Databases
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    <p>You can use an ORM to map the command inheritance to database. For example you can use "Table per Hierarchy" technique provided by the ORMs (eg: Entity Framework, nHibernate, etc). ORM will instantiate the correct subclass when you retrieve them.</p> <p>Here's an example of doing it in Entity Framework Code first</p> <pre><code>abstract class Command : ICommand { public int Id {get;set;} public abstract void Execute(); } class CommandA : Command { public int X {get;set;} public int Y {get;set;} public override void Execute () { ... } } class CommandB : Command { public string Name {get;set;} public override void Execute () { ... } } </code></pre> <p>Refere <a href="http://blogs.msdn.com/b/adonet/archive/2011/03/15/ef-4-1-code-first-walkthrough.aspx" rel="noreferrer">EF 4.1 Code First Walkthrough</a> to configure this model with EF.</p> <p>If your commands takes drastically different set of parameter you can consider using "Table per Type" inheritance modeling. Here you will have pay some significant performance penalty because of lot of Unions and table joins involved in this.</p> <p>Alternative approach would be to store the Command parameters as a XML configuration where you (de)serialize manually. This way you can keep all your commands in a single table without sacrificing performance. Again this has a drawback where you can not filter using the command parameters.</p> <p>Each approach has its Pros and Cons. You can choose the strategy which suits your requirements.</p>
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    1. POStore objects with common base class in database
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    1. COSounds interesting. Does it work in practice? Does it scale? Is the data still queryable manually?
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    2. CO@aero inheritance mapping is common but if you have to deal with 1000s of commands at once, then ORMs will take considerable time
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    3. COPerformance-wise, it's worth to create a sample database with lots of data in it that will resemble the actual production database as close as possible, and then run all suggested test cases against it using several approaches including your current implementation. It may happen that the common table with custom arguments accessed directly with Dapper is actually faster than any of the suggested ORMs.
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