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Consider a trip itinerary. There are 20 possible stops on a tour. A standard tour involves stops 1 through 20 in order. However, each user may create their own tour consisting of 5 or more stops in any order with possibility for repeats. What is the most efficient way to model this in a database?
If we use a join table
user_id, stop_id, order
we would have millions of records very quickly but we could easily pull the stop & user attributes on queries.
If we stored the stops as an array,
user_id, stop_id_array_in_order
we have a much smaller, non-normalized table and we cannot easily access the stop attributes.
Are there other options that allow for accessing of parent attributes while minimizing table size?
I would define the entities and create tables for them with the relations between them in separate tables as you described in the first example:
users table
tours table
stops table
tours_users table (a User can go to a Tour more than once)
stops_order table: stop_id, order, tours_users_id
For querying the tables, for any user you want to check their tour you can achieve this with the tours_users table , if the stops needs to be retrieved , you can easily join the tours_users table with the stops_order table through the tours_users_id.
If the tables are indexed correctly, there should be no problem with performance and you will be using the relational database engine as you supposed to.
You're thinking that saving some space will help you. It won't. It's also arguable how much space you'd actually save.
You'd also be using an unordered data structure - that's something you don't want. You want ordered structure (table) which can relate to other records - and that's exactly the reason why we normalize tables - so we can extrapolate all kinds of data without altering physical location. The other benefit is that ordered structures can be indexed and we can reduce the amount of time finding the records. Tradeoff is spending space to keep the index records.
However, millions, billions - even trillions of rows are ok. Just imagine how difficult it would be querying a structure where an array is saved as a comma separated list in a column (or multiple columns). It would be a nightmare to write a query, and performance would go down linearly as amount of records goes up.
TL;DR: keep it normalized.
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I will use this database to build a website using Laravel Framework.
from my experience, when you are developing an online store, the information about orders should be stored separately, not with relations
let me give you an example:
i order product A, my order is being processed, meanwhile, you delete product A from your database (different reasons), if you have the product_id in my order, what will happen?.
Also, you should make an intersection table for users and payment details, they may have more credit cards. An intersection table for users and delivery addresses would also be easier to manage than a text colum
As others mentioned this is too broad to answer.
But I can give you some pointers to remember.
Normalization
This is the primary purpose of relationships. Basically this is not duplicating data, so you wouldn't put a state in every address you would have a state table and put it's id in the address.
You have some of this, but you can over normalize too. Like the payment status. Likely these wont change much over time so you could use an ENUM field which is basically a text field with a list of acceptable values in it.
Pretty much if you have a One to One relationship, you don't really need another table for it. The only reason I can think of was back when InnoDB didn't have full text support, then you could make a MyIsam table and a InnoDB table to kind of use both their benefits. Otherwise it just makes things harder because you have an extra join, and you have to make user that you tables dont become a Many to One relationship.
An example in yours is Orders and Delivery Addresses, this would probably be a one to one, it's not like you can deliver the same item to more then one address. Your probably thinking, I can reuse those addresses for different orders, but if you read below you might see why that is not always a good idea. Which is not saying you cant use them again, you just probably shouldn't allow edits to them and that can cause a whole cascade of issues.
Consistancy
When dealing with things like orders, you should bake as much data into the table as you can. This is de-normalization. But the reason is that, products can be deleted addresses can change etc. You don't want these things affecting your orders later. So by baking that data in you don't have to worry about not being able to change those things. Obviously you still want some links like to the User but you may want to bake in the email they used for that order, that way latter if they say I didn't get the email, you can know what email was used not the one they currently have, maybe they changed it.
Hierarchies
This is specifically for the category table, you may want to look at some of the hierarchy models like nested set, or adjacency list. This will eliminate tables and allow more nesting levels. It's quite a bit harder to setup, but it's way more flexible.
Another choice is to use something like a tag system, where you have a list of tags and associate those with the products through a many to many relationship. I think we all know what tags are but if your not sure, than look at the tags on Stack Overflow. These can help improve search results and help tie related products together even if they are in different categories. For example you could have
veggies > potatoes
utensils > potato peelers
They are related, but you probably won't put them in the same category.
You could even use both!
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I would like to know if it is possible to have the following database behaviour:
Create a USER table, with primary key USER_ID
Data comes in from external source: e.g. "USER_ID, TIMESTAMP, DATA"
For each user in the USER table, create a table to store only data entries pertinent to USER_ID, and store all incoming Data with the correct USER_ID into that table
When querying all the data entries for a specific USER_ID, just return all rows from that table.
I could of course do this all in one table "ALLDATALOG" and then search for all entries in ALLDATALOG that contain USER_ID, but my concern is that as the ALLDATALOG table grows, searches will take too long.
You should not split your tables like that. You will want an index on the USER_ID column in your data log table. Searches do become slower as data size increases, but your strategy will not necessarily mitigate that. It will however make your application more complex to write, harder to debug, and quite likely actually slow it down.
You should also consider unpacking that data blob into additional columns and tables as appropriate in order to take advantage of the relational nature of the database.
How many rows do you expect the table to hold over time? Thousands? Millions? Billions? At what rate do you expect rows to be added?
Suggestion 1: As answered by Jonathan, do not split the tables. It won't help you increase the speed.
Suggestion 2: If you still want to split the tables. Use the logic in your PHP code. Check if the table for a particular use already exists or not. If it does, insert values in it and if it doesn't create a new one. Should be quite straight forward. If you want me to share code for this, let me know.
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I have reviewed some q&a but thought something specific to my subject would help me get off the fence.
I have an app that calculates pricing based on several different formulas and hundreds of different material types.
user A may use formula A and material A, B, C
user B uses formula A and material A, B, C, + they want to add a
material that no one else uses Material unique_A
when user A is on the app he doesn't want to see user B's unique material.
I was thinking of using a unique table of materials for each user so that it is "faster??? more efficient??? to grab the list of materials, instead of trying to set up some sort of off, on function that grabbed only the materials the user wants from one global table.
Which way is better? One table or a unique table for each user?
You can have a table of all materials.
materials = (id, name, other attributes...)
and a table of users:
myusers = (id, name, etc....)
then you can have a table that basically represents the many to many relationship between these two:
user_materials = (user_id, material_id)
You can then select the specific materials used by a user by joining these tables. Application wise, this arrangement is better than trying to create a table for each user. Queries will become difficult. This way you also have answer to the question: Which users are using material A?
Unless you have very few users, each with his own stable non changing items,
I don't see any sense in doing this.
Plus , most likely you will not get into performance issues
if you are talking about a domain of users and materials.
It's not like there are millions of either , right?
One "best practice" for databases is to reduce information duplicity. Actually variations of that exists for just about any field of theory there is.
It would mean however that your approach of a unique table per user would not be a good idea.
Not only would it duplicate data, but maintaining such a database would become a gigantic task as the number of users increases.
I would prefer to have a global table of materials, a table of users and a table over which user want's which materials.
The 'one-table-approach' can be considered better because it reduces complexity, both in database and in the code which should access the database, and duplication of information.
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I have a table that has 23 columns of data in it that I need to display. It's obviously unreasonably wide, and I am looking for a strategy to make it a little bit more manageable for my users.
That sounds like it would be better off just making the data available as CSV so that users can download it and read it in their favorite spreadsheet program. I know from experience that nothing made our users(1) happier (with one notable exception) than when we added this option in, and it's really quite easy to do. (Yeah, putting everything in a slick web interface is a nice goal, but sometimes you get better results by not working nearly so hard.)
(1) Our users are scientists. Physicists, in particular, but I'm told that biologists are the same. Your users might be different; check!
I think that 99% of times user is not interested in that many data at the same time, so try to split it somehow:
Try to show couple of main columns, and use jQuery and popups to show details for every row including other data from other columns.
Possibly not all users are interested in all columns. Show columns that are common to all users, and put an option above to show / hide additional columns
If none applies, then just show all 23 columns with horizontal splitter, no other option. If you really do this for some complex reporting purposes, perhaps provide ability to reorder columns so that users can put columns that they are interested in side to side or something.
However, I'm certain that your report can be splitted, either in many more specific reports targeting only parts of that data, or some other way...
What normally is done in databases (as you could see your table like one), is to split it up.
Especially if you have a lot of copied rows, like e.g. 10 columns are equal for all rows.
Example:
Table with customers having bought something.
The first 10 columns are for the customer's name, address, telephone etc.
If these 10 columns are equal for every customer then you can move it to a customer table and use an ID (or other unique column) to split it.
However, if all 23 columns do not have such repeating values than maybe the best thing you can do is create some kind of column selection or multiple tables with only certain columns shown.
E.g. Suppose you have a customer table with 23 information column about that customer, you can have one table with address information, one with company information etc.
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Assume PHP/MYSQL but I don't necessarily need actual code, I'm just interested in the theory behind it.
A good use-case would be Facebook's photo gallery page. You can drag and drop a photo on the page, which fires an Ajax event to save the new sort order. I'm implementing something very similar.
For example, I have a database table "photos" with about a million records:
photos
id : int,
userid : int,
albumid : int,
sortorder : int,
filename : varchar,
title : varchar
Let's say I have an album with 100 photos. I drag/drop a photo into a new location and the Ajax event fires off to save on the server.
Should I be passing the entire array of photo ids back to the server and updating every record? Assume input validation by "WHERE userid=loggedin_id", so malicious users can only mess with the sort order of their own photos
Should I be passing the photo id, its previous sortorder index and its new sortorder index, retrieve all records between these 2 indices, sort them, then update their orders?
What happens if there are thousands of photos in a single gallery and the sort order is changed?
What about just using an integer column which defines the order? By default you assign numbers * 1000, like 1000, 2000, 3000.... and if you move 3000 between 1000 and 2000 you change it to 1500. So in most cases you don't need to update the other numbers at all. I use this approach and it works well. You could also use double but then you don't have control about the precision and rounding errors, so rather don't use it.
So the algorithm would look like: say you move B to position after A. First perform select to see the order of the record next to A. If it is at least +2 higher than the order of A then you just set order of B to fit in between. But if it's just +1 higher (there is no space after A), you select the bordering records of B to see how much space is on this side, divide by 2 and then add this value to the order of all the records between A and B. That's it!
(Note that you should use transaction/locking for any algorithm which contains more than a single query, so this applies to this case too. The easiest way is to use InnoDB transaction.)
Store as a linked list, sortorder is a foreign key reference to the next photo_id in the set.
this would probably be a 'linked list' construct.
To me the second method of updating is the way to go (update only the range that changes). You are mentioning "What happens if there are thousands of photos in a single gallery ...", and to me that is never going to happen. Lets take your facebook example. Facebook doesn't show thousands of photos on one page, they split it up to about 10-20 per page.
The way I'd do this in a nonrelational database is to store a list of photo IDs on the 'album' entity/record, in the order desired. Reordering the photos results in reordering the list, and only a single database write.
Some SQL databases (Eg, PostgreSQL) have native list datatypes, but MySQL doesn't. You could serialize the list as a string or binary on MySQL.
3rd-normal-form trained database gurus will scream at you that this is a terrible approach, but RDBMSes are optimized for OLAP type queries, where query flexibility is more important than read performance. Webapps are best written with a 'write heavy, read light' strategy in mind, and this sort of denormalization is exactly in line with that.