I want to do a ranking. I have in my database many users and I want to do a ranking with them, but I don't know how to.
I need to get data from many tables in my database for some calculations. I already do this in a view. It will show the data and calculations, but I have a problem. Is it possible to sort the table columns?
This way, I'm sorting in the view rather than the database.
I'm searching, but I've only found references to sort tables within the database.
Sorry for my english, I'm learning.
Thanks
Related
I'm still very much a noob and I've been having quite a bit of trouble figuring out how to structure my DB for my Gym/Workout Log app.
The data is to be presented in TableViews with Rows/Sections.The idea is that the end user would first select a day of the week and will name his workout, and he could have multiple workouts under the same day of the week if he wishes. Then, within each workout, he could have multiple exercises, and within each exercise, he could have an array of Weights and Repetitions that need to maintain the order in which they are pushed in (might be some trouble there since I heard that arrays do not always maintain the same order when queried).
There are a few ways that I can go about structuring my DB, but I know that I have to avoid Sub-Collections because although sub-collections will structure my DB beautifully, they are a pain to work with when it comes to reading and performing cascading deletes. I've read that Maps are the way to go, but that's kind of what I''m having trouble with, especially in terms of reading the data. I'm going to post what I have come up with and I'm hoping that someone can suggest on how I can improve the model or what I can change so that I can access the String values of Days, Workouts, Exercises, and Weight/Repetitions as easily as possible, because the way I have it set out, those values are stored as Keys. Much appreciated!
You can nest up to 100 levels but doesn't mean you should. You can organize your data as a subcollection which is a collection within a specific document. You can query across subcollections with the same collection ID using Collection Group Queries. You can find best practices here
I am fairly new to data warehouses and I want to make sure my plan makes sense. I am using a star schema to capture insurance information for reporting purposes. The users want to see everything as-of a specific day, since ever field can change daily I am planning to have a record in the fact table join to a unique record in each dimension. I know that this will generate a lot of records but I am unable to think of another way to do it.
I appreciate any insight.
Hello and good morning.
I am working on a side project where I am adding an analytic board to an already existing app. The problem is that now the users table has over 400 columns. My question is that what's a better way of organizing this table such as splintering the table off into separate tables. How do you do that and how do you communicate the tables between the new tables?
Another concern is that If I separate the table will I still be able to save into it through the user model? I have code right now that says:
user.wallet += 100
user.save
If I separate wallet from user and link the two tables will I have to change this code. The reason I'm asking this is that there is a ton of code like this in the app.
Thank you so much if you can help me understanding how to organize a database. As a bonus if there is a book that talks about database organization can you recommend it to me (preferably one that is in rails).
Edit: Is there also a way to do all of this without loosing any data. For example transfer the data to a new column on the new table then destroying the old column.
Please read about:
Database Normalization
You'll get loads of hits when searching for that string and there are many books about database design covering that subject.
It is most likely, that this table of yours lacks normalization, but you have to see yourself!
Just to give an orientation - I would get a little anxious when dealing with a tenth of that number of columns. That saying, I clearly have to stress that there might be well normalized tables with 400 columns as well as sloppily created examples with just 10 columns.
Generally speaking, the probability of dealing with bad designed tables and hence facing trouble simply rises with the number of columns.
So take your time and if you find out, that users table needs normalization next step would indeed be to spread data over several tables. Because that clearly (and most likely even heavily) affects the coding of your application here is where you thoroughly have to balance pros and cons - simply impossible to judge that from far away.
Say, you have substantial problems (e.g. fierce performance problems - you wouldn't post it) that could be eased by normalization there are different approaches of how to split data. Here please read about:
Cardinalities
Usually the new tables are linked by
Foreign Keys
, identical data (like a user id) that appear in multiple tables and that are used to join them, that is.
And finally, yes, you can do that without losing data as the overall amount of information never changes when normalizing.
In case your last question was meant to be technical: There is no problem in reading data from one column and inserting them into a new one (of a new table). That has to happen in a certain order as foreign keys have to be filled before you can use them. See
Referential Integrity
However, quite obvious: Deleting data and dropping columns interferes with the operability of your application. Good planning is due.
I'm working on financial data mart structure.
And I'm having some doubts on whats the better approach to do so.
The source system database,Dynamics AX 2009, has three tables for customer transaction.
One table for open transactions, where the Customer still needs to pay for service/product;
One table for settle transactions, where it holds what the customer have already paid;
Finally a table that have all customers transactions, holds transactions from open to settle and also others transactions as customer to bank or ledger accounts.
I thought in two options, first I will maintain a fact table representing the three table, fact for open transactions, fact for any customer transaction and fact for settle transaction.
Second is to create a single fact to hold all transactions, to do so I would have to do a full join on three tables.
I'm not sure on both approaches, as the first seems to copy tables from production and create the proper dimension.
On the Second one I would create a massive fact table, that where data would constantly change, as open transaction are delete on source system when they are settle.
Another doubt, should i create a fact with scd(slowly changing dimension) structure to maintain history data?(star date, end date , flag)
It's hard to say from the information given whether this needs to be one or more Fact tables. However, the key point which you should use to decide is whether all of the information is at the same granularity. Consider the grain of your intended Fact table(s) and you should find an answer for whether you need one table or multiple tables.
If all of the information sits at the same grain - i.e. all of the same dimensions apply to all of the measures you are considering putting into the same Fact table - then they can probably all live in the same Fact table. If you're finding that some of the Dimensions wouldn't apply to some of the measures then you probably need to re-think your design. Either you might need multiple Fact tables, or you might need to take all of your measures down to the lowest grain and combine hierarchies into single Dimensions if you currently have them split across multiple Dimensions.
While it's been mentioned that having measures in separate cubes could make it difficult to compare things, keep in mind that you don't need one cube per Fact table. You can have multiple Fact tables in a single cube, and sometimes this is very helpful when you need to be able to compare measures which share some Dimensions but not others. This is far, far better than forcing data which does not have the same grain into one Fact table.
Also, it sounds like what you're trying to model is the sales ledger of an organisation. I'd suggest having a dig around via Google as you may well be able to find materials discussing dimensional data warehouse design for sales ledger structures, rather than reinventing the wheel. If you don't have a decent understanding of the accounting concepts you're trying to model I would especially recommend looking for a reference schema to work from, or failing that doing some reading up on accountancy concepts (and sales ledgers specifically). Understanding the account structure should help you understand what the grain of your Fact table(s) needs to be, how to model the Dimensions, and so on.
This is a really helpful abridged version of Kimball's modelling techniques which discusses grain, and the different types of Fact table, amongst many other topics:
http://www.kimballgroup.com/wp-content/uploads/2013/08/2013.09-Kimball-Dimensional-Modeling-Techniques11.pdf
I think you should just use one fact table (one cube) and use a dimension to differentiate between open/settled/etc. transactions. That's what dimensions are for: They help you to categorize your measures and get a specific view on them. This approach will also open much more possibilities to create knowledge with your cube. With separate cubes for open/settled/etc. transactions, it will be harder or not possible to set this data into contrast.
Since the data is changing constantly, you should consider to update your fact table in a given time and rebuild your cube if it needs to.
If you use scd or not really depends on the data you process and what it is used for. Is there a business case claiming it? Is there a technical use?
I think this is something you have to decide on your own.
I'm building an application where I will be gathering statistics from a game. Essentially, I will be parsing logs where each line is a game event. There are around 50 different kinds of events, but a lot of them are related. Each event has a specific set of values associated with it, and related events share a lot of these attributes. Overall there are around 50 attributes, but any given event only has around 5-10 attributes.
I would like to use Rails for the backend. Most of the queries will be event type related, meaning that I don't especially care about how two event types relate with each other in any given round, as much as I care about data from a single event type across many rounds. What kind of schema should I be building and what kind of database should I be using?
Given a relational database, I have thought of the following:
Have a flat structure, where there are only a couple of tables, but the events table has as many columns as there are overall event attributes. This would result in a lot of nulls in every row, but it would let me easily access what I need.
Have a table for each event type, among other things. This would let me save space and improve performance, but it seems excessive to have that many tables given that events aren't really seperate 'ideas'.
Group related events together, minimizing both the numbers of tables and number of attributes per table. The problem then becomes the grouping. It is far from clear cut, and it could take a long time to properly establish event supertypes. Also, it doesn't completely solve the problem of there being a fair amount of nils.
It was also suggested that I look into using a NoSQL database, such as MongoDB. It seems very applicable in this case, but I've never used a non-relational database before. It seems like I would still need a lot of different models, even though I wouldn't have tables for each one.
Any ideas?
This feels like a great use case for MongoDB and a very awkward fit for a relational database.
The types of queries you would be making against this data is very key to best schema design but imagine that your documents (in a single collection similar to 1. above) look something like this:
{ "round" : 1,
"eventType": "et1",
"attributeName": "attributeValue",
...
}
You can easily query by round, by eventType, getting back all attributes or just a specified subset, etc.
You don't have to know up front how many attributes you might have, which ones belong with which event types, or even how many event types you have. As you build your prototype/application you will be able to evolve your model as needed.
There is a very large active community of Rails/MongoDB folks and there's a good chance that you can find a lot of developers you can ask questions and a lot of code you can look at as examples.
I would encourage you to try it out, and see if it feels like a good fit. I was going to add some links to help you get started but there are too many of them to choose from!
Since you might have a question about whether to use an object mapper or not so here's a good answer to that.
A good write-up of dealing with dynamic attributes with Ruby and MongoDB is here.