For example I have photos and videos tables, I can comment on these, but when I send it to database which way is better?
To have 2 tables for comments:
photo_comments and
video_comments
Or to have 1 table comments and
create a row inside the table like
type and put there if it's a
photo_comment or video_comment
I think the 1 is faster because I have less data when I need to query the table but maybe the 2 is easier to use.
Please let me know what's the best way, speed is very important for me.
I'm talking about a very big system with millions of data, millions of comments, so I want the fastest way to get the results, for me doesn't matter if I need to code more or need to keep in mind something in plus, results are much more important!
If you really have two separate data tables photos and videos, I would always choose to use two separate comments tables, too.
Why?
If you put all your comments into a single comments table, but that references media from two separate data tables, there's no way you can easily set up a referential integrity between your comments table and the two data tables. There are some workarounds (like having two separate reference fields, one for each), but none are really very compelling. Not having a referential integrity will ultimately lead to "zombie" data that doesn't belong to any existing media entry.
Having two comments tables allows each comment table to properly reference its associated data table, thus your data integrity in the database will be better.
For that reason, if you have two separate data tables, I would always choose to use two separate comments tables as well.
It depends a bit more on how photos and videos are structured. Consider the following DB Design:
MediaType
----------
ID *
Name
Media
----------
ID *
TypeID
OwnerName
Name
Size
Path
Photo
----------
MediaID *
MediaTypeID (constraint, always set to the photo type)
Height
Width
Video
---------
MediaID *
MediaTypeID (constraint, always set to the video type)
Rating
If Photo and Video both had a FK to MediaType and to Media, I would make Comments relate to the Media table instead of either one, and not to the Photos or Videos table directly. This is often the type of design I use when Photo and Video have a lot of common properties. It's especially useful when you want to do things like security because you aren't boxed into repeating the same visibility and ownership constructs on each type of media you're dealing with. It's also quite fast to query because many queries often look only for common properties, or just type-specific rows, so some tables don't need to be included. Designing the database by modeling these IS-A relationships also keeps your indexes highly selective, which means speed.
If you're locked into your design and Videos and Photos have no commmon "base table", then I would make a separate comments table for each.
Why not having only one comment table? Is there any diffrence between a comment on a video or a photo? If not you should only have a column that holds the foreign key for the video/photo the comment is poiting to and an additional column with the type ENUM that holds the information of the type of resource the comment is ment for.
Using an ENUM will keep your queries very fast (as it is saved as a number) and makes it easy to use string in your query.
Splitting up the tables would be better performance-wise, since you wouldn't have to query on an extra "comment type" column. The downside of doing things this way is not reusing code (possibly in the future, if you add comments to other things). But it doesn't sound like you're concerned with that.
I don't think that the choice of whether to have 1 or 2 tables for comments is going to have any appreciable impact on the performance of your application.
You should choose whichever one makes more sense in the context of your application.
For example, if comments on photos and comments on videos are both going to act in the same way then you should have one table, if however (for example) comments on videos are allowed to be twice as long as comments on photos, or comments on photos have an additional "ranking" field or something, then 2 tables would make more sense.
your queries will either look like
select * from comments where linked_id = 555
or
select * from comments where linked_id = 555 and comment_type = 1
(with comment type=1 meaning it's a video).
As long as comment type as an index, they will basically be just as fast.
Only thing I would consider, is columns. If video comments has a different set of comments from picture comments, split em up. If everything is the same, keep em together.
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.
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.
I have a SQL Server 2008 database with a snowflake-style schema, so lots of different lookup tables, like Language, Countries, States, Status, etc. All these lookup table have almost identical structures: Two columns, Code and Decode. My project manager would like all of these different tables to be one BIG table, so I would need another column, say CodeCategory, and my primary key columns for this big table would be CodeCategory and Code. The problem is that for any of the tables that have the actual code (say Language Code), I cannot establish a foreign key relationship into this big decode table, as the CodeCategory would not be in the fact table, just the code. And codes by themselves will not be unique (they will be within a CodeCategory), so I cannot make an FK from just the fact table code field into the Big lookup table Code field.
So am I missing something, or is this impossible to do and still be able to do FKs in the related tables? I wish I could do this: have a FK where one of the columns I was matching to in the lookup table would match to a string constant. Like this (I know this is impossible but it gives you an idea what I want to do):
ALTER TABLE [dbo].[Users] WITH CHECK ADD CONSTRAINT [FK_User_AppCodes]
FOREIGN KEY('Language', [LanguageCode])
REFERENCES [dbo].[AppCodes] ([AppCodeCategory], [AppCode])
The above does not work, but if it did I would have the FK I need. Where I have the string 'Language', is there any way in T-SQL to substitute the table name from code instead?
I absolutely need the FKs so, if nothing like this is possible, then I will have to stick with my may little lookup tables. any assistance would be appreciated.
Brian
It is not impossible to accomplish this, but it is impossible to accomplish this and not hurt the system on several levels.
While a single lookup table (as has been pointed out already) is a truly horrible idea, I will say that this pattern does not require a single field PK or that it be auto-generated. It requires a composite PK comprised of ([AppCodeCategory], [AppCode]) and then BOTH fields need to be present in the fact table that would have a composite FK of both fields back to the PK. Again, this is not an endorsement of this particular end-goal, just a technical note that it is possible to have composite PKs and FKs in other, more appropriate scenarios.
The main problem with this type of approach to constants is that each constant is truly its own thing: Languages, Countries, States, Statii, etc are all completely separate entities. While the structure of them in the database is the same (as of today), the data within that structure does not represent the same things. You would be locked into a model that either disallows from adding additional lookup fields later (such as ISO codes for Language and Country but not the others, or something related to States that is not applicable to the others), or would require adding NULLable fields with no way to know which Category/ies they applied to (have fun debugging issues related to that and/or explaining to the new person -- who has been there for 2 days and is tasked with writing a new report -- that the 3 digit ISO Country Code does not apply to the "Deleted" status).
This approach also requires that you maintain an arbitrary "Category" field in all related tables. And that is per lookup. So if you have CountryCode, LanguageCode, and StateCode in the fact table, each of those FKs gets a matching CategoryID field, so now that is 6 fields instead of 3. Even if you were able to use TINYINT for CategoryID, if your fact table has even 200 million rows, then those three extra 1 byte fields now take up 600 MB, which adversely affects performance. And let's not forget that backups will take longer and take up more space, but disk is cheap, right? Oh, and if backups take longer, then restores also take longer, right? Oh, but the table has closer to 1 billion rows? Even better ;-).
While this approach looks maybe "cleaner" or "easier" now, it is actually more costly in the long run, especially in terms of wasted developer time, as you (and/or others) in the future try to work around issues related to this poor design choice.
Has anyone even asked your project manager what the intended benefit of this is? It is a reasonable question if you are going to spend some amount of hours making changes to the system that there be a stated benefit for that time spent. It certainly does not make interacting with the data any easier, and in fact will make it harder, especially if you choose a string for the "Category" instead of a TINYINT or maybe SMALLINT.
If your PM still presses for this change, then it should be required, as part of that project, to also change any enums in the app code accordingly so that they match what is in the database. Since the database is having its values munged together, you can accomplish that in C# (assuming your app code is in C#, if not then translate to whatever is appropriate) by setting the enum values explicitly with a pattern of the first X digits are the "category" and the remaining Y digits are the "value". For example:
Assume the "Country" category == 1 and the "Language" catagory == 2, you could do:
enum AppCodes
{
// Countries
United States = 1000001,
Canada = 1000002,
Somewhere Else = 1000003,
// Languages
EnglishUS = 2000001,
EnglishUK = 2000002,
French = 2000003
};
Absurd? Completely. But also analogous to the request of merging all lookup tables into a single table. What's good for the goose is good for the gander, right?
Is this being suggested so you can minimise the number of admin screens you need for CRUD operations on your standing data? I've been here before and decided it was better/safer/easier to build a generic screen which used metadata to decide what table to extract from/write to. It was a bit more work to build but kept the database schema 'correct'.
All the standing data tables had the same basic structure, they were mainly for dropdown population with occasional additional fields for business rule purposes.
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.