I want to create a sqlite database with at least two tables: account and service. One account can have several services and one service can be used by several accounts.
I would like to be able to query all the services which one account uses.
Now, where it gets complicated for me is that I would like to avoid a third table which is usually used - as far as I know - to resolve this many-to-many relationship.
Is there an appropriate way to do this?
Thank you!
You can denormalize your schema and store relations in a field containing an array in each table. But this is going to be less efficient to query and not all database engines support array type. Actually sqlite3 doesn't. You can mitigate that by storing that as a JSON data type which will be then an array in JSON representation.
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Background: I have a relational db background and have never built anything for DynamoDB that wasn't just used for fast writes with very few reads. I am trying to learn DynamoDB patterns by migrating one of my help desk apps from MySQL to DynamoDB.
The application is a fairly simple one from a data storage perspective. A user submits a request and that request generates 1 or more tickets.
Setup: I have screens where people see initial requests and that request's tickets and search views that allow support to query on a bunch of attributes of a ticket (last name of user, status of ticket, use case of ticket, phone number of user, dept of user). This design in a SQL db is pretty straightforward but in Dynamo, I'm really being thrown for a loop on how to structure primary/sort keys and secondary indexes (if necessary).
I created one collection for requests and one collection for tickets. The individual requests have an array of ticket ids that belong to it. The ticket item has an attribute that stores the request id so that I can search that way. But what I am hung up on, is how do I incorporate searching on a ticket/request's attributes without having to do a full scan?
I read about composite keys and perhaps creating a composite sort key similar to: ## so that I can search on each of those fields directly without having to know the primary key (ticket id).
Question: How do you design dynamo collections/tables that require querying a lot of different attribute values without relying on a primary key?
This is typically something that DynamoDB is not good at, not to say it definitely cannot be done. The strength and speed for DynamoDB comes from having well known access patterns and designing your schema for these patterns. In general if you don't know what your users will search for, or there are many different possible queries, it's better to look at something like RDS or a native SQL DB. That being said a possible direction to solve this could be to create multiple lists for each of the fields and duplicate the data. This could all be done in the same table.
I have an ASP.NET data entry application that is used by multiple clients. The application consists of multiple data entry modules that are common to all clients.
I now have multiple clients that want their own custom module added which will typically consist of a dozen or so data points. Some values will be text, others numeric, some will be dropdown selections, etc.
I'm in need of suggestions for handling the data model for this. I have two thoughts on how to handle. First would be to create a new table for each new module for each client. This is pretty clean but I don't particular like it. My other thought is to have one table with columns for each custom data point for each client. This table would end up with a lot of columns and a lot of NULL values. I don't really like either solution and suspect there's a better way to do this, so any feedback you have will be appreciated.
I'm using SQL Server 2008.
As always with these questions, "it depends".
The dreaded key-value table.
This approach relies on a table which lists the fields and their values as individual records.
CustomFields(clientId int, fieldName sysname, fieldValue varbinary)
Benefits:
Infinitely flexible
Easy to implement
Easy to index
non existing values take no space
Disadvantage:
Showing a list of all records with complete field list is a very dirty query
The Microsoft way
The Microsoft way of this kind of problem is "sparse columns" (introduced in SQL 2008)
Benefits:
Blessed by the people who design SQL Server
records can be queried without having to apply fancy pivots
Fields without data don't take space on disk
Disadvantage:
Many technical restrictions
a new field requires DML
The xml tax
You can add an xml field to the table which will be used to store all the "extra" fields.
Benefits:
unlimited flexibility
can be indexed
storage efficient (when it fits in a page)
With some xpath gymnastics the fields can be included in a flat recordset.
schema can be enforced with schema collections
Disadvantages:
not clearly visible what's in the field
xquery support in SQL Server has gaps which makes getting your data a real nightmare sometimes
There are maybe more solutions, but to me these are the main contenders. Which one to choose:
key-value seems appropriate when the number of extra fields is limited. (say no more than 10-20 or so)
Sparse columns is more suitable for data with many properties which are filled out infrequent. Sounds more appropriate when you can have many extra fields
xml column is very flexible, but a pain to query. Appropriate for solutions that write rarely and query rarely. ie: don't run aggregates etc on the data stored in this field.
I'd suggest you go with the first option you described. I wouldn't over think it. The second option you outlined would be a bad idea in my opinion.
If there are fields common to all the modules you're adding to the system you should consider keeping those in a single table then have other tables with the fields specific to a particular module related back to the primary key in the common table. This is basically table inheritance (http://www.sqlteam.com/article/implementing-table-inheritance-in-sql-server) and will centralize the common module data and make it easier to query across modules.
The following questions are about the DB set up with aspnet_regsql.exe (for .NET 4):
Why is the username stored in aspnet_Users both in original form and in lowercase? Why not lowercase all the time?
Why are Users and UsersMembership two distinct tables? Is this just because we can have different membership/application or is some best practice?
Should data like "IsApproved" be stored in DB like a column? For me it seems like a temporary column that, once approved, could be removed. So why not store it a table with key/value pairs (something like "ExtendedpProperties). Similar for other columns like "Comment" or "LastLockoutDate".
What is the purpose of "LastUpdatedDate" in "aspnet_PersonalizationPerUser"?
Why are there two columns for Value in aspnet_Profile?
Is there something wrong in that DB? Do you think that it should have been designed in another way? Please provide arguments.
Thanks!
The idea of any calculated column is to save cycles on doing those calculations during querying. Most especially during large queries. The other thought is one which you had in indexing those columns. Again, this is done to save cycles.
The membership table holds information related to the MembershipProvider API interface. The users table stores usernames and user ids, which are referenced from many providers.
The aspnetdb system is very modular and each piece can be customized through the various providers. The tables need to be separated so each interface can be rewritten, redirected, etc.
Where do you want to store this information else?
Maybe you want to know when the user or the application last changed WebParts
PropertyNames holds a string value containing information about the profile property values present in the PropertyValuesString and PropertyValuesBinary fields. The string holds a colon-delimited list of items.
Looks like, you have been given an assignment , everything is there for a reason go through Asp.net Membership Documentation
I am planning to create a website using ASP.NET and SQL Server. However, my plan for the database design leaves me wondering if there is a better way.
The website will serve as a repository of information for various users. I figure I would have two databases, a Membership and Profile database.
The profile database would contain user data for all users, where each user may have ~20 tables. I would create the tables when the user account is created and generate a key used to name the tables. The tables are not directly related.
For Example a set of tables for two different users could look like:
User1 Tables - TransactionTable_Key1, AssetTable_Key1, ResearchTable_Key1 ....;
User2 Tables - TransactionTable_Key2, AssetTable_Key2, ResearchTable_Key2 ....;
The Key1, Key2 etc.. values would be retrieved based on the MembershipID data when the account was created. This could result in a very large number of tables over time. I'm not sure if this will limit scalability by setting up the database in this way. Any recommendations?
Edit: I should mention that some of these tables would contain 20k+ rows.
Realistically it sounds like you only really need one database for this.
From the way you worded your question, it sounds like you're trying to dynamically create tables for users as they create accounts. I wouldn't recommend this method.
What you want to do is create a master table that contains a primary key for each individual user. I'm assuming this is the Membership table. Then create the ~20 tables that you need for the profiles of these members. Every record, no matter the number of users that you have, will go into these tables. These 20 tables would need to have a foreign key pointing to the unique identifier of the Membership table.
When you want to query a Member for their user information, just select from the tables where the membership table's primary Id matches the foreign key in the profile tables.
This would result in only a few tables in the end and is easily maintainable and follows better database design.
Your ORM layer (EF, LINQ, DAL code) will hate having to deal with one set of tables per tenant. It is much better to have either one set of tables for all tenant in a single database, or a separate database per tenant. The later is only better if schema upgrade has to be vetted by tenant (like Salesforce.com has). If you can afford to upgrade all tenant to a new schema at once then there is no reason for database per tenant.
When you design a schema that hold multiple tenant the important things to remember are
don't use heaps, all tables must be clustered index
add the tenant ID as the leftmost key to every clustered
add the tenant ID as the leftmost key to every non-clustered index too
add the Left.tenantID = right.tenantID predicate to every join
add the table.TenantID = #currentTenantID to every query
These are fairly simple rules and if you obey them (with no exceptions) you will get a perfect partitioning per tenant of every query (no query will ever ever scan rows in a range of a different tenant) so you eliminate contention between tenants. To be more through, you can disable lock escalation to make sure no tenant escalates to block every other tenant.
This design also lends itself to table partitioning and to sharing the database for scale-out.
You definitely don't want to create a set of tables for each user, and you would want these only in one database. Even with SQL Server 2008's large capacity for tables (note really total objects in database), it would quickly become unmanageable. Your best bet is to use 20 tables, and separate them via a column into user areas. You might consider partitioning the tables by this user value, but that should be tested for performance reasons too.
Yes, since the tables only contain id, key, and value, why not make one single table?
Have the columns:
id, user ID, key, value
Put an Index on the user ID field.
A key idea behind a relational database is that the table structure does not change. You create a solid set of tables, and these are the "bones" of your application.
Cheers,
Daniel
Neal,
The solution really depends on your requirement. If security and data access are concern and you have only a handful of users, you can set up a different db for each user with access for him set to only his/her database.
Other wise, what Daniel Williams suggested is a good alternative where you have one DB and tables laid out with a indexed column partitioning the users data rows.
It's hard to tell from the summary, but it looks like you are designing for dynamic attribution by user. This design approach is called EAV (Entity-Attribute-Value) and consists of a simple base collection key (UserID, SiteID, ProductID...) and then rows consisting of name/value pairs. In a more complex version, categories are sometimes added as "super columns" to the tuple/row and provide sub-groupings for a set of name/value pairs.
Designing in this way moves responsibility for data type integrity, relational integrity and tuple integrity to the application layer.
The risk with doing this in a relational system involves the breaking of the tuple or row into a set of rows. Updates, deletes, missing values and the definition of a tuple are no longer easily accessible through human interaction. As your application evolves and the definition of a tuple changes, it becomes almost impossible to tell if a name/value pair is missing because it's part of an earlier-version tuple or because it was unintentionally deleted. Ad-hoc research as well becomes harder to manage as business analysts must keep an understanding of the virtual structure either in their heads or in documentation provided.
If you are looking to implement an EAV model, I would suggest you look at a non-relational solution (nosql) like MongoDB or CouchDB. These stores allow a developer to save and retrieve "documents" or json-formatted messages that are essentially made up of a collection of name/value pairs and can look very much like a serialized object. The advantage here is that you can store dynamic attribution without breaking your tuple. You always know that you have a complete tuple because you can store and retrieve it as a single "blob" of information that can be serialized and deserialized at-will. You can also update single attributes within the tuple, if that's a concern.
MongoDB also provides some database-like features such as multiple-attribute indexes, a query engine that is robust in comparison to other similar non-relational offerings and a sharding solution that is much less trouble than trying to do it with MySQL.
I hope this helps.
I have worked on a timesheet application application in MVC 2 for internal use in our company. Now other small companies have showed interest in the application. I hadn't considered this use of the application, but it got me interested in what it might imply.
I believe I could make it work for several clients by modifying the database (Sql Server accessed by Entity Framework model). But I have read some people advocating multiple databases (one for each client).
Intuitively, this feels like a good idea, since I wouldn't risk having the data of various clients mixed up in the same database (which shouldn't happen of course, but what if it did...). But how would a multiple database solution be implemented specifically?
I.e. with a single database I could just have a client register and all the data needed would be added by the application the same way it is now when there's just one client (my own company).
But with a multiple database solution, how would I create a new database programmatically when a user registers? Please note that I have done all database stuff using Linq to Sql, and I am not very familiar with regular SQL programming...
I would really appreciate a clear detailed explanation of how this could be done (as well as input on whether it is a good idea or if a single database would be better for some reason).
EDIT:
I have also seen discussions about the single database alternative, suggesting that you would then add ClientId to each table... But wouldn't that be hard to maintain in the code? I would have to add "where" conditions to a lot of linq queries I assume... And I assume having a ClientId on each table would mean that each table would have need to have a many to one relationship to the Client table? Wouldn't that be a very complex database structure?
As it is right now (without the Client table) I have the following tables (1 -> * designates one to many relationship):
Customer 1 -> * Project 1 -> * Task 1 -> * TimeSegment 1 -> * Employee
Also, Customer has a one to many relationship directly with TimeSegment, for convenience to simplify some queries.
This has worked very well so far. Wouldn't it be possible to simply have a Client table (or UserCompany or whatever one might call it) with a one to many relationship with Customer table? Wouldn't the data integrity be sufficient for the other tables since the rest is handled by the relationships?
as far as whether or not to use a single database or multiple databases, it really all depends on the use cases. more databases means more management needs, potentially more diskspace needs, etc. there are alot more things to consider here than just how to create the database, such as how will you automate the backup process creation, etc. i personally would use one database with a good authentication system that would filter the data to the appropriate client.
as to creating a database, check out this blog post. it describes how to use SMO (sql management objects) in c#.net to create a database. they are a really neat tool, and you'll definitely want to familiarize yourself with them.
to deal with the follow up question, yes, a single, top level relationship between clients and customers should be enough to limit the new customers to their appropriate data.
without any real knowledge about your application i can't say how complex adding that table will be, but assuming your data layer is up to snuff, i would assume you'd really only need to limit the customers class by the current client, and then get all the rest of your data based on the customers that are available.
did that make any sense?
See my answer here, it applies to your case as well: c# database architecture