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Archive for the ‘Data Access’ Category



Object Relational Mapping Sucks!

Wednesday, June 25th, 2008

For reporting, that is.image

And doesn’t handle concurrency!

Unless you don’t expose setters.

I guess it depends, doesn’t it?

Well, that was Ted’s assertion in his recent Pragmatic Architecture column on data access.

But, “it depends” doesn’t get the system built, does it?

So, here are some rules for using o/r mapping that will get you 99% of the way there.

Yes, you heard me.

Rules.

They do not depend.

If you’re doing something significantly bigger than enterprise-scale development, and you are already doing this, and it isn’t enough, give me a call. Here we go.

  1. No reporting.

    I mean it. Don’t report off of live data.
    This isn’t just a o/r mapping thing.
    Users can tolerate some, if not quite a lot of latency.

    And it’s not like objects are even used. It’s just rolled up data. Not a single behaviour for miles.

  2. Don’t expose setters

    You want multiple users sharing and collaborating on data, right? Then don’t force them to either overwrite each others data, or throw away their own. There is one simple way to avoid that: Get an object, call a method. Once the object has the most up to date data, pass all the client data in via a method call. The object will decide if its valid, from a business perspective as well, and then update the appropriate fields.

    Now your DBAs can vertically partition tables accordingly, and improve throughput. After that, you can increase the isolation level, to improve safety, without hurting throughput.

    This will also keep your logic encapsulated, bringing you closer to a true Domain Model.

    If your O/R mapping tool requires you to have setters on your domain classes, hide those from your service layer behind an interface.

  3. Grids are like reports.

    No o/r mapping required there either. While you probably won’t be showing grids of yesterday’s data to users in an interactive environment, it’s still just data – no behaviour.

    However, users should NOT update data in those grids. This gets back to rule 2. Have users select a specific task they want to perform, pop open a window, and have them do it there. Change customer address. Discount order. You get the picture. That way you’ll know what method to call on those objects you designed in rule 2.

Before wrapping up, one small thing.

You can use an O/R mapping tool to do reporting, just, for the love of Bill, don’t use the same classes you designed for your OLTP domain model. But, just because you can, doesn’t necessarily mean you should. Datasets datatables are probably just as viable a solution.



How to create fully encapsulated Domain Models

Friday, February 29th, 2008

image Update: The new and improved solution is now available: Domain Events, Take 2.

Most people getting started with DDD and the Domain Model pattern get stuck on this. For a while I tried answering this on the discussion groups, but here we have a nice example that I can point to next time.

The underlying problem I’ve noticed over the past few years is that developers are still thinking in terms of querying when they need more data. When moving to the Domain Model pattern, you have to “simply” represent the domain concepts in code – in other words, see things you aren’t used to seeing. I’ll highlight that part in the question below so that you can see where I’m going to go with this in my answer:

I have an instance where I believe I need access to a service or repository from my entity to evaluate a business rule but I’m using NHibernate for persistence so I don’t have a real good way to inject services into my entity. Can I get some viewpoints on just passing the services to my entity vs. using a facade?

Let me explain my problem to provide more context to the problem.

The core domain revolves around renting video games. I am working on a new feature to allow customers to trade in old video games. Customers can trade in multiple games at a time so we have a TradeInCart entity that works similar to most shopping carts that everybody is familiar with. However there are several rules that limit the items that can be placed into the TradeInCart. The core rules are:

1. Only 3 games of the same title can be added to the cart.
2. The total number of items in the cart cannot exceed 10.
3. No games can be added to the cart that the customer had previously reported lost with regards to their rental membership.
    a. If an attempt is made to add a previously reported lost game, then we need to log a BadQueueStatusAddAttempt to the persistence store.

So the first 2 rules are easily handled internally by the cart through an Add operation. Sample cart interface is below.

   1:  class TradeInCart{
   2:      Account Account{get;}
   3:      LineItem Add(Game game);
   4:      ValidationResult CanAdd(Game game);
   5:      IList<LineItems> LineItems{get;}
   6:  }

However the #3 rule is much more complicated and can’t be handled internally by the cart, so I have to depend on external services. Splitting up the validation logic for a cart add operation doesn’t seem very appealing to me at all. So I have the option of passing in a repository to get the previously reported lost games and a service to log bad attempts. This makes my cart interface ugly real quick.

   1:  class TradeInCart{
   2:      Account Account{get;}
   3:      LineItem Add(
   4:          Game game, 
   5:          IRepository<QueueHistory> repository, 
   6:          LoggingService service);
   7:   
   8:      ValidationResult CanAdd(
   9:          Game game, 
  10:          IRepository<QueueHistory> repository, 
  11:          LoggingService service);
  12:   
  13:      IList<LineItems> LineItems{get;}
  14:  }

The alternative option is to have a TradeInCartFacade that handles the validations and adding the items to the cart. The façade can have the repository and services injected though DI which is nice, but the big negative is that the cart ends up totally anemic.

Any thought on this would be greatly appreciated.

Thanks,
Jesse

As I highlighted above, the thing that will help you with your business rules is to introduce the Customer object (that you probably already have) with the property GamesReportedLost (an IList<Game>). Your TradeInCart would have a reference to the Customer object and could then check the rule in the Add method.

Before I go into the code, it looks like your Account object might be used the same way, but your description of the domain doesn’t mention accounts, so I’m going to assume that that’s unrelated for now:

   1:  public class Customer{
   2:   
   3:      /* other properties and methods */
   4:   
   5:      private IList<Game> gamesReportedLost;
   6:      public virtual IList<Game> GamesReportedLost 
   7:      { 
   8:          get
   9:          {
  10:              return gamesReportedLost;
  11:          }
  12:          set
  13:          {
  14:              gamesReportedLost = value;
  15:          }
  16:      }
  17:  }

Keep in mind that the GamesReportedLost is a persistent property of Customer. Every time a customer reports a game lost, this list needs to be kept up to date. Here’s the TradeInCart now:

   1:  public class TradeInCart
   2:  {
   3:      /* other properties and methods */
   4:   
   5:      private Customer customer;
   6:      public virtual Customer Customer
   7:      { 
   8:          get { return customer; }
   9:          set { customer = value; }
  10:      }
  11:   
  12:      private IList<LineItem> lineItems;
  13:      public virtual IList<LineItem> LineItems
  14:      {
  15:          get { return lineItems; }
  16:          set { lineItems = value; }
  17:      }
  18:   
  19:      public void Add(Game game)
  20:      {
  21:          if (lineItems.Count >= CONSTANTS.MaxItemsPerCart)
  22:          {
  23:              FailureEvents.RaiseCartIsFullEvent();
  24:              return;
  25:          }
  26:   
  27:          if (NumberOfGameAlreadyInCart(game) >=
  28:              CONSTANTS.MaxNumberOfSameGamePerCart)
  29:          {
  30:              FailureEvents
  31:                .RaiseMaxNumberOfSameGamePerCartReachedEvent();
  32:              return;
  33:          }
  34:   
  35:          if (customer.GamesReportedLost.Contains(game))
  36:              FailureEvents.RaiseGameReportedLostEvent();
  37:          else
  38:              this.lineItems.Add(new LineItem(game));
  39:      }
  40:   
  41:      private int NumberOfGameAlreadyInCart(Game game)
  42:      {
  43:          int result = 0;
  44:   
  45:          foreach(LineItem li in this.lineItems)
  46:              if (li.Game == game)
  47:                  result++;
  48:   
  49:          return result;
  50:      }
  51:  }
  52:   
  53:  public static class FailureEvents
  54:  {
  55:      public static event EventHandler GameReportedLost;
  56:      public static void RaiseGameReportedLostEvent()
  57:      {
  58:           if (GameReportedLost != null)
  59:               GameReportedLost(null, null);
  60:      }
  61:   
  62:      public static event EventHandler CartIsFull;
  63:      public static void RaiseCartIsFullEvent()
  64:      {
  65:           if (CartIsFull != null)
  66:               CartIsFull(null, null);
  67:      }
  68:   
  69:      public static event EventHandler MaxNumberOfSameGamePerCartReached;
  70:      public static void RaiseMaxNumberOfSameGamePerCartReachedEvent()
  71:      {
  72:           if (MaxNumberOfSameGamePerCartReached != null)
  73:               MaxNumberOfSameGamePerCartReached(null, null);
  74:      }
  75:  }

image Your service layer class that calls the Add method of TradeInCart would first subscribe to the relevant events in FailureEvents. If one of those events is raised, it would do the necessary logging, external system calls, etc.

As you can see, the API of TradeInCart doesn’t need to make use of any external repositories, nor do you need to inject any other external dependencies in.

One thing I didn’t do in the above code to keep it “short” is to define the relevant custom EventArgs for bubbling up the information as to which game was reported lost or already have 3 of those in the cart. That is something that definitely should be done so that the service layer can pass this information back to the client.

Here’s a look at Service Layer code:

   1:  public class AddGameToCartMessageHandler :
   2:      BaseMessageHandler<AddGameToCartMessage>
   3:  {
   4:      public override void Handle(AddGameToCartMessage m)
   5:      {
   6:          using (ISession session = SessionFactory.OpenSession())
   7:          using (ITransaction tx = session.BeginTransaction())
   8:          {
   9:              TradeInCart cart = session.Get<TradeInCart>(m.CartId);
  10:              Game g = session.Get<Game>(m.GameId);
  11:   
  12:              Domain.FailureEvents.GameReportedLost +=
  13:                gameReportedLost;
  14:              Domain.FailureEvents.CartIsFull +=
  15:                cartIsFull;
  16:              Domain.FailureEvents.MaxNumberOfSameGamePerCartReached +=
  17:                maxNumberOfSameGamePerCartReached;
  18:   
  19:              cart.Add(g);
  20:   
  21:              Domain.FailureEvents.GameReportedLost -=
  22:                gameReportedLost;
  23:              Domain.FailureEvents.CartIsFull -=
  24:                cartIsFull;
  25:              Domain.FailureEvents.MaxNumberOfSameGamePerCartReached -=
  26:                maxNumberOfSameGamePerCartReached;
  27:   
  28:              tx.Commit();
  29:          }
  30:      }
  31:   
  32:      private EventHandler gameReportedLost = delegate { 
  33:            Bus.Return((int)ErrorCodes.GameReportedLost);
  34:          };
  35:   
  36:      private EventHandler cartIsFull = delegate { 
  37:            Bus.Return((int)ErrorCodes.CartIsFull);
  38:          };
  39:   
  40:      private EventHandler maxNumberOfSameGamePerCartReached = delegate { 
  41:            Bus.Return((int)ErrorCodes.MaxNumberOfSameGamePerCartReached);
  42:          };
  43:      }
  44:  }

It’s important to remember to clean up your event subscriptions so that your Service Layer objects get garbage collected. This is one of the primary causes of memory leaks when using static events in your Domain Model. I’m hoping to find ways to use lambdas to decrease this repetitive coding pattern. You might be thinking to yourself that non-static events on your Domain Model objects would be easier, since those objects would get collected, freeing up the service layer objects for collection as well. There’s just on small problem:

The problem is that if an event is raised by a child (or grandchild object), the service layer object may not even know that that grandchild was involved and, as such, would not have subscribed to that event. The only way the service layer could work was by knowing how the Domain Model worked internally – in essence, breaking encapsulation.

If you’re thinking that using exceptions would be better, you’d be right in thinking that that won’t break encapsulation, and that you wouldn’t need all that subscribe/unsubscribe code in the service layer. The only problem is that the Domain Model needs to know that the service layer had a default catch clause so that it wouldn’t blow up. Otherwise, the service layer (or WCF, or nServiceBus) may end up flagging that message as a poison message (Read more about poison messages). You’d also have to be extremely careful about in which environments you used your Domain Model – in other words, your reuse is shot.

Conclusion

I never said it would be easy 🙂

However, the solution is simple (not complex). The same patterns occur over and over. The design is consistent. By focusing on the dependencies we now have a domain model that is reusable across many environments (server, client, sql clr, silverlight). The domain model is also testable without resorting to any fancy mock objects.

One closing comment – while I do my best to write code that is consistent with production quality environments, this code is more about demonstrating design principles. As such, I focus more on the self-documenting aspects of the code and have elided many production concerns.

Do you have a better solution?

Something that I haven’t considered?

Do me a favour – leave me a comment. Tell me what you think.



From CRUD to Domain-Driven Fluency

Friday, February 15th, 2008

I got a question about how to stay away from CRUD based service interfaces when the logic itself is like that, and I’ve found that this shift in thinking really needs more examples, so I’ve decided to put this out there:

For instance, in an HR system, the process of interviewing candidates – wouldn’t you just insert, update, and delete these Appointment objects?

If I were to put on my domain-driven hat, I would describe those requirements differently – interview appointments have a lifecycle: proposed, accepted, cancelled, etc. It seems that only a user of the role HR Interviewer should be able to make appointments for themselves, so the service layer code would probably look something like this:

using (ISession session = SessionFactory.OpenSession())
using (ITransaction tx = session.BeginTransaction())
{
    ICandidateInterviewer interviewer = session.Get<ICandidateInterviewer>(message.InterviewerId);
    ICandidate candidate = session.Get<ICandidate>(message.CandidateId);

    interviewer.ScheduleInterviewWith(candidate).At(message.RequestedTime);  
    tx.Commit();
}  

The “ScheduleInterviewWith” method accepts an ICandidate and returns an IAppointment. IAppointment has a method “At” which accepts a DateTime parameter and returns void – just changes the data of the appointment. The state of the appointment at creation time would probably be proposed. The appointment object would probably be added to the list of appointments for that interviewer – that’s what will cause it to be persisted automatically.

Later, when the candidate accepts the meeting, we could have the following method on ICandidate – void Accept(IAppointment); that would obviously check that the candidate is the right person for that interview, the appointment’s current state (not cancelled), etc – finally updating its state. What part of this looks like create, update, delete? If that’s what your service layer to domain interaction looks like, do you now know what your messages will be looking like?CRUD seems to be what most of us are familiar with. Moving to domain-driven thinking takes time and practice, but is well worth it. Contrast this with a more traditional O/R mapping solution:

using (ISession session = SessionFactory.OpenSession())
using (ITransaction tx = session.BeginTransaction())
{
    ICandidateInterviewer interviewer = session.Get<ICandidateInterviewer>(message.InterviewerId);
    ICandidate candidate = session.Get<ICandidate>(message.CandidateId); 

    Appointment a = new Appointment(); 

    a.Interviewer = interviewer; 
    interviewer.Appointments.Add(a); 

    a.Candidate = candidate;
    candidate.Appointments.Add(a); 

    a.Time = message.RequestedTime; 

    session.Save(a);  

    tx.Commit(); 
} 

As you can see, we’ve got simpler, more expressive, and more testable code when employing the domain model pattern, than using “just” O/R mapping. I’m not saying that the domain model pattern doesn’t need O/R mapping in the background for it to work. But that’s just it – the persistence gunk needs to be in the background and the business logic needs to be encapsulated.

So, while I’ll agree with Dave that the Domain Model is more lifestyle than pattern, I would argue against these conclusions:

If this post had a point, it’s only to share the idea that Domain Model is a big, big thing. It’s probably overkill in a lot of cases where you have simple applications that have very simple purposes.

As you just saw in the example above, there is no “overkill” to be seen. The domain model in the example wasn’t “a big, big thing”.

The domain model. Use it.

Why not have a better lifestyle?   ;-)



Handling messages out of order

Saturday, December 15th, 2007

I wanted to follow up on my recent post, “In order messaging a myth?” by showing the exact code that solves the issue. I have a podcast waiting to come online that deals with the specifics, so keep your eye out for that too.

The important thing to note is that if we just automatically return the message to the queue, we may get “stuck” with that message if the first PolicyCreatedMessage never arrived. This opens us up to a Denial-of-Service attack by quite simply flooding us with a bunch of messages that never get cleaned up.

Anyway, the general idea is to first try the regular happy path, and only if we see that prerequisite data isn’t available, do we see if another thread may be working on that data. This is done by decreasing the isolation level of our transaction from the regular ReadCommitted to ReadUncommitted. This will enable our thread to see if some other thread inserted the policy in to the Policies table but hasn’t committed its transaction yet.

    public class PolicyApprovedMessageHandler : BaseDBMessageHandler<PolicyApprovedMessage>

    {

        public override void Handle(PolicyApprovedMessage message)

        {

            bool policyExists = true;

 

            using (ISession s = OpenSession())

            using (ITransaction tx = s.BeginTransaction(IsolationLevel.ReadCommitted))

            {

                Policy p = s.Get<Policy>(message.PolicyId);

 

                if (p != null)

                {

                    p.Approve();

                    tx.Commit();

                }

                else

                    policyExists = false;

            }

 

            if (!policyExists) // check to make sure

                using (ISession s = OpenSession())

                using (ITransaction tx = s.BeginTransaction(IsolationLevel.ReadUncommitted))

                {

                    Policy p = s.Get<Policy>(message.PolicyId);

 

                    if (p != null) // another thread hasn’t committed its tx yet, so try message again later

                        this.bus.HandleCurrentMessageLater();

                    else

                        this.bus.Return((int)ErrorCodes.PolicyNotFound);

                }

        }

    }

The next step will be how we take this code and make it generic, so that we don’t have write the same code over and over again for the different kinds of message handlers we have.

But that will have to wait until the next installment 🙂



TechEd Persistent Domain Models Video now Online

Thursday, November 15th, 2007

You can now find my talk from TechEd – ARC401 Designing High Performance, Persistent Domain Models – online. You have to log in to the TechEd site first, otherwise the DRM will block the video.

Enjoy.

Watch in Media Player



Asynchronous, High-Performance Login for Web Farms

Saturday, November 10th, 2007

Often during my consulting engagements I run into people who say, "some things just can’t be made asynchronous" even after they agree about the inherent scalability that asynchronous communications pattern bring. One often-cited example is user authentication – taking a username and password combo and authenticating it against some back-end store. For the purpose of this post, I’m going to assume a database. Also, I’m not going to be showing more advanced features like ETags to further improve the solution.

The Setup

Just so that the example is in itself secure, we’ll assume that the password is one-way hashed before being stored. Also, given a reasonable network infrastructure our web servers will be isolated in the DMZ and will have to access some application server which, in turn, will communicate with the DB. There’s also a good chance for something like round-robin load-balancing between web servers, especially for things like user login.

Before diving into the meat of it, I wanted to preface with a few words. One of the commonalities I’ve found when people dismiss asynchrony is that they don’t consider a real deployment environment, or scaling up a solution to multiple servers, farms, or datacenters.

The Synchronous Solution

In the synchronous solution, each one of our web servers will be contacting the app server for each user login request. In other words, the load on the app server and, consequently, on the database server will be proportional to the number of logins. One property of this load is its data locality, or rather, the lack of it. Given that user U logged in, the DB won’t necessarily gain any performance benefits by loading all username/password data into memory for the same page as user U. Another property is that this data is very non-volatile – it doesn’t change that often.

I won’t go to far into the synchronous solution since its been analysed numerous times before. The bottom line is that the database is the bottleneck. You could use sharding solutions. Many of the large sites have numerous read-only databases for this kind of data, with one master for updates – replicating out to the read-only replicas. That’s great if you’re using a nice cheap database like mySql (of LAMP), not so nice if you’re running Oracle or MS Sql Server.

Regardless of what you’re doing in your data tier, you’re there. Wouldn’t it be nice to close the loop in the web servers? Even if you are using Apache, that’s going to be less iron, electricity, and cooling all around. That’s what the asynchronous solution is all about – capitalizing on the low cost of memory to save on other things.

The Asynchronous Solution

In the asynchronous solution, we cache username/hashed-password pairs in memory on our web servers, and authenticate against that. Let’s analyse how much memory that takes:

Usernames are usually 12 characters or less, but let’s take an average of 32 to be sure. Using Unicode we get to 64 bytes for the username. Hashed passwords can run between 256 and 512 bits depending on the algorithm, divide by 8 and you have 64 bytes. That’s about 128 bytes altogether. So we can safely cache 8 million of these with 1GB of memory per web server. If you’ve got a million users, first of all, good for you 🙂 Second, that’s just 128 MB of memory – relatively nothing even for a cheap 2GB web server.

Also, consider the fact that when registering a new user we can check if such a username is already taken at the web server level. That doesn’t mean it won’t be checked again in the DB to account for concurrency issues, but that the load on the DB is further reduced. Other things to notice include no read-only replicas and no replication. Simple. Our web servers are the "replicas".

The Authentication Service

What makes it all work is the "Authentication Service" on the app server. This was always there in the synchronous solution. It is what used to field all the login requests from the web servers, and, of course, allowed them to register new users and all the regular stuff. The difference is that now it publishes a message when a new user is registered (or rather, is validated – all a part of the internal long-running workflow). It also allows subscribers to receive the list of all username/hashed-password pairs. It’s also quite likely that it would keep the same data in memory too.

The same message can be used to publish both single updates, and returning the full list when using NServiceBus. Let’s define the message:

[Serializable]
public class UsernameInUseMessage : IMessage
{
    private string username;
    public string Username
    {
        get { return username; }
        set { username = value; }
    }

    private byte[] hashedPassword;
    public byte[] HashedPassword
    {
        get { return hashedPassword; }
        set { hashedPassword = value; }
    }
}

And the message that the web server sends when it wants the full list:

[Serializable]
public class GetAllUsernamesMessage : IMessage
{

}

And the code that the web server runs on startup looks like this (assuming constructor injection):

 

public class UserAuthenticationServiceAgent

    public UserAuthenticationServiceAgent(IBus bus) 
    { 
        this.bus = bus;
        bus.Subscribe(typeof(UsernameInUseMessage)); 
        bus.Send(new GetAllUsernamesMessages());
    }

}

And the code that runs in the Authentication Service when the GetAllUsernamesMessage is received:

 

public class GetAllUsernamesMessageHandler : BaseMessageHandler<GetAllUsernamesMessage>
{
    public override void Handle(GetAllUsernamesMessage message)
    {
        this.Bus.Reply(Cache.GetAll<UsernameInUseMessage>());
    }
}

 

And the class on the web server that handles a UsernameInUseMessage when it arrives:

 

public class UsernameInUseMessageHandler : BaseMessageHandler<UsernameInUseMessage>
{
    public override void Handle(UsernameInUseMessage message)
    { 
        WebCache.SaveOrUpdate(message.Username, message.HashedPassword); 
    }
}

When the app server sends the full list, multiple objects of the type UsernameInUseMessage are sent in one physical message to that web server. However, the bus object that runs on the web server dispatches each of these logical messages one at a time to the message handler above.

So, when it comes time to actually authenticate a user, this the web page (or controller, if you’re doing MVC) would call:

public class UserAuthenticationServiceAgent
{
    public bool Authenticate(string username, string password)
    {
        byte[] existingHashedPassword = WebCache[username];
        if (existingHashedPassword != null)
            return existingHashedPassword == this.Hash(password);

        return false;
    }
}

 

When registering a new user, the web server would of course first check its cache, and then send a RegisterUserMessage that contained the username and the hashed password.

[Serializable]
[StartsWorkflow]
public class RegisterUserMessage : IMessage
{
    private string username;
    public string Username
    {
        get { return username; }
        set { username = value; }
    }

    private string email;
    public string Email
    {
        get { return email; }
        set { email = value; }
    }

    private byte[] hashedPassword;
    public byte[] HashedPassword
    {
        get { return hashedPassword; }
        set { hashedPassword = value; }
    }
}

 

When the RegisterUserMessage arrives at the app server, a new long-running workflow is kicked off to handle the process:

public class RegisterUserWorkflow :
    BaseWorkflow<RegisterUserMessage>, IMessageHandler<UserValidatedMessage>
{
    public void Handle(RegisterUserMessage message)
    {
        //send validation request to message.Email containing this.Id (a guid)
        // as a part of the URL
    }

    /// <summary>
    /// When a user clicks the validation link in the email, the web server
    /// sends this message (containing the workflow Id)
    /// </summary>
    /// <param name="message"></param>
    public void Handle(UserValidatedMessage message)
    {
        // write user to the DB

        this.Bus.Publish(new UsernameInUseMessage(
            message.Username, message.HashedPassword));
    }
}

That UsernameInUseMessage would eventually arrive at all the web servers subscribed.

Performance/Security Trade-Offs

When looking deeper into this workflow we realize that it could be implemented as two separate message handlers, and have the email address take the place of the workflow Id. The problem with this alternate, better performing solution has to do with security. By removing the dependence on the workflow Id, we’ve in essence stated that we’re willing to receive a UserValidatedMessage without having previously received the RegisterUserMessage.

Since the processing of the UserValidatedMessage is relatively expensive – writing to the DB and publishing messages to all web servers, a malicious user could perform a denial of service (DOS) attack without that many messages, thus flying under the radar of many detection systems. Spoofing a guid that would result in a valid workflow instance is much more difficult. Also, since workflow instances would probably be stored in some in-memory, replicated data grid the relative cost of a lookup would be quite small – small enough to avoid a DOS until a detection system picked it up.

Improved Bandwidth & Latency

The bottom line is that you’re getting much more out of your web tier this way, rather than hammering your data tier and having to scale it out much sooner. Also, notice that there is much less network traffic this way. Not such a big deal for usernames and passwords, but other scenarios built in the same way may need more data. Of course, the time it takes us to log a user in is much shorter as well since we don’t have to cross back and forth from the web server (in the DMZ) to the app server, to the db server.

The important thing to remember in this solution is doing pub/sub. NServiceBus merely provides a simple API for designing the system around pub/sub. And publishing is where you get the serious scalability. As you get more users, you’ll obviously need to get more web servers. The thing is that you probably won’t need more database servers just to handle logins. In this case, you also get lower latency per request since all work needed to be done can be done locally on the server that received the request.

ETags make it even better

For the more advanced crowd, I’ll wrap it up with the ETags. Since web servers do go down, and the cache will be cleared, what we can do is to write that cache to disk (probably in a background thread), and "tag" it with something that the server gave us along with the last UsernameInUseMessage we received. That way, when the web server comes back up, it can send that ETag along with its GetAllUsernamesMessage so that the app server will only send the changes that occurred since. This drives down network usage even more at the insignificant cost of some disk space on the web servers.

And in closing…

Even if you don’t have anything more than a single physical server today, and it acts as your web server and database server, this solution won’t slow things down. If anything, it’ll speed it up. Regardless, you’re much better prepared to scale out than before – no need to rip and replace your entire architecture just as you get 8 million Facebook users banging down your front door.

So, go check out NServiceBus and get the most out of your iron.



Fetching Strategy NHibernate Implementation Available

Sunday, September 16th, 2007

A couple of months ago I put out a post discussing one way to implement custom fetching strategies. Anyway, I finally got around to putting my money where my mouth was…

So, I’ve implemented the pattern in NHibernate, adding the following method to ISession:

T Create<T>();

As well as adding the following interface to the NHibernate package:

public interface IFetchingStrategy<T>
{
ICriteria AddFetchJoinTo(ICriteria criteria);
}

All this enables you to have a stronger separation between your service layer classes and your domain model class, as well as for you to express each service-level use case as a domain concept – an interface.

Once you have such an interface, you can create a fetching strategy for that use case and define exactly how deep of an object graph you want to load so that you only hit the DB once for that use case.

The nice thing is that its all configured with Spring. In other words, if you the entry for your fetching strategy class exists, you get the improved performance, if it doesn’t, you don’t. All without touching your service layer classes.

Just as an example, when I’m in the use case modeled by “ICustomer”, I want to get all the customer’s orders, and their orderlines. This would be done by having a class like this:

public class CustomerFetchingStrategy : IFetchingStrategy<ICustomer>
{
public ICriteria AddFetchJoinTo(ICriteria criteria)
{
criteria.SetFetchMode(“orders”, FetchMode.Eager).
SetFetchMode(“orders.orderLines”, FetchMode.Eager);

return criteria;
}
}

And the configuration would look like this (as a part of the regular spring template):

<object id=”CustomerFetchingStrategy” type=”Domain.Persistence.CustomerFetchingStrategy, Domain.Persistence” />

If you want to take a look at the full solution, you can find it here. For some reason, the combined file was too big for the upload on my blog so it’s split into two. Unzip both packages into the same directory. You’ll find a file called “db_scripts.sql” which contains the schema for the DB. Don’t forget to update your connection string in the “hibernate.cfg.xml”. If you’re looking for the changes I made to the NHibernate source, you can find it in the “Updated NHibernate Files” directory. The only real change is to the “SessionImpl.cs” file.

Relevant NHibernate and Spring binaries.

Source code of example.

BTW, there is some intelligent thread-safe caching going on in SessionImpl now so that you get a much smaller performance hit (in terms of code that uses reflection) on subsequent usages of the same interfaces.

Let me know what you think.



Performant and Explicit Domain Models

Monday, June 4th, 2007

Some Technical Difficulties

Ayende and I had an email conversation that started with me asking what would happen if I added an Order to a Customer’s “Orders” collection, when that collection was lazy loaded. My question was whether the addition of an element would result in NHibernate hitting the database to fill that collection. His answer was a simple “yes”. In the case where a customer can have many (millions) of Orders, that’s just not a feasible solution. The technical solution was simple – just define the Orders collection on the Customer as “inverse=true”, and then to save a new Order, just write:

session.Save( new Order(myCustomer) );

Although it works, it’s not “DDD compliant” 🙂

In Ayende’s post Architecting for Performance he quoted a part of our email conversation. The conclusion I reached was that in order to design performant domain models, you need to know the kinds of data volumes you’re dealing with. It affects both internals and the API of the model – when can you assume cascade, and when not. It’s important to make these kinds of things explicit in the Domain Model’s API.

How do you make “transparent persistence” explicit?

The problem occurs around “transparent persistence”. If we were to assume that the Customer object added the Order object to its Orders collection, then we wouldn’t have to explicitly save orders it creates, so we would write service layer code like this:

using (IDBScope scope = this.DbServices.GetScope(TransactionOption.On))
{
IOrderCreatingCustomer c = this.DbServices.Get<IOrderCreatingCustomer>(msg.CustomerId);
c.CreateOrder(message.OrderAmount);

scope.Complete();
}

On the other hand, if we designed our Domain Model around the million orders constraint, we would need to explicitly save the order, so we would write service layer code like this:

using (IDBScope scope = this.DbServices.GetScope(TransactionOption.On))
{
IOrderCreatingCustomer c = this.DbServices.Get<IOrderCreatingCustomer>(msg.CustomerId);
IOrder o = c.CreateOrder(message.OrderAmount);
this.DbServices.Save(o);

scope.Complete();
}

But the question remains, how do we communicate these guidelines to service layer developers from the Domain Model? There are a number of ways, but it’s important to decide on one and use it consistently. Performance and correctness require it.

Solution 1: Explicitness via Return Type

The first way is a little subtle, but you can do it with the return type of the “CreateOrder” method call. In the case where the Domain Model wishes to communicate that it handles transparent persistence by itself, have the method return “void”. Where the Domain Model wishes to communicate that it will not handle transparent persistence, have the method return the Order object created.

Another way to communicate the fact that an Order has been created that needs to be saved is with events. There are two sub-ways to do so:

Solution 2: Explicitness via Events on Domain Objects

The first is to just define the event on the customer object and have the service layer subscribe to it. It’s pretty clear that when the service layer receives a “OrderCreatedThatRequiresSaving” event, it should save the order passed in the event arguments.

The second realizes that the call to the customer object may come from some other domain object and that the service layer doesn’t necessarily know what can happen as the result of calling some method on the aggregate root. The change of state as the result of that method call may permeate the entire object graph. If each object in the graph raises its own events, its calling object will have to propagate that event to its parent – resulting in defining the same events in multiple places, and each object being aware of all things possible with its great-grandchild objects. That is clearly bad.

What [ThreadStatic] is for

So, the solution is to use thread-static events.

[Sidebar] Thread-static events are just static events defined on a static class, where each event has the ThreadStaticAttribute applied to it. This attribute is important for server-side scenarios where multiple threads will be running through the Domain Model at the same time. The easiest thread-safe way to use static data is to apply the ThreadStaticAttribute.

Solution 3: Explicitness via Static Events

Each object raises the appropriate static event according to its logic. In our example, Customer would call:

DomainModelEvents.RaiseOrderCreatedThatRequiresSavingEvent(newOrder);

And the service layer would write:

DomainModelEvents.OrderCreatedThatRequiresSaving +=
delegate(object sender, OrderEventArgs e) { this.DbServices.Save(e.Order); };

The advantage of this solution is that it requires minimal knowledge of the Domain Model for the Service Layer to correctly work with it. It also communicates that anything that doesn’t raise an event will be persisted transparently behind the appropriate root object.

Statics and Testability

I know that many of you are wondering if I am really advocating the use of statics. The problem with most static classes is that they hurt testability because they are difficult to mock out. Often statics are used as Facades to hide some technological implementation detail. In this case, the static class is an inherent part of the Domain Model and does not serve as a Facade for anything.

When it comes to testing the Domain Model, we don’t have to mock anything out since the Domain Model is independent of all other concerns. This leaves us with unit testing at the single Domain Class level, which is pretty useless unless we’re TDD-ing the design of the Domain Model, in which case we’ll still be fiddling around with a bunch of classes at a time. Domain Models are best tested using State-Based Testing; get the objects into a given state, call a method on one of them, assert the resulting state. The static events don’t impede that kind of testing at all.

What if we used Injection instead of Statics?

Also, you’ll find that each Service Layer class will need to subscribe to all the Domain Model’s events, something that is easily handled by a base class. I will state that I have tried doing this without a static class, and injecting that singleton object into the Service Layer classes, and in that setter having them subscribe to its events. This was also pulled into a base class. The main difference was that the Dependency Injection solution required injecting that object into Domain Objects as well. Personally, I’m against injection for domain objects. So all in all, the static solution comes with less overhead than that based on injection.

Summary

In summary, beyond the “technical basics” of being aware of your data volumes and designing your Domain Model to handle each use case performantly, I’ve found these techniques useful for designing its API as well as communicating my intent around persistence transparency. So give it a try. I’d be grateful to hear your thoughts on the matter as well as what else you’ve found that works.

Related posts:



Layering – too simplistic to actually work

Sunday, June 3rd, 2007

After seeing Mark’s post on Reasons for Isolation describing the ways Layered Architectures break down, and the ways making it more testable can change it, I’ve got to wonder – is Layering just too simplistic to actually work?

Just the other day I was doing a design review for a fairly simple Smart Client whose design was layered. In order to stay away from interfaces that accepted dozens of ints, strings, and dates, they wanted to have each layer talk to the other using “entities”. So where are these entities defined – oh, in a “vertical layer” that all the horizontal layers talk to.

OK, so we’ve taken the simplistic one-dimensional layered architecture and added a dimension. What now?

Well, it seems that having the business logic and the entities in separate layers goes against one of the most basic Object Oriented principles – encapsulation. So, let’s put the entities back in the Business Logic Layer. But then how will the Data Access Layer accept those objects as parameters?

So, that is solved by keeping Entity Interfaces in the “vertical” shared “layer”, and having the entities in the business logic layer implement those interfaces. That way, the data access layer can still accept parameters corresponding to those interfaces:

void InsertCustomer(Shared.Entities.ICustomer customer);

So far so good. Now, we want more testable UI layer code – so we use Model-View-Controller (MVC) – of whichever flavor suits your fancy. I’d say that Supervising Controller is a must. You could also add another presenter for more complex screens as in Passive View, but I’d be less strict on that. So, in which layer do these Controllers/Presenters sit? And is the Business Logic Layer the Model? Or is the Model just part of it?

Well, our Supervising Controllers are those who decide what action to do and when, where to get the data from, etc. That sounds like business logic to me. So let’s put them in the BLL. Presenters for the Passive View are much more UI centered, so let’s put them in the Presentation Layer. But we don’t want them tied to the implementation of the view, so we’ll put them in a separate package, and have them depend only on the view’s interface. So we’ll put the view interfaces in a package separate from the view implementation as well.

If it wasn’t clear up to this point, all the questions raised in this post are architectural in nature – as in they have a substantial impact on the structure and flow of the system, and will definitely have a profound effect on its maintainability. In other words, if you think that Layer Diagram covers your design – you’re probably deluding yourself. Personally, I think that’s why many developers consider architects to be “out of touch with the real world”.

When you have a design that answers these, and other architectural concerns, you’ll find that layering is of little importance. The specific constraints on each package are what counts. The fact that the Presentation Layer can talk to the Business Logic Layer doesn’t mean that the classes in your Views Implementation Package can. A large part of an architects work is to specify these constraints, and communicate them to the team. Tools like FxCop may help in terms of enforcing these constraints, but I believe that getting the team to actually “buy-in” is more effective.

Single-dimensional layered architectures don’t work. They violate Einstein’s maxim:

Make everything as simple as possible, but not simpler.

Layering – “simpler” to the point of simplistic.



NHibernate will rule, because Ayende already does

Sunday, May 20th, 2007

First I find out that NHibernate does support “Persistence by Reachability”, even though the docs say it doesn’t. Next, Ayende makes it support multiple queries in a single DB roundtrip, something I’ve been asking all the other O/R mappers out there to do. To top it off, he’s got his sights set on solving the issues I raised in my talk on Complex Business Logic with DDD and O/R Mapping at DevTeach. That’s right, he’s going to give me my decorators and state machines.

I love you, Oren.

I know that the ADO.NET Entity Framework guys are open to this as well, but I’m pretty sure that the “Entity Model” thinking will hold them back. You just can’t divorce data and behavior – not when employing state machines or decorators.

I’m sold.



   


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“Udi has helped PCLine on projects by implementing architectural blueprints demonstrating the value of simple design and code.”

Rhys Campbell Rhys Campbell, Owner at Artemis West
“For many years I have been following the works of Udi. His explanation of often complex design and architectural concepts are so cleanly broken down that even the most junior of architects can begin to understand these concepts. These concepts however tend to typify the "real world" problems we face daily so even the most experienced software expert will find himself in an "Aha!" moment when following Udi teachings.
It was a pleasure to finally meet Udi in Seattle Alt.Net OpenSpaces 2008, where I was pleasantly surprised at how down-to-earth and approachable he was. His depth and breadth of software knowledge also became apparent when discussion with his peers quickly dove deep in to the problems we current face. If given the opportunity to work with or recommend Udi I would quickly take that chance. When I think .Net Architecture, I think Udi.”

Sverre Hundeide Sverre Hundeide, Senior Consultant at Objectware
“Udi had been hired to present the third LEAP master class in Oslo. He is an well known international expert on enterprise software architecture and design, and is the author of the open source messaging framework nServiceBus. The entire class was based on discussion and interaction with the audience, and the only Power Point slide used was the one showing the agenda.
He started out with sketching a naive traditional n-tier application (big ball of mud), and based on suggestions from the audience we explored different solutions which might improve the solution. Whatever suggestions we threw at him, he always had a thoroughly considered answer describing pros and cons with the suggested solution. He obviously has a lot of experience with real world enterprise SOA applications.”

Raphaël Wouters Raphaël Wouters, Owner/Managing Partner at Medinternals
“I attended Udi's excellent course 'Advanced Distributed System Design with SOA and DDD' at Skillsmatter. Few people can truly claim such a high skill and expertise level, present it using a pragmatic, concrete no-nonsense approach and still stay reachable.”

Nimrod Peleg Nimrod Peleg, Lab Engineer at Technion IIT
“One of the best programmers and software engineer I've ever met, creative, knows how to design and implemet, very collaborative and finally - the applications he designed implemeted work for many years without any problems!

Jose Manuel Beas
“When I attended Udi's SOA Workshop, then it suddenly changed my view of what Service Oriented Architectures were all about. Udi explained complex concepts very clearly and created a very productive discussion environment where all the attendees could learn a lot. I strongly recommend hiring Udi.”

Daniel Jin Daniel Jin, Senior Lead Developer at PJM Interconnection
“Udi is one of the top SOA guru in the .NET space. He is always eager to help others by sharing his knowledge and experiences. His blog articles often offer deep insights and is a invaluable resource. I highly recommend him.”

Pasi Taive Pasi Taive, Chief Architect at Tieto
“I attended both of Udi's "UI Composition Key to SOA Success" and "DDD in Enterprise Apps" sessions and they were exceptionally good. I will definitely participate in his sessions again. Udi is a great presenter and has the ability to explain complex issues in a manner that everyone understands.”

Eran Sagi, Software Architect at HP
“So far, I heard about Service Oriented architecture all over. Everyone mentions it – the big buzz word. But, when I actually asked someone for what does it really mean, no one managed to give me a complete satisfied answer. Finally in his excellent course “Advanced Distributed Systems”, I got the answers I was looking for. Udi went over the different motivations (principles) of Services Oriented, explained them well one by one, and showed how each one could be technically addressed using NService bus. In his course, Udi also explain the way of thinking when coming to design a Service Oriented system. What are the questions you need to ask yourself in order to shape your system, place the logic in the right places for best Service Oriented system.

I would recommend this course for any architect or developer who deals with distributed system, but not only. In my work we do not have a real distributed system, but one PC which host both the UI application and the different services inside, all communicating via WCF. I found that many of the architecture principles and motivations of SOA apply for our system as well. Enough that you have SW partitioned into components and most of the principles becomes relevant to you as well. Bottom line – an excellent course recommended to any SW Architect, or any developer dealing with distributed system.”

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