I have a WPF application that uses entity framework. I am going to be implementing a repository pattern to make interactions with EF simple and more testable. Multiple clients can use this application and connect to the same database and do CRUD operations. I am trying to think of a way to synchronize clients repositories when one makes a change to the database. Could anyone give me some direction on how one would solve this type of issue, and some possible patterns that would be beneficial for this type of problem?
I would be very open to any information/books on how to keep clients synchronized, and even be alerted of things other clients are doing(The only thing I could think of was having a server process running that passes messages around). Thank you
The easiest way by far to keep every client UI up to date is just to simply refresh the data every so often. If it's really that important, you can set a DispatcherTimer to tick every minute when you can get the latest data that is being displayed.
Clearly, I'm not suggesting that you refresh an item that is being edited, but if you get the fresh data, you can certainly compare collections with what's being displayed currently. Rather than just replacing the old collection items with the new, you can be more user friendly and just add the new ones, remove the deleted ones and update the newer ones.
You could even detect whether an item being currently edited has been saved by another user since the current user opened it and alert them to the fact. So rather than concentrating on some system to track all data changes, you should put your effort into being able to detect changes between two sets of data and then seamlessly integrating it into the current UI state.
UPDATE >>>
There is absolutely no benefit from holding a complete set of data in your application (or repository). In fact, you may well find that it adds detrimental effects, due to the extra RAM requirements. If you are polling data every few minutes, then it will always be up to date anyway.
So rather than asking for all of the data all of the time, just ask for what the user wants to see (dependant on which view they are currently in) and update it every now and then. I do this by simply fetching the same data that the view requires when it is first opened. I wrote some methods that compare every property of every item with their older counterparts in the UI and switch old for new.
Think of the Equals method... You could do something like this:
public override bool Equals(Release otherRelease)
{
return base.Equals(otherRelease) && Title == otherRelease.Title &&
Artist.Equals(otherRelease.Artist) && Artists.Equals(otherRelease.Artists);
}
(Don't actually use the Equals method though, or you'll run into problems later). And then something like this:
if (!oldRelease.Equals(newRelease)) oldRelease.UpdatePropertyValues(newRelease);
And/Or this:
if (!oldReleases.Contains(newRelease) oldReleases.Add(newRelease);
I'm guessing that you get the picture now.
Related
We have multiple projects with multiple portlets and need to send an array of objects between them.
Our situation:
One of the porlets is like a "Master-portlet", it will be responsible for all the REST-calls and consume json-data and parse it to Java-Objects.
All the other portlets will receive an array of objects and show them to the user.
Our thoughts and solution:
We wanted to implement this by sending arrays of objects trough events. One of the "smaller" portlets will send an event to the "Master-portlet" and the "Master-portlet" will then answer with a new event and send the right array of objects back.
Our problem:
We dont know how to send arrays of objects trough events. Is this even possible?
Also we are not sure if this is the right way to solve this. Are events ment to send a bigger amount of data?
Is there a better solution for our case? Maybe it would be better to implement a database and all the portlets get the information from there?
Consider portlet events (and portlets) the UI layer of your application. Based on this, judge if the amount of data that you send back and forth makes sense or not. Also, if you closely couple the portlets, you're just hiding the fact that they can only function together - at least a questionable idea. You rather want them to react to common circumstances (events), but not rely on a specific source of events (master portlet) being available.
That being said: The more complex the data is that you send as payload of a JSR-286 event, the easier you run into classloading problems in cases where your portlets are in different webapplications. If you restrict yourself to Java native types (e.g. String, Map, etc) you will omit problems with the classloader.
Typically you want to communicate changes to the current context (e.g. new "current customer" selected - and an identifier) but not all of the particular data (e.g. the new customer's name and order history). The rest of the data typically comes through the business layer anyway.
That's not to say that you absolutely must not couple your portlets - just that my preference is to rather have them very loosely coupled, so that I can add individual small portlets that replace those that I thought of yesterday.
If you have some time, I've covered a bit of this in a webinar last year, I hope that this adds some clarification where I was too vague in this quick answer.
Many examples on the net show you how to use ng-repeat with in-memory data, but in my case I have long table with infinite scroll that gets data by sending requests to a REST API (scroll down - fetch some data, scroll down again - fetch some more data, etc.). It does work, but I'm wondering how can I integrate that with filters?
Right now I have to call a specific method of API service that makes a request based on text in "search" input box and then controller updates $scope.data.
Is it possible to build a custom filter that would do that? And then my view would be utterly decoupled from the service and I could declaratively tell it how to group and order and filter data, regardless if it's in-memory or comes from a remote server, server that can serve only limited records at a time.
Also later I'm gonna need grouping and ordering as well, I'm so tempted to download the entire dataset and lock parts of the app responsible for grouping, searching and ordering (until all data is on the client), but:
a) that dataset is huge (hundred thousands of records)
b) nobody wants to deal with cache invalidation headaches
c) doing so feels so damn wrong, you don't really expect me to 'keep' all that data in-memory, right?
Can you guys point me to maybe some open-source examples where I can steal some ideas from?
Basically I need to build a service and filters that let me to work with my "pageable" data that comes from api, like it's in memory-data.
Regardless of how you choose to solve it (there are many ways to infinite-scroll with angular, here is one: http://binarymuse.github.io/ngInfiniteScroll/), at its latest current beta version, ng-repeat works really bad with large amount of data - so do filters. The reason is obvious - pulling so much information for changes is a tuff job. Moreover, ng-repeat by default will re-draw your complete list every time something changes.
There are many solutions you can explore in this area, here are the ones I found productive:
http://kamilkp.github.io/angular-vs-repeat/#?tab=8
http://www.williambrownstreet.net/blog/2013/07/angularjs-my-solution-to-the-ng-repeat-performance-problem/
https://github.com/allaud/quick-ng-repeat
You should also consider the following, which really helps with large amounts of data.
https://github.com/Pasvaz/bindonce
Updated
I guess you can't really control your server output, because filtering and ordering large amount of data are better off done on the server side.
I was pointing out the links above since even if you write your own filters (and order-bys), which is quite simple to do - http://jsfiddle.net/gdefpfqL/ - (filter by some company name and then click the "Add More" button - to add more items). ordering by is virtually impossible if you can't control the data coming for the server - the only option is getting it all, ordering and then lazy load from the client's memory. So if each of your list items doesn't have many binding by it self (as in the example I've added) - the list item is a fairly simple one (for instance: you simply present the results as a plain text in a <li>{{item.name}}</li> then angular ng-repeat might work for you. In this case, filters will work as expected - say you filter by searched text:
<li ng-repeat="item in items | filter:searchedText"></li>
even for new items added after the user has searched a text, it will still works because the magic of binding.
In his book on DbContext, #RowanMiller shows how to use the DbSet.Local property to avoid 1.) unnecessary roundtrips to the database and 2.) passing around collections (created with e.g. ToList()) in the application (page 24). I then tried to follow this approach. However, I noticed that from one using [} – block to another, the DbSet.Local property becomes empty:
ObservableCollection<Destination> destinationsList;
using (var context = new BAContext())
{
var query = from d in context.Destinations …;
query.Load();
destinationsList = context.Destinations.Local; //Nonzero here.
}
//Do stuff with destinationsList
using (var context = new BAContext())
{
//context.Destinations.Local zero here again;
//So no way of getting the in-memory data from the previous using- block here?
//Do I have to do another roundtrip to the database here to get the same data I wanted
//to cache locally???
}
Then, what is the point on page 24? How can I avoid the passing around of my collections if the DbSet.Local is only usable inside the using- block? Furthermore, how can I benefit from the change tracking if I use these short-lived context instances not handing over any cache data to each others under the hood? So, if the contexts should be short-lived for freeing resources such as connections, have I to give up the caching for this? I.e. I can’t use both at the same time (short-lived connections but long-lived cache)? So my only option would be to store the results returned by the query in my own variables, exactly what is discouraged in the motivation on page 24?
I am developing a WPF application which maybe will also become multi-tiered in the future, involving WCF. I know Julia has an example of this in her book, but I currently don’t have access to it. I found several others on the web, e.g. http://msdn.microsoft.com/en-us/magazine/cc700340.aspx (old ObjectContext, but good in explaining the inter-layer-collaborations). There, a long-lived context is used (although the disadvantages are mentioned, but no solution to these provided).
It’s not only that the single Destinations.Local gets lost, as you surely know all other entities fetched by the query are, too.
[Edit]:
After some more reading in Julia Lerman’s book, it seems to boil down to that EF does not have 2nd level caching per default; with some (considerable, I think) effort, however, ones can add 3rd party caching solutions, as is also described in the book and in various articles on MSDN, codeproject etc.
I would have appreciated if this problem had been mentioned in the section about DbSet.Local in the DbContext book that it is in fact a first level cache which is destroyed when the using {} block ends (just my proposal to make it more transparent to the readers). After first reading I had the impression DbSet.Local would always return the same reference (Singleton-style) also in the second using {} block despite the new DbContext instance.
But I am still unsure whether the 2nd level cache is the way to go for my WPF application (as Julia mentions the 2nd level cache in her article for distributed applications)? Or is the way to go to get my aggregate root instances (DDD, Eric Evans) of my domain model into memory by one or some queries in a using {} block, disposing the DbContext and only holding the references to the aggregate instances, this way avoiding a long-lived context? It would be great if you could help me with this decision.
http://msdn.microsoft.com/en-us/magazine/hh394143.aspx
http://www.codeproject.com/Articles/435142/Entity-Framework-Second-Level-Caching-with-DbConte
http://blog.3d-logic.com/2012/03/31/using-tracing-and-caching-provider-wrappers-with-codefirst/
The Local property provides a “local view of all Added, Unchanged, and Modified entities in this set”. Like all change tracking it is specific to the context you are currently using.
The DB Context is a workspace for loading data and preparing changes.
If two users were to add changes at the same time, they must not know of the others changes before they saved them. They may discard their prepared changes which suddenly would lead to problems for other other user as well.
A DB Context should be short lived indeed, but may be longer than super short when necessary. Also consider that you may not save resources by keeping it short lived if you do not load and discard data but only add changes you will save. But it is not only about resources but also about the DB state potentially changing while the DB Context is still active and has data loaded; which may be important to keep in mind for longer living contexts.
If you do not know yet all related changes you want to save into the database at once then I suggest you do not use the DB Context to store your changes in-memory but in a data structure in your code.
You can of course use entity objects for doing so without an active DB Context. This makes sense if you do not have another appropriate data class for it and do not want to create one, or decide preparing the changes in them make more sense. You can then use DbSet.Attach to attach the entities to a DB Context for saving the changes when you are ready.
Lets take an example of WinForms applcation and making invoice. On the Invoice form we retrieve a list of products, so the user will be ale to pick products for current invoice. Lets also consider that during this process user realizes that he needs to add a new product (or edit current) to ProductList before he can place it in invoice. So he opens a ProductForm where all the products are retreived (again).
It could also be in opposite order, that user first edits Products, and then without closing the Products Form, opens new Invoice. The principle is that data is two times loaded, and effectively its the same data.
What is the propper way to handle this scenario, so we can tell one form that data is already loaded, and to retrieve that data from memory? And when all the consumers (Forms) of the data are closed, then also the data should be released from memory? Or I am going in wrong direction, and there is a better way?
Thanks,
Goran
Definitelly go with data loaded "twice" or you will introduce much worse problems.
Sharing data means sharing ObjectContext. Even in WinForms application this is considered as bad approach. Check this article (it is about NHibernate but the description is valid for EF as well).
The problem is that ObjectContext is unit of work. If share context between two windows you can easily get into situation where you modify data in first window (without saving them!) and you continue in second window where you push save button but it will save data from both windows! You can't selectively save data only from one window when you share the context.
If the Controls that are using the data are all child controls of a shared Parent control, then you could just pass around the datacontext, so that they all shared the same datacontext.
However, the general use case with databases, which is what backs EF in most cases, is to read the data in each time that it is needed.
A solution to this if as you say you already have the item being used in one form is to just take a Refrence to that item into your new form.
So in the case Where you have an invoice which has a Product List and you want to add to the product list, you could pass the product list from the invoice to the opening product list.
There are some issues with this:
If another user changes the datasource while one has opened it (a.k.a. Concurrency)
Handling save don't save scenarios where they may have made a change in one area that they don't actually want added to the data.
However, unless it is a true performance issues, I would just load the data every time. You can simplify this a lot by using the repository pattern, so you can just call a single method to get a list of products or an invoice, or whatever part of data you need.
I have a collection of "active objects". That is, objects that need to preiodically update themselves. In turn, these objects should be used to update a WPF-based GUI.
In the past I would just have each object include it's own thread, but that only makes sense when working with a finite number of objects with well-defined life-cycles. Now I'm using objects that only exist when needed by a form so the life cycle is unpredicable. Also, I can have dozens of objects all making database and web service calls.
Under normal circumstances the update interval is 1 second, but it can take up to 30 seconds due to timeouts.
So, what design would you recommend?
You may use one dispatcher (scheduler) for all or group of active objects. Dispatcher can process high priority tasks at the first place then other ones.
You can see this article about the long-running active objects with code to find out how to do it. In additional I recommend to look at Half Sync/ Half Async pattern.
If you have questions - welcome.
I am not an expert, but I would just have the objects fire an event indicating when they've changed. The GUI can then refresh the necessary parts of itself (easy when using data binding and INotifyPropertyChanged) whenever it receives an event.
I'd probably try to generalize out some sort of data bus, if possible, and when objects are 'active' have them add themselves to a list of objects to be updated. I'd especially be tempted to use this pattern if the objects are backed by a database, as that way you can aggregate multiple queries, instead of having to do a single query per each object.
If there end up being no listeners for a specific object, no big deal, the data just goes nowhere.
The core updater code can then use a single timer (or multiple, or whatever is appropriate) to determine when to get updates. Doing this as more of a dataflow, and less of a 'state update' will probably save a lot of sanity in the end.