I'm having conception difficulties to implement something in a database. I have two solutions for a problem, and I was wondering which one is the best.
Problem :
Let's picture a table speciality with 2 fields : speciality_id and speciality_name.
So for example :
1 - Mage
2 - Warrior
3 - Priest
Now, I have a table user with fields such as user_id, name, firstname etc ...
In this table, there is a field called speciality. The speciality stores an integer, corresponding to the speciality_id of the table speciality.
That would be acceptable for users that have only one speciality. I want to improve the model to be able to have multiple specialities for a user.
Here are my two solutions :
Create a table 'solution1' which link the user_id with the speciality_id and remove the speciality field in the user table. So for a user which has 2 specialities, 2 rows will be created in the table 'solution1'.
Change the type of the field speciality in the user table to be able to write down the specialities, separated with commas.
For example 2;3
The problem I got with the second solution is for making foreign keys between my table user and my table specialities, to link them. I may have a bit more difficulties with the PHP in the future too, while wanting to get the specilities for a user (will need to use a parser I guess).
Which solution do you find is the best ?
Thanks.
Absolutely go with your first solution.
Create a third "Many-to-Many" table that allows you to relate a user to multiple specialties. This is the only way to go in your case.
When designing tables, you always want to have each column contain one and only one data element. Think about what querying your second solution would look like. What would you do when you wanted to see all users who had a given specialty?
You might try something like this:
select * from user where specialty like '%2%'
Well, what happens when you have specialties that go to 12? Now "2" matches multiple entities. You could devolve further and try to be tricky, but...you really should just make your data design as normal as possible to avoid all the mess, headache, and errors. Go with Solution 1.
i think the best way is to follow solution1 cause solution2 will end up will lot of complexity later on
I'm and intern and I've been tasked with something I'm pretty unfamiliar with. My manager has requested I create a simple MySQL database using data from an Excel file(s) and I have no idea where to start. I would normally ask someone here for help but everyone seems to be really busy. Basically, the purpose of the database is to see what different object-groups relate to one another so as to keep things standardized. Trying not to go into detail about things not really relevant.
I was asked to first design a schema for the database and then I would get an update on how to implement it. Would I just start by writing queries to create tables? I'm assuming I would need to convert the Excel files to .csv, how do I read this data and send it to the correct table based on Object Type (an attribute of each object, represented in a column)?
I don't want to ask too much right now, but if someone could help me understand what I need to do to get started I would really appreciate it.
Look at the column headers in your spread sheet.
Decide which columns relate to Objects and which columns relate to Groups
The columns that relate to just Objects will become your field names for the Object table. Give this table an ID field so you can uniquely identify each Object.
The columns that relate to the Groups will become field names for a Group table. Give this table an ID field so you can uniquely identify each Group.
Think about if an Object can be in more than one Group - if so you will probably need an Object-Group table. This table would most likely contain an ObjectID and a GroupID.
I know this may be a simple question and if I knew what I was looking for in specific I might be able to find it on my own. However this idea is a little out of the box in my line of normal thinking. So the question is, can I store an object/array of data in a single column that is actually searchable without having to break the object/array down with server-side script.
What the concept is, is I have a table in my db currently and its not even a definite table currently. But what I was initially thinking of having is a single table that each row will have a unique id and with this id a set of numbers (or more if I can actually store an object). What this data is, is my hope for not have rows of what could be redundant data. This is part of a one-to-many / many-to-many concept. The only thing I can think of off the top of my head is Google+ and it's "Circles" I want to be able to take a set of things group them together in a Circle like thing. Where if I choose that circle it will only show to those I want it show to.
Maybe I have this all wrong. If so, if someone can point me in a more solid direction that would be awesome. Bottom line is, I have a series of tables that have one distinct ID across all of them that is unique. This table is hoped to bridge some of those IDs to other things I have in the works. Where I can group these IDs together with one distinct id.
You probably want to implement an ER diagram like this example:
A user can have zero, one or more circles.
Then there's a many-to-many relationship between users and circles.
I'm a software developer. I love to code, but I hate databases... Currently, I'm creating a website on which a user will be allowed to mark an entity as liked (like in FB), tag it and comment.
I get stuck on database tables design for handling this functionality. Solution is trivial, if we can do this only for one type of thing (eg. photos). But I need to enable this for 5 different things (for now, but I also assume that this number can grow, as the whole service grows).
I found some similar questions here, but none of them have a satisfying answer, so I'm asking this question again.
The question is, how to properly, efficiently and elastically design the database, so that it can store comments for different tables, likes for different tables and tags for them. Some design pattern as answer will be best ;)
Detailed description:
I have a table User with some user data, and 3 more tables: Photo with photographs, Articles with articles, Places with places. I want to enable any logged user to:
comment on any of those 3 tables
mark any of them as liked
tag any of them with some tag
I also want to count the number of likes for every element and the number of times that particular tag was used.
1st approach:
a) For tags, I will create a table Tag [TagId, tagName, tagCounter], then I will create many-to-many relationships tables for: Photo_has_tags, Place_has_tag, Article_has_tag.
b) The same counts for comments.
c) I will create a table LikedPhotos [idUser, idPhoto], LikedArticles[idUser, idArticle], LikedPlace [idUser, idPlace]. Number of likes will be calculated by queries (which, I assume is bad). And...
I really don't like this design for the last part, it smells badly for me ;)
2nd approach:
I will create a table ElementType [idType, TypeName == some table name] which will be populated by the administrator (me) with the names of tables that can be liked, commented or tagged. Then I will create tables:
a) LikedElement [idLike, idUser, idElementType, idLikedElement] and the same for Comments and Tags with the proper columns for each. Now, when I want to make a photo liked I will insert:
typeId = SELECT id FROM ElementType WHERE TypeName == 'Photo'
INSERT (user id, typeId, photoId)
and for places:
typeId = SELECT id FROM ElementType WHERE TypeName == 'Place'
INSERT (user id, typeId, placeId)
and so on... I think that the second approach is better, but I also feel like something is missing in this design as well...
At last, I also wonder which the best place to store counter for how many times the element was liked is. I can think of only two ways:
in element (Photo/Article/Place) table
by select count().
I hope that my explanation of the issue is more thorough now.
The most extensible solution is to have just one "base" table (connected to "likes", tags and comments), and "inherit" all other tables from it. Adding a new kind of entity involves just adding a new "inherited" table - it then automatically plugs into the whole like/tag/comment machinery.
Entity-relationship term for this is "category" (see the ERwin Methods Guide, section: "Subtype Relationships"). The category symbol is:
Assuming a user can like multiple entities, a same tag can be used for more than one entity but a comment is entity-specific, your model could look like this:
BTW, there are roughly 3 ways to implement the "ER category":
All types in one table.
All concrete types in separate tables.
All concrete and abstract types in separate tables.
Unless you have very stringent performance requirements, the third approach is probably the best (meaning the physical tables match 1:1 the entities in the diagram above).
Since you "hate" databases, why are you trying to implement one? Instead, solicit help from someone who loves and breathes this stuff.
Otherwise, learn to love your database. A well designed database simplifies programming, engineering the site, and smooths its continuing operation. Even an experienced d/b designer will not have complete and perfect foresight: some schema changes down the road will be needed as usage patterns emerge or requirements change.
If this is a one man project, program the database interface into simple operations using stored procedures: add_user, update_user, add_comment, add_like, upload_photo, list_comments, etc. Do not embed the schema into even one line of code. In this manner, the database schema can be changed without affecting any code: only the stored procedures should know about the schema.
You may have to refactor the schema several times. This is normal. Don't worry about getting it perfect the first time. Just make it functional enough to prototype an initial design. If you have the luxury of time, use it some, and then delete the schema and do it again. It is always better the second time.
This is a general idea
please don´t pay much attention to the field names styling, but more to the relation and structure
This pseudocode will get all the comments of photo with ID 5
SELECT * FROM actions
WHERE actions.id_Stuff = 5
AND actions.typeStuff="photo"
AND actions.typeAction = "comment"
This pseudocode will get all the likes or users who liked photo with ID 5
(you may use count() to just get the amount of likes)
SELECT * FROM actions
WHERE actions.id_Stuff = 5
AND actions.typeStuff="photo"
AND actions.typeAction = "like"
as far as i understand. several tables are required. There is a many to many relation between them.
Table which stores the user data such as name, surname, birth date with a identity field.
Table which stores data types. these types may be photos, shares, links. each type must has a unique table. therefore, there is a relation between their individual tables and this table.
each different data type has its table. for example, status updates, photos, links.
the last table is for many to many relation storing an id, user id, data type and data id.
Look at the access patterns you are going to need. Do any of them seem to made particularly difficult or inefficient my one design choice or the other?
If not favour the one that requires the fewer tables
In this case:
Add Comment: you either pick a particular many/many table or insert into a common table with a known specific identifier for what is being liked, I think client code will be slightly simpler in your second case.
Find comments for item: here it seems using a common table is slightly easier - we just have a single query parameterised by type of entity
Find comments by a person about one kind of thing: simple query in either case
Find all comments by a person about all things: this seems little gnarly either way.
I think your "discriminated" approach, option 2, yields simpler queries in some cases and doesn't seem much worse in the others so I'd go with it.
Consider using table per entity for comments and etc. More tables - better sharding and scaling. It's not a problem to control many similar tables for all frameworks I know.
One day you'll need to optimize reads from such structure. You can easily create agragating tables over base ones and lose a bit on writes.
One big table with dictionary may become uncontrollable one day.
Definitely go with the second approach where you have one table and store the element type for each row, it will give you a lot more flexibility. Basically when something can logically be done with fewer tables it is almost always better to go with fewer tables. One advantage that comes to my mind right now about your particular case, consider you want to delete all liked elements of a certain user, with your first approach you need to issue one query for each element type but with the second approach it can be done with only one query or consider when you want to add a new element type, with the first approach it involves creating a new table for each new type but with the second approach you shouldn't do anything...
I'm pretty sure I already know the answer, but would like some confirmation...
We received 220 text files of providers. Each file is a different category of provider. In total there are 3.2 million records.
My inclination is to create a category table and a provider table that links to category by an ID, then index any other columns that may be searched on like state, or even last name.
The other option is to have one table per category, but I think other than the smaller row size there are a lot of disadvantages to this approach.
It's a PHP/MySQL implementation.
Anyone think the separate table option is better for any reason?
Thanks,
D.
Go with two table approach -- categories and providers.
This will enable you to
easily adding new categories
easily reverse search Categories based on a column such as state of provider.
It make sense from data-structure point of view as well. One type of data in one table.
I agree with your original thought, and with Nishant's answer. In addition to his points, it also normalizes the data, and allows easy updates if a category changes names for some reason.