Implementing N-Tier Change Tracking with Linq to SQL

 

When designing our application data model, we think some of our entities as an in-memory cache of small pieces of data living in a database (MSSQL, Oracle, Xml files, etc.). This data will be jumping between both worlds.

To keep this "cache" synchronized, we need mechanisms to read data from storage, and update changes back, to perform that we create CRUD operations.

The "U" in CRUD is the subject of this entry, update changes back.

Once we read an entity from the db we must track changes on it, in order to reproduce them in the storage.

To facilitate this, ADO.Net brought features as the DataRow.RowState property. Based on that we wrote code, that typically uses the RowState to perform the corresponding creations, updates, or deletes in the db.

What happens when we have Linq to SQL custom classes?

 

Linq to SQL DataContext Object Tracking

When entities are obtained from a DataContext object, this DataContext subscribes to change notification events on every entity, and tracks changes automatically, generating an internal change set. When we want to persist changes, we call the DataContext SubmitChanges() method and all the INSERT, UPDATE and DELETE commands are sent to the SQL Server.

This mechanism works great in a connected scenario, but in an N-tier architecture, modifications of your entities can be done in a machine far far away from the DataContext that created them, they can't (or shouldn't! :)) notify this changes thru the wire.

As we explained in previous posts, we need detached entities.

How do Linq to SQL supports this scenario? It allows you to detach and re-attach entities, but now change tracking is your job.

Detaching entities can be achieved in two ways:

• serializing-deserializing entities, deserialized entities are detached by nature.
• setting the DataContext ObjectTrackingEnabled property to false (after that all entities obtained are not tracked).

Notice that the first option would force serialization and deserialization even in a connected Winforms app,  so we'll always use the second.

Once your entity comes back modified to the data access layer you can re-attach it to a new DataContext using the Attach() method in every Linq Table, but you must tell if this entity has been modified/created/deleted (or not).

"Those who don’t know their history are doomed to repeat it."

That means we need to track this information on the client, and send it back to the server. We need to build our own... disconnected change tracking!

 

Disconnected Change Tracking

Of course we are not the first in getting here!, using Linq to SQL in an N-tier scenario is something many people is working on. Actually the same issue is been discussed in the Entity Framework world, because there seems to be no official solution there either (yet).

So I googled a bit to see what others are doing. And most of the solutions can be grouped in this two categories:

Portable Client-DataContext

At an early stage of Linq to SQL Microsoft were planning to ship this with the first release, as explained by Mat Warren, he described it like this:

"The mechanism that does the change tracking on the client is similar to a mini-connectionless DataContext.  It is a type that packages up all the objects, lists of objects and graphs that you want to send to the client.  It serializes itself and everything you've given it automatically.  (It implements IXmlSerializable.)  On the client, the same class also manages change-tracking for all the objects that were serialized with it.  When serialized again (on the trip back) it serializes both the objects and their change information that it logged.  Back on the middle tier, you just make one call to re-attach the whole package to a new DataContext instance and then call SubmitChanges."

Finally, this didn't get to the current release, and many people came up with their own implementation of it, deeper ruminations on this approach can be found in this OakLeaf article.

The best thing here is "entity pureness", entities completely ignore persistence, they can be pure POCOs, without a base class. But be aware that this pureness is not so absolute, entities must implement interfaces an events for property change notification, we just don't note this because the implementation is in auto-generated code.

Also, this means that an entity never knows his own dirty state or original values, to know it you must reference this portable context. This makes rollback changes a complicated task (actually there's no support for rollback to original values in the Linq to SQL DataContext).

This also requires some "packing" and "unpacking" code in the client.

 

Entities with state flags

The other approach implies including in every entity a state field, and eventually original values. An attractive point here is that this is just what our old well known ADO.Net DataSet has been doing all this time (se DataRow.RowState property). It's a pattern we've seeing for years in change tracking.

We can achieve this using an entity base class (this can be set in a Dbml file, but unfortunately this attribute is not visible in the O/R Designer).

To avoid sticking ourselves to an specific implementation we can use an "entity with state" interface.

 

The Tercer Planeta's choice

Matthew Hunter is working on the same problem, and asked in a previous post which way are we taking, that's why I decided to write this entry.

When standing against this fork in the road so crucial in our lives, first of all we breath deeply, and thought why we need this, and decide to list the kind of changes we want to track. And we found at that all we need to track is:

• Dirty state in every entity
• Added/Removed/Existent states only in entity collections

Why we don't want Added/Removed/Existent states in single entities? Because that info should be in the business logic, in other words the business logic knows if I'm creating, deleting or updating. We don't want a generic "ApplyChanges" method internally doing an insert, update or delete at will.

This means, if I'm in the ProducEditForm and click on the "save" button, I expect the Form (and not the entity) to tell me which action to perform (create, update or delete).

Based on that we came up with a separation of concerns here.

We chose the path of entities with state, in this path of green hills and crystal clear waters, every entity knows his dirty state thru a boolean flag in their base class. But adds/deletes of children are tracked by a custom collection class (replacing EntitySet).

Optionally, entities can keep a copy of their original values (for change rollback and concurrency checking when there's no timestamp), to allow this we may force ICloneable implementation.

Tracking must be activated explicitly. This doesn't only allow optional "read-only" mode, but also to distinguish new and pre-existent (on the db) entities.

ULinqGen compatibility

To facilitate change tracking the way I described above, a minor surgery is required on the Linq to SQL auto-generated entities... thanks god we are building a code generator custom tool for Dbml!

We are adding some improvements to our ULinqGen tool.

Our code generator must support change tracking but without binding it to our (or any) custom change tracking implementation.

What should we add to auto-generated code?

• Entity base class, Linq to SQL already has this feature, so no extra work would be necessary. the only drawback is that the EntityBaseClass attribute is global to all the entities in a Dbml, and is not visible from the O/R Designer (you can write it on the Dbml file with notepad). We'll probably add capability to specify per-entity base class.
• Property change notification, but as we don't have a listening context, we only need a generic "I'm getting dirty!" instance method call, we are requiring an IEntityState interface with this method. The implementation is let to the base class (if any), it could be an extension method of IEntityState!.
• We want to support optional "original values tracking", to allow this ULinqGen could easily generate an ICloneable implementation based on the entity metadata.

This will keep our code generator tool pretty much "naive" about the specific change tracking system. And read-only mode is still the default.

I'm not showing any code because we're currently discussing much of this, so you'll have to wait for the following ULinqGen releases! ;)

First thoughts on Designing a LINQ-enabled Application Framework

 

In the previous weeks (and the followings :), we've been intensively stressing the different LINQ-to-SQL features, lots of prototyping and architecture sketches, where made trying to obtain some conclusions about: What role (if any at all) do we want to give to LINQ in the architecture of our applications?

First of all, we need to answer a basic question "Do we want to add LINQ to our model?"

As Jose wrote on the previous article, there's no doubt we love LINQ as set of language extensions, combined with a set providers (LINQ-to-*) allowing us to write elegant strong-typed queries over heterogeneous collections without knowing all their specific APIs.

Considering this, it would be great to have a LINQ "Queryable" data access layer. With that idea,  we started to analyze LINQ-to-SQL integration in Enterprise applications of different scale.

 

Two-tier (logically separated) WinForms/WPF Application

This is our simple case: a presentation layer designed to be always physically connected to a business layer retrieving business entities from a local Data Source.

Even while there's a logical separation between layers, they share a common Application Domain. It's the case of simple desktop application accessing directly to a local (or remote) database.

Unit of Work

When we retrieve entities from our database we will use a DataContext, who follows the Unit-of-Work pattern.

It stays alive during a single business operation, handling the SQL Connection, and tracking changes on all the entities associated to it.

Every time we insert, modify or delete entities from a DataContext it updates an in-memory ChangeSet, with copies of the original and modified values of this entities.

Finally, when we finished working with them, we tell to the DataContext to submit this changes, and all the necessary commands are sent to the database. Then it's ready to be disposed.

The DataContext follows the Unit-of-Work pattern.

This is absolutely great in this connected environment. We query our DataContext, bind the IQueryable result to a BindingSource, a DataBinded Grid, edit, insert, or delete records, and when we are ready, all we need to do is MyDataContext.SubmitChanges();

And this won't only update any change we made to the entities, it will handle foreign-keys, concurrency checks and transactability.

This also means that the entities belong to their DataContext during all their lifetime, this wiring allows features as deferred loading (of properties, associated entities, child collections) and db-generated fields.

For a lot of reasons, this seems to be the main scenario for which the current Linq-To-Sql implementation has been designed.

 

N-tier (physically separated) Application

Let's try to scale the previous approach to a N-tier application, in this case our Business Layer is exposed thru a Service Layer, consumed (WCF) by a physically remote presentation layer (Winforms/WPF client, Asp.Net website, etc.)

How does LINQ-to-SQL supports this scenario?

Initially, we could say that LINQ-to-SQL will remain behind the Business Layer, and won't trespass the WCF barrier.

Out-of-Topic There's a few adventurous developers (here is a project in CodePlex) implementing serialization of Expression Trees, allowing to query a remote collection exposed thru a WCF Service, serializing the query (represented in an Expression Tree), deserializing it on the server, and returning the results to the client.

 

But there's something we surely want to move around these layers, Entities.

 

The auto-generated LINQ-to-SQL entities, can get decorated (selecting unidirectional serialization in the O/R Designer) with [DataContract] and [DataMember] attributes, allowing them to travel as parameters or results of a WCF Service Operation.

As expected, this would break the connected state of this entities, loosing all the cool features we had in the previous scenario (change tracking, deferred loading, etc.)

Those aren't actually very bad news, because having that features would encourage data-centric practices, opposed to the SOA model, that WCF is based on.

If we look to the Fowler's Lazy Load pattern description "An object that doesn't contain all of the data you need but knows how to get it.", we can note that the last underlined words, are in deep contradiction with the Persistence Ignorance pattern that we are trying to follow.

One of the reasons for this is that Linq, and all the new language extensions in C# 3.0 and VB9, eases  the handling of POCO entities, a principle that LINQ-to-SQL and the new Entity Framework seems to take advantage of.

In this scenario, having our entities detached from the DataContext is something we want. And by-design, entities get detached when serialized.

When this entities (or collection of entities), return modified to the Business Layer, they are detached, we just need to attach them to a new DataContext and submit their changes.

As track changing has been broken, when we re-attach an entity to a DataContext we need to tell how this entity must be updated, specifying:

• Original and current copies of the entities

or simply:

• Only current copies, as all modified

 

In few words, the ability to re-attach entities, adds basic N-tier support to LINQ-to-SQL, cutting off all the magic features (see Change Tracking, Deferred Loading, etc) that the connected state gave us.

 

One size fits all Solution

The previous scenarios seems to be well handled by the current LINQ implementation. But, an immediate conclusion we had studying them, it's that they imply a different logic behind the business layer.

The connected nature of the first type of application, is certainly un-scalable to the second, having a DataContext alive thru all the lifetime of an entity is unacceptable in an enterprise application model.

Besides that, it would be a bad choice in Asp.Net website to keep the DataContext (with it's ChangeSet) alive in memory between postbacks.

We want the 2 tiers in the Two-tier application, to be not only logically separated, but "physically separable", that would improve scalability (allowing reuse of the business layer in an N-tier application), and force a better responsibility-delegation between business and presentation layers.

Disclaimer: Forcing a "one size fits all" solution, "N-tier ready", implies some over-engineering for people building a simple desktop RAD applications (like in first scenario), but our main concern is focusing in Enterprise Solutions. In this Two-tier simpler always-connected desktop app, a possible advice could be: use LINQ-to-SQL "as it is".

 

All this took us to the significant choice of allowing only detached entities outside the business layer.

That implies destroying the DataContext after the entities are retrieved, and re-attaching them to a new DataContext at the moment of submitting changes. Many people got there, and found themselves struggling with the "Attach only when detached" nightmare. Rick Strahl is one of them (or should I say, us).

Attach only when detached

As explained in the Dinesh Kulkarni's blog detaching-attaching of Entities has been thought for N-Tier scenarios only, that's why attaching is allowed only for entities who has been previously serialized and deserialized.

That works great in N-Tier, but serializing-deserializing has no sense in a common application domain.

A workaround that many people had found for this, is roughly cut all the wires between entities and their DataContext, that can be accomplished resetting some Event Handlers, and replacing some deferred-loading-aware collections (EntitySet and EntityRef) with a simpler array or List<T>.

Fortunately for us, there's a feature in LINQ-to-SQL that comes to solve (in a more elegant way) this issues!.

LINQ-to-SQL POCO support

Even while the O/R Designer and SqlMetal provide automatic generation of wrapper-classes over our data entities, it's perfectly allowed to use our own POCOs decorated with the appropriate attributes.

The POCO movement (nicely explained here), it's based on the Persistence Ignorance pattern, which ensures Responsibility Delegation, in other words, we don't want our Entities to know anything about how they are persisted. The default auto-generated entities, pretty much respect this principle, they don't know anything about persistence (part of this info is in attributes decoration or mapping files).

But they do participate in their persistence mechanism!, by being closely associated to a DataContext, not only notifying changes, but loading deferred values or associated entities from it.

This behavior is mainly achieved thru change notifying events (declared in INotifyPropertyChanging/ed interface), and the new types EntityRef and EntitySet.

This two classes are used in auto-generated entities to load (lazy or not) properties created from foreign-keys, EntityRef is used for single reference (as in Product.Manufacturer.Name), and EntitySet for child-collections (as in Manufacturer.Products[2].Price).

They not only contain associated entities, they have the logic for deferred loading, and notifying the DataContext about modifications in references and child collections, allowing the change tracking feature.

As we read in LINQ-to-SQL blogs, it's possible to replace this types, with simpler, disconnected versions, EntityRef, can be replaced by a direct reference, and EntitySet by any ICollection<T>.

 

Putting the pieces together

With this ideas in mind, we started building prototypes, messing with O/R Designer and SqlMetal auto-generated code.

Putting together the pieces we want, replacing/discarding others.

These days we're starting to see the light and the end of tunnel, with custom tools and code we started to write.

More on this on following posts...