documents table, your current PK makes no sense. Again, you've slapped an identity column into the table. By itself, this column is a key for the table. The inclusion of any other columns does not make the key any more "unique" - that inclusion is logical nonsense. Following your pattern, you would designate the identity column as the primary key. But ...
According to your image, the documents table is related to one and only one subdocument. You added a foreign key to that table - which matches the image. You also added additional columns and foreign keys to the "higher" tables. So now a document "points" to a specific subdocument. It also points to a specific subset - which may have no relationship to the subdocument. The same thought applies to the other FK. I have a doubt that this is logically correct. So why do these columns (and related FKs) exist? Perhaps this is the result of premature optimization - which everyone knows is the root of all evil coding. Again, it is impossible to know if this is "right" or even "useful" for your model.
To answer your question "... is there a way", the answer is obviously yes. You remove the columns of which you complain. You added them - Why? Is this perhaps a problem with the tool you are using?
And some last comments. There is nothing special about "varchar(50)". Perhaps this is a place holder that will be updated later. It may also be another sign of laziness. And generally speaking, columns with names like "type" and "code" tend to be foreign keys to "lookup" tables - because people like to add, modify, or remove these sorts categorization values over time. I'm also concerned about the column name overlap among the tables. "Location" exists in multiple tables, as do action_code and action_id. And a column named "id" (action_id) suggests a lookup to another table - is it? Should it be? Is there a relationship between action_id and action_code? From a distance it is impossible to answer any of these questions.
But designing a database is more art than science. Sometimes you just need to create something, populate it with some sample data, and then determine if it works for your needs. Everyone will get something wrong in the first try. That is expected; that is how you learn. The most difficult part is actually completing your first attempt.
The relationship I wanna model goes kinda like this:
A master TextResource object that stores high level shared non-localizable data, like maximum length.
One single detail object we can call SourceText, that needs to be tracked separately.
The rest of detail objects, that we can call TargetText.
Both Source and TargetText objects store a string localized in a particular language, along with other localization data.
But the string stored in SourceText is the original one and hence, even if the data schema is the same, they're not functionally equal and this piece of data needs to exist and be unique per each TextResource master object.
And the options I've thought of are:
Regular master-detail tables, but store the SourceText ID in the master table... Potentially creating a circular reference?
Regular master-detail tables, but add a flag/category column to the detail table that marks a row as Source or Target... Though this could potentially lead to having more than one "Source" detail per master and could make querying for the Source data less straight-forward
Store the Source data in the master table, even if this means having similar columns on both master and detail tables (and screwing normalization while at it)
Create three different tables: master, main and detail. Master (TextResource) and main (SourceText) would have a 1-to-1 relationship while there could be n detail (TargetText) rows per master, but other than that the Source and Target tables would share most of their schema
I see benefits and potential problems on all four approaches, so maybe you could lend me a hand deciding one?
What I want to achieve would boil down to:
Have one, and only one, Source string per Resource
Be able to query Text Resources and their Source strings easily and fast
Be able to query the localized strings of a given Resource, including the Source one, easily and fast
Be able to store versioned data of each localized string, including the Source one
And of course, avoid bad practices and observe normalization
Thanks in advance :)
I am using JCo3. While working with BAPI, i get tables that are part of it. While reading metadata of these tables, i will be interested to know which field is the primary key field for the table.
This is important for me while writing persistence related code in java.
Edited:
In fact, I am interested in all BAPIs. For example: BAPI_PO_CREATE1, BAPI_GOODSMVT_CANCEL, etc
Idea is to make this part of the base classes so that the key is identified automatically. I also would like to understand the exceptions, if any.
I found the function module "DDIF_FIELDINFO_GET" useful to get field level metadata. This metadata has information to indicate if it is a Key field.
Good Luck!!
A lot of the applications I write make use of lookup tables, since that was just the way I was taught (normalization and such). The problem is that the queries I make are often more complicated because of this. They often look like this
get all posts that are still open
"SELECT * FROM posts WHERE status_id = (SELECT id FROM statuses WHERE name = 'open')"
Often times, the lookup tables themselves are very short. For instance, there may only be 3 or so different statuses. In this case, would it be okay to search for a certain type by using a constant or so in the application? Something like
get all posts that are still open
"SELECT * FROM posts WHERE status_id = ".Status::OPEN
Or, what if instead of using a foreign id, I set it as an enum and queried off of that?
Thanks.
The answer depends a little if you are limited to freeware such as PostGreSQL (not fully SQL compliant), or if you are thinking about SQL (ie. SQL compliant) and large databases.
In SQL compliant, Open Architecture databases, where there are many apps using one database, and many users using different report tools (not just the apps) to access the data, standards, normalisation, and open architecture requirements are important.
Despite the people who attempt to change the definition of "normalisation", etc. to suit their ever-changing purpose, Normalisation (the science) has not changed.
if you have data values such as {Open; Closed; etc} repeated in data tables, that is data duplication, a simple Normalisation error: if you those values change, you may have to update millions of rows, which is very limited design.
Such values should be Normalised into a Reference or Lookup table, with a short CHAR(2) PK:
O Open
C Closed
U [NotKnown]
The data values {Open;Closed;etc} are no longer duplicated in the millions of rows. It also saves space.
the second point is ease of change, if Closed were changed to Expired, again, one row needs to be changed, and that is reflected in the entire database; whereas in the un-normalised files, millions of rows need to be changed.
Adding new data values, eg. (H,HalfOpen) is then simply a matter of inserting one row.
in Open Architecture terms, the Lookup table is an ordinary table. It exists in the [SQL compliant] catalogue; as long as the FOREIGN KEY relation has been defined, the report tool can find that as well.
ENUM is a Non-SQL, do not use it. In SQL the "enum" is a Lookup table.
The next point relates to the meaningfulness of the key.
If the Key is meaningless to the user, fine, use an {INT;BIGINT;GUID;etc} or whatever is suitable; do not number them incrementally; allow "gaps".
But if the Key is meaningful to the user, do not use a meaningless number, use a meaningful Relational Key.
Now some people will get in to tangents regarding the permanence of PKs. That is a separate point. Yes, of course, always use a stable value for a PK (not "immutable", because no such thing exists, and a system-generated key does not provide row uniqueness).
{M,F} are unlikely to change
if you have used {0,1,2,4,6}, well don't change it, why would you want to. Those values were supposed to be meaningless, remember, only a meaningful Key need to be changed.
if you do use meaningful keys, use short alphabetic codes, that developers can readily understand (and infer the long description from). You will appreciate this only when you code SELECT and realise you do not have to JOIN every Lookup table. Power users too, appreciate it.
Since PKs are stable, particularly in Lookup tables, you can safely code:
WHERE status_code = 'O' -- Open
You do not have to JOIN the Lookup table and obtain the data value Open, as a developer, you are supposed to know what the Lookup PKs mean.
Last, if the database were large, and supported BI or DSS or OLAP functions in addition to OLTP (as properly Normalised databases can), then the Lookup table is actually a Dimension or Vector, in Dimension-Fact analyses. If it was not there, then it would have to be added in, to satisfy the requirements of that software, before such analyses can be mounted.
If you do that to your database from the outset, you will not have to upgrade it (and the code) later.
Your Example
SQL is a low-level language, thus it is cumbersome, especially when it comes to JOINs. That is what we have, so we need to just accept the encumbrance and deal with it. Your example code is fine. But simpler forms can do the same thing.
A report tool would generate:
SELECT p.*,
s.name
FROM posts p,
status s
WHERE p.status_id = s.status_id
AND p.status_id = 'O'
Another Exaple
For banking systems, where we use short codes which are meaningful (since they are meaningful, we do not change them with the seasons, we just add to them), given a Lookup table such as (carefully chosen, similar to ISO Country Codes):
Eq Equity
EqCS Equity/Common Share
OTC OverTheCounter
OF OTC/Future
Code such as this is common:
WHERE InstrumentTypeCode LIKE "Eq%"
And the users of the GUI would choose the value from a drop-down that displays
{Equity/Common Share;Over The Counter},
not {Eq;OTC;OF}, not {M;F;U}.
Without a lookup table, you can't do that, either in the apps, or in the report tool.
For look-up tables I use a sensible primary key -- usually just a CHAR(1) that makes sense in the domain with an additional Title (VARCHAR) field. This can maintain relationship enforcement while "keeping the SQL simple". The key to remember here is the look-up table does not "contain data". It contains identities. Some other identities might be time-zone names or assigned IOC country codes.
For instance gender:
ID Label
M Male
F Female
N Neutral
select * from people where gender = 'M'
Alternatively, an ORM could be used and manual SQL generation might never have to be done -- in this case the standard "int" surrogate key approach is fine because something else deals with it :-)
Happy coding.
Create a function for each lookup.
There is no easy way. You want performance and query simplicity. Ensure the following is maintained. You could create a SP_TestAppEnums to compare existing lookup values against the function and look for out of sync/zero returned.
CREATE FUNCTION [Enum_Post](#postname varchar(10))
RETURNS int
AS
BEGIN
DECLARE #postId int
SET #postId =
CASE #postname
WHEN 'Open' THEN 1
WHEN 'Closed' THEN 2
END
RETURN #postId
END
GO
/* Calling the function */
SELECT dbo.Enum_Post('Open')
SELECT dbo.Enum_Post('Closed')
Question is: do you need to include the lookup tables (domain tables 'round my neck of the woods) in your queries? Presumably, these sorts of tables are usually
pretty static in nature — the domain might get extended, but it probably won't get shortened.
their primary key values are pretty unlikely to change as well (e.g., the status_id for a status of 'open' is unlikely to suddenly get changed to something other than what it was created as).
If the above assumptions are correct, there's no real need to add all those extra tables to your joins just so your where clause can use a friend name instead of an id value. Just filter on status_id directly where you need to. I'd suspect the non-key attribute in the where clause ('name' in your example above) is more likely to get changes than the key attribute ('name' in your example above): you're more protected by referencing the desire key value(s) of the domain table in your join.
Domain tables serve
to limit the domain of the variable via a foreign key relationship,
to allow the domain to be expanded by adding data to the domain table,
to populate UI controls and the like with user-friendly information,
Naturally, you'd need to suck domain tables into your queries where you you actually required the non-key attributes from the domain table (e.g., descriptive name of the value).
YMMV: a lot depends on context and the nature of the problem space.
The answer is "whatever makes sense".
lookup tables involve joins or subqueries which are not always efficient. I make use of enums a lot to do this job. its efficient and fast
Where possible (and It is not always . . .), I use this rule of thumb: If I need to hard-code a value into my application (vs. let it remain a record in the database), and also store that vlue in my database, then something is amiss with my design. It's not ALWAYS true, but basically, whatever the value in question is, it either represents a piece of DATA, or a peice of PROGRAM LOGIC. It is a rare case that it is both.
NOT that you won't find yourself discovering which one it is halfway into the project. But as the others said above, there can be trade-offs either way. Just as we don't always acheive "perfect" normalization in a database design (for reason of performance, or simply because you CAN take thngs too far in pursuit of acedemic perfection . . .), we may make some concious choices about where we locate our "look-up" values.
Personally, though, I try to stand on my rule above. It is either DATA, or PROGRAM LOGIC, and rarely both. If it ends up as (or IN) a record in the databse, I try to keep it out of the Application code (except, of course, to retrieve it from the database . . .). If it is hardcoded in my application, I try to keep it out of my database.
In cases where I can't observe this rule, I DOCUMENT THE CODE with my reasoning, so three years later, some poor soul will be able to ficure out how it broke, if that happens.
The commenters have convinced me of the error of my ways. This answer and the discussion that went along with it, however, remain here for reference.
I think a constant is appropriate here, and a database table is not. As you design your application, you expect that table of statuses to never, ever change, since your application has hard-coded into it what those statuses mean, anyway. The point of a database is that the data within it will change. There are cases where the lines are fuzzy (e.g. "this data might change every few months or so…"), but this is not one of the fuzzy cases.
Statuses are a part of your application's logic; use constants to define them within the application. It's not only more strictly organized that way, but it will also allow your database interactions to be significantly speedier.
For a school project I'm making a simple Job Listing website in ASP.NET MVC (we got to choose the framework).
I've thought about it awhile and this is my initial schema:
JobPostings
+---JobPostingID
+---UserID
+---Company
+---JobTitle
+---JobTypeID
+---JobLocationID
+---Description
+---HowToApply
+---CompanyURL
+---LogoURL
JobLocations
+---JobLocationID
+---City
+---State
+---Zip
JobTypes
+---JobTypeID
+---JobTypeName
Note: the UserID will be linked to a Member table generated by a MembershipProvider.
Now, I am extremely new to relational databases and SQL so go lightly on me.
What about naming? Should it be just "Description" under the JobPostings table, or should it be "JobDescription" (same with other columns in that main table). Should it be "JobPostingID" or just "ID"?
General tips are appreciated as well.
Edit: The JobTypes are fixed for our project, there will be 15 job categories. I've made this a community wiki to encourage people to post.
A few thoughts:
Unless you know a priori that there is a limited list of job types, don't split that into a separate table;
Just use "ID" as the primary key on each table (we already know it's a JobLocationID, because it's in the JobLocations table...);
I'd drop the 'Job' prefix from the fields in JobPostings, as it's a bit redundant.
There's a load of domain-specific info that you could include, like salary ranges, and applicant details, but I don't know how far you're supposed to be going with this.
Job Schema http://gfilter.net/junk/JobSchema.png
I split Company out of Job Posting, as this makes maintaining the companies easier.
I also added a XREF table that can store the relationship between companies and locations. You can setup a row for each company office, and have a very simple way to find "Alternative Job Locations for this Company".
This should be a fun project...good luck.
EDIT: I would add Created and LastModifiedBy (Referring to a UserID). These are great columns for general housekeeping.
Looks good to me, I would recommend also adding Created, LastModified and Deleted columns to the user updateable tables as well for future proofing.
Make sure you explicitly define your primary and foreign keys as well in your schema.
What about naming? Should it be just
"Description" under the JobPostings
table, or should it be JobDescription
(same with other columns in that main
table). Should it be "JobPostingID" or
just "ID"?
Personally, I specify generic-sounding fields like "ID" and "Description" with prefixes as you suggest. It avoids confusion about what the id/description applies to when you write queries later on (and saves you the trouble of aliasing them).
I'd recommend folding the data you're going to be storing in JobLocations back into the main table. It's ok to have a table for states and another for countries, but I doubt you want a table that contains every city/state/country pair, you really don't gain anything from it. What happens if someone goes in and edits their location? You'd have to check to make sure no other joblisting points to the location and edit it, else create a new location and point to that instead.
My usual pattern is address and city as text with the record and FK to a state table.