For example, here's the problem I faced... I have three tables. Products, Districtrates, Deliverycharges. In my app, a product's delivery will be calculated through a pre-defined rate defined in the Districtrates table. If we want, we can also add a custom rate overriding the pre-defined rate. Each product can have all 25 districts or only some. So here's my solution :
Create three tables as I mentioned above. Districtrates table will only have 25 records for all the 25 districts in my country. For each product, I will add 25 records to the Deliverycharges table with the productID, deliveryrateID and a custom rate value if available. Some products might have less than 25 districts (Only the ones available for that product).
I can even store this in a simple hash in one cell in the products table. Like this : {district1: nil, district2: 234, district4: 543} (It's in Ruby syntax). In here, if the value is nil, we can take the default value from the deliveryrate table. Here also the hash will have all 25 districts! But the above method (creating a table) is easy to work with. The only problem is, it will add nearly 25 records per each product.
So my question is, is this a good thing? This is only one scenario... There are more where we can use one simple array or hash in a cell rather than creating a table. Creating a table is easy to maintain. But is it the right way?
One of the main points of using a relational database is the ability to query (and update) the data in it using SQL.
That only works if you put the data in a form that the database actually understands. Traditionally, this means defining a table schema.
There are now extensions to let the database work with "semi-structured" data (such as XML/JSON/JSONB), but you should only need to go there when the data really does not fit into the relational model, otherwise you are giving up on a lot of features/performance.
If you put a Ruby string into a text column, you will not have any way to use it from SQL. So no proper searching, indexing, or efficient updates of these delivery rates.
I'm working on a project to make a digital form of this paper
this paper (can't post image)
and the data will displayed on a Web in a simple table view. There will be NO altering, deleting, updating. It's just displaying (via SELECT * of course) the data inputted.
The data will be inserted via android app and stored in a single table which has 30 columns in mysql.
and the question is, is it a good idea if i use a single table? because i think there will be no complex operation in the sql.
and the other question is, am i violating some rules for this method?
I need your opinion. thanks.
It's totally ok to use only one table, if that suits your needs. What you can do to make the database a little bit 'smarter' is add new tables for attributes in your paper that will be repeated. So, for example, the Soil Type could be another table where there are two columns, ID and Description, and you will use it as a foreign key in each record in the main table. You need this if you want your database to be in 3NF.
To sum up, yes you can have one table if that's all you need. However, adding more tables might help save some space and make your database more flexible. It's up to you to decide! :)
Being new to relational database design, I am trying to clarify one piece of information to properly design this database. Although I am using Filemaker as the platform, I believe this is a universal question.
Using the logic of ideally having all one to many relationships, and using separate tables or join tables to solve these.
I have a database with multiple products, made by multiple brands, in multiple product categories. I also want this to be as scale-able as possible when it comes to reporting, being able to slice and dice the data in as many ways as possible since the needs of the users are constantly changing.
So when I ask the question "Does each Brand have multiple products" I get a yes, and "Does each product have multiple brands" the answer is no. So this is a one to many relationship, but it also seems that a self-join table might give me everything that I need.
This methodology also seems to go down a rabbit hole for other "product related" information such as product category, each product is tied to one product category, but only one product category is related to a product.
So I see 2 possibilities, make three tables and join them with primary and foreign keys, one for Brand, one for Product Category, and one for Products.
Or the second possibility is to create one table that has the brand and product category and product info all in one table (since they are all product related) and simply do self-joins and other query based tables to give me the future reporting requirements that will be changing over time.
I am looking for input from experiences that might point me in the right direction.
Thanks in advance!
Could you ever want to store additional information about a brand (company URL, phone number, etc.) or about a product category (description, etc.)?
If the answer is yes, you definitely want to use three tables. If you don't, you'll be repeating all that information for every single item that belongs to the same brand or same category.
If the answer is no, there is still an advantage to using three tables - it will prevent typos or other spelling inconsistencies from getting into your database. For example, it would prevent you from writing a brand as "Coca Cola" for some items and as "Coca-Cola" for other items. These inconsistencies get harder and harder to find and correct as your database grows. By having each brand only listed once in it's own table, it will always be written the same way.
The disadvantage of multiple tables is the SQL for your queries is more complicated. There's definitely a tradeoff, but when in doubt, normalize into multiple tables. You'll learn when it's better to de-normalize with more experience.
I am not sure where do you see a room for a self-join here. It seems to me you are saying: I have a table of products; each product has one brand and one (?) category. If that's the case then you need either three tables:
Brands -< Products >- Categories
or - in Filemaker only - you can replace either or both the Brands and the Categories tables with a value list (assuming you won't be renaming brands/categories and at the expense of some reporting capabilities). So really it depends on what type of information you want to get out in the end.
If you truly want your solution to be scalable you need to parse and partition your data now. Otherwise you will be faced with the re-structuring of the solution down the road when the solution grows in size. You will also be faced with parsing and relocating the data to new tables. Since you've also included the SQL and MySQL tags if you plan on connecting Filemaker to an external data source then you will definitely need to up your game structurally.
Building everything in one table is essentially using Filemaker to do Excel work and it won't cut it if you are connecting to SQL, MySQL, etc.
Self join tables are a great tool. However, they should really only be used for calculating small data points and should not be used as pivot points or foundations for your reporting features. It can grow out of control as time goes on and you need to keep your backend clean.
Use summary and sub-summary reporting features to slice product based data.
For retail and general product management solutions, whether it's Filemaker/SQL/or whatever the "Brand" or "Vendor" is it's own table. Then you would have a "Products" table (the match key being the "Brand ID").
The "Product Category" field should be a field in the "Products" table. You can manage the category values by building a standard value list or building a value list based on a "Product Category" table. The second scenario is better for long term administration.
Apologies if this is redundant, and it probably is, I gave it a look but couldn't find a question here that fell in with what I wanted to know.
Basically we have a table with about ~50000 rows, and it's expected to grow much bigger than that. We need to be able to allow admin users to add in custom data to an item based on its category, and users can just pick which fields defined by the administrators they want to add info to.
Initially I had gone with an item_categories_fields table which pairs up entries from item_fields to item_categories, so admins can add custom fields and reuse them across categories for consistency. item_fields has a relationship to item_field_values which links values with fields, which is how we handled things in .NET. The project is using CAKEPHP though, and we're just learning as we go, so it can get a bit annoying at times.
I'm however thinking of maybe just adding an item_custom_fields table that is essentially the item_id and a text field that stores XMLish formatted data. This is just for the values of the custom fields.
No problems if I want to fetch the item by its id as the required data is stored in the items table, but what if I wanted to do a search based on a custom field? Would a
SELECT * FROM item_custom_fields
WHERE custom_data LIKE '%<material>Plastic</material>%'
(user input related issues aside) be practical if I wanted to fetch items made of plastic in this case? Like how slow would that be?
Thanks.
Edit: I was afraid of that as realistically this thing will be around 400k rows for that one table at launch, thanks guys.
Any LIKE query that starts with % will not use any indexes you have on the column, so the query will scan the whole table to find the result.
The response time for that depends highly on your machine and the size of the table, but it definitely won't be efficient in any shape or form.
Your previous/existing solution (if well indexed) should be quite a bit faster.
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...