Im running a process that will affect a lot of records within a database for a user. I only want to apply all of the changes or none of them depending on the result of all of the changes. (e.g if one of the sub processes fail then no changes overall should take place). I also want to save notifications to the database to alert users of the outcome of the processes (e.g if a sub process fails then a notification is raised to let the user know that no changes were made due to reason x).
The best way I can think to do this is to detach all of the entries within the change tracker as they are added, then create notifications if something has succeeded or failed and save changes, then when it comes to applying all the changes I can iterate though the change tracker and reset the Entity State and save changes once more.
The issue i'm facing with this approach is that when it comes to reset the Entity State, I don't know whether the entity is Added or Modified. I could implement my own change tracker to store the previous state of the entity but it would make EF's change tracker redundant.
I could also only add all of the entity's right when I come to save them but that would require passing many objects down a chain link of nested methods right until the end.
Does anyone have any better suggestions or is it standard practice to use one of the mentioned hacks for this problem?
It sounds like you are trying to implement the Unit of Work pattern. The DbContext of EntityFramework makes this fairly easy to use, as the DbContext its self is the unit of work.
Just instantiate a new context and make the changes you need to it. You can pass the context around to any functions that make their changes. Once the "logical unit" operations are complete, call SaveChanges. As long as the individual methods do not call SaveChanges, you can compose them together in to a single unit, committed once the entire logical operation as finished. Everything will be committed atomically, within a single transaction. The data won't be left in an inconsistent state.
You told about transactions. Using Transactions or SaveChanges(false) and AcceptAllChanges()?
also you can implement versions of data in DB. as for me it will be more ease and correct way (you must always only insert data and never update. 1-to-many). in this case you can simply delete last records or mark them as unactive
Related
The Problem
We have an app that stores hierarchical data in a database. We have defined a POCO object which represents a row of data.
The problem is we need certain properties to be dependent on the item's children and others on their ancestors. As an example, if a ((great)grand)child has incomplete state, then implicitly all of its parents are also incomplete. Similarly, if a parent has a status of disabled, then all children should be implicitly disabled as well.
On the database side of things, everything works thanks to triggers. However, the issue we're having is then synching those changes to any in-memory ORM objects that may have been affected.
That's why we're thinking to do all of this, we need to ensure there is only ever one model instance in memory for any specific row in the database. That's the crux of the entire problem.
We're currently doing that with triggers in the DB, and one giant hash-set of weak references to the objects keyed on the database's ID for the in-memory ORM objects, but we're not sure that's the proper way to go.
Initial Design
Our 'rookie' design started by loading all objects from the database which quickly blew out the memory, let alone took a lot of time loading data that may never actually be displayed in the UI as the user may never navigate to it.
Attempt 2
Our next attempt expanded on the former by dynamically loading only the levels needed for actual display in the UI, which greatly sped up loading, but now doesn't allow the state of the hierarchy to be polled without several calls to the database.
Attempt 2B
Similar to above, but we added persistent 'implicit status' fields which were updated via triggers in the database. That way if a parent was disabled, a trigger updated all children accordingly. Then the model objects simply refreshed themselves with the latest values from the database. This has the down-side of putting some business logic in the model layer and some in the database triggers as well as making both database writes and reads needed for every operation.
Fully Dynamic
This time we tried to make our models 'dumb' and removed our business layer completely from the code, moving that logic entirely to the database. That way there was only single-ownership of the business rules. Plus, this guaranteed bad data couldn't be inserted into the database in the first place. However, here too we needed to constantly poll the database for the 'current' values, meaning some logic did have to be built in to know which objects needed to be refreshed.
Fully Dynamic with Metadata
Similar to above, but all write calls to the database returned an update token that told the models if they had to refresh any loaded parents or children.
I'm hoping to get some feedback from the SO community on how to solve this issue.
I have a method that will Remove a set of entities.
I have a method that will AddOrUpdate a set of entities.
These methods are independently useful, but they have issues working together in entity framework.
The problem is that after removing a set of entities, for example (A,B,C,D), subsequent queries that resolve to one or more of those records always return cached garbage copies whose property values were nulled during the removal process. An intermediate DbContext.SaveChanges solves the issue, but introduces additional overhead and leaves the operation in a half-complete state, so it would also have to be wrapped in another transaction.
What's the best way to handle this.
Should I avoid an API that has Remove and Add/Update operations altogether, instead opting for an up-front hybrid operation that determines which ones are actually being removed and which ones are sticking around to be updated? or
Should I keep the two useful methods and just wrap the two steps in a transaction scope, so that I can save changes to the context immediately after the remove, allowing subsequent adds/updates to properly reflect their removal, while still have the ability to commit or rollback at the end (e.g. if the new permissions can/cannot be set)?
I don't want use lower-level operations such as turning off tracking or attaching/detaching entities.
Suppose the entities are permissions. Business logic dictates that I should use a logical two-step process to reset a user's permissions by first deleting any that I have permission to delete, followed immediately by trying to add/update any new permissions that I am allowed to assign.
When approaching this with two separate steps, I run into the problem as follows. The first problem I encounter is that immediately after removing a set of permission entities like (A,B,C,D), entity framework mangles the object properties, setting many of them to null (presumably to sever foreign key relationships). The problem is that because the entities still exist in the database, when trying to "add or update" a permission which still has a record in the database but has been removed in the context, EF always returns the cached/garbage copy of it. So although I've removed the entity... I can't actually determine, within that same context, whether I need to re-attach/update it or add a new entity outright. In other words, the framework returns an entity as though it exists (because it does still exist in the database) in spite of it being flagged as removed, but that entity object has garbage/null data, so that I can't even tell at that point whether it's safe to add a new one or I should try to "un-remove" the existing one.
It seems to me that such a remove/add-or-update pattern is simply not good for this kind of entity framework (or even ORMs in general). Instead, I'd have to determine, in a single up-front operation, whether any of the new permissions already exist, so I can selectively delete the ones that are going away, while updating the ones that are just being reassigned (a new access level, for example).
I have a form with few tabs, and in each tab an grid control. When user select a row to be deleted i want to remove it from the grid, and if the object exist in the database remove it too, but not permanent - only if and when user clicks save on form.
For now, if object doesn't exist in db i remove it from the list, and if objects exist in db i delete it from db and remove it from the list. But, if user clicks Cancel button he expects row/s not to be deleted from database.
I have two possible solutions on my mind: 1) - remove object from list, and if objects exist in db add it to the list of objects to be deleted 2) - implement another list, getter will return only objects with state != ToBeDeleted (performance?)
Note: i'm not using ORM tool, working with my own ado.net based data access framework.
I think the case you are descibing just asks pretty much for a Transaction.
ADO.Net handles them easily, provided you are using a reasonable database engine (so: no SqlServerCE for example:))
See for example the TransactionScope class. You construct such object before interacting with the database, and the changes will be "commited" if and only if you call Complete(). If you just leave it alone or if you Dispose() it, the transaction will be cancelled and all changes on the DB will be "rolledback", so, reverted.
So, in your case, you may open the transaction in the Form's ctor or onLoaded(), and Complete() at "save", and Dispose() at any other window closing.
While this is the normal way of handling such things for small systems, especially single-user ones, but be careful: if your system has to handle many concurent useres, you may be not able to use it in this way. The Transaction blocks rows and tables until it is completed or cancelled, and the therefore "other users" may see large delays..
So, how many users do you have to support and how often they will try to edit the same things?
-- edit: (10 users)
With that many users, you will want to avoid long-running transactions. Opening transaction at form-load will be unacceptable, and will lock many users away until that one current user closes the window. But, using transactions at Save() that push all the changes in one batch are OK.
Of course, if you can eliminate transactions at all - that's great! But, it is very hard thing to do if you also need to preserve data integrity.. To eliminate the need of transactions, almost always you have to redesign both the data structure on the DB side, and the way you obtain and work with the data. If you want to redesign both, then I'd really recommend to first try redesigning it to use some existing data-access framework, as even the basic .Net ADO has really nice features for online editing of databases held at SqlClient-compliant databases..
So, assuming you don't want to rewrite/rethink most of your code, you just need to buffer the data and also, delay all of the actual operations on the database.
You may want to do it in a "simple" form: when you display your form, instead of binding your Form directly to the database-driven datasources - download all required data to some BindingList<>s, DataTables, etc - whatever container you like. And bind your form to them instead. Probably you have something like that already set up. But, the important thing is that all those datacontainers must be offline or at least readonly+delayloaded.
Next, you've got to intercept all operations that the user performs on the UI. Surely you have it done already, as I'm assuming the application works:) As your Forms are bound to that offline cached items, your application should perform the operation on that cached data, and don't touch the database at all. But there's more: along with performing them on cached data, you should record what happens to which table.
Then, when finally the user stops playing around and presses CANCEL :) - you just trash everything and close the form. database not changed.
On Save - you open a fresh transaction, then iterate over the list of changes and effectively replay your recorder changes on the database, then commit transaction.
Please note two things though: the database could have changed during the time the users cached the data and the time he pressed Save. You have to detect this and abort, or resolve conflicts. You should do that inside that transaction, either during or before executing the recorded changes. You may detect it by simply comparing the online data with offline cached data (the unchanged original values, not those modified by user), or you may use some other mechanisms like OptimisticLocking and just compare the version tags on the rows.
If you don't like record-replay, you may implement a "DIFF"ing utility that takes the modified offline data and compares it in a generic way with the current-online tables. This is somewhat harder, but has a bonus: with such utility, you can initially doubly-cache the data: one copy for offline reference (just stored and never touched by the user) and one copy for offline editing (all those bound to the Forms). Now, upon Save you open transaction and diff the reference data against the online database. If there are any difference - you've just detected a collision. Solve/merge/abort/etc. If no differences, then you diff the modified data against online-data, and apply all differences found to the database and commit transaction.
Either of those methods has its pros and cons: aside from difficulty of implementation, there's memory issues of caching, latency issues if you dare to copy too large tables, etc.
But - once solved, it would work pretty nice.
And as you finish, you can go and boast that you have just implemented a smaller sis' of the DataSet+DataTable. I'm not joking, and I'm not laughing at you. I'm just trying to show you why everyone is telling you to rewise your DAO layer and try understanding and using the hard work that was already done for you by the platform designers/developers :)
Anyways, I've said you can avoid the clashes and transactions at all if you rethink your data structure.. For example: why do you DELETE the rows at all? I know there's a nifty DELETE statement in the SQL, but, well, do you really need to delete that row? Can't you just add some 'bool isDeleted' column and when user deletes the row from the Grid - just make set that rowcell to True and make the application filter-out any isDeleted=true rows and not show them? and not include them in views and aggregations? Bonus: sys/db admins now have a magic tool: undelete..
Let's take it further: do you need to UPDATE the rows? Maybe you can just APPEND some information that from (this-date) that row should have a new price? of course, the structure must be greatly altered: entities doesn't have properties, but have logs of timestamped property changes (or either the rows must have version numbers and be duplicated..), queries must be done against only the newest versiosn data, etc. Pros: database is now append-only. Transactions, if needed at all, are hyper-short. Cons: SELECT queries are complicated and may be slow, especially when joining many tables..
Pro/Con: and your db actually starts looking very meta- instead of data-base...
Con: and this is really hard task to "upgrade" existing application to such db structure. Writing a new app from scratch and importing data from odl system may be few times faster.
Now, to summarise:
I do not recommend any of the ways described.
First, I recommend you to take some ORM framework like NHibernate, EntityFramework, XPO from DevExpress, or whetever else. Any of them will save you lots of time. Those three I list here even have OptimisticLocking collision detection built-in. Why use SQL-self-written framework when such tools exist?
If not, then next I recommed to use existing tools found in the framework. you use SqlClient, whydontya use DataSet and DataTables? They are provided along with SqlClient and they have many useful mechanisms just built-in, which otherwise you will spend weeks on implementing and testing all by yourself. Learn to use DataSets and its collision detection, and its merging algorithms, and use them. You will loose a bit of time on experimenting and learning, but you will save huge amounts of time on not-reinventing the wheel.
If you really want to do it manually, start with data-caching and record-replay. It is easy to comprehend, it is quite easy to introduce anywhere where you currently use plain SQL queries, and will quickly introduce you to all kinds of cache-syncing and version-checking problems, and you will soon learn in details why all those strange mechanisms in the above-mentioned frameworks were implemented, how they work and what pros/cons they have.
and about the doubly-cached diffing approach.. it will be more tempting to write that record-repay, but please: use it only if you know very well how to detect/solve/merge collisions. Have at least one record-replay approach implemented before you try it..
..and of course yo umay use long-lasting transactions. Dumb-easy to introduce, and they "just irritate" the users.. Well, or even make the system unusable when >90% of the users constantly collide and hit the locks, heh.. No, that was a joke. Don't use long-lasting transactions. They are ok for 1-4 users, or for very sparse databases..
I'm using .NET entity framework 4.1 with code-first approach to effectively solve the following problem, here simplified.
There's a database table with tens of thousands of entries.
Several users of my program need to be able to
View the (entire) table in a GridRow, which implied that the entire Table has to be downloaded.
Modify values of any random row, changes are frequent but need not be persisted immediately. It's expected that different users will modify different rows, but this is not always true. Some loss of changes is permitted, as users will most likely update same rows to same values.
On occasion add new rows.
Sounds simple enough. My initial approach was to use a long-running DbContext instance. This one DbContext was supposed to track changes to the entities, so that when SaveChanges() is called, most of the legwork is done automatically. However many have pointed out that this is not an optimal solution in the long run, notably here. I'm still not sure if I understand the reasons, and I don't see what a unit-of-work is in my scenario either. The user chooses herself when to persist changes, and let's say that client always wins for simplicity. It's also important to note that objects that have not been touched don't overwrite any data in the database.
Another approach would be to track changes manually or use objects that track changes for me, however I'm not too familiar with such techniques, and I would welcome a nudge in the right direction.
What's the correct way to solve this problem?
I understand that this question is a bit wishy-washy, but think of it as more fundamental. I lack fundamental understanding about how to solve this class of problems. It seems to me that long living DbContext is the right way, but knowledgeable people tell me otherwise, which leads me to confusion and imprecise questions.
EDIT1
Another point of confusion is the existance of Local property on the DbSet<> object. It invites me to use a long running context, as another user has posted here.
Problem with long running context is that it doesn't refresh data - I more discussed problems here. So if your user opens the list and modify data half an hour she doesn't know about changes. But in case of WPF if your business action is:
Open the list
Do as many actions as you want
Trigger saving changes
Then this whole is unit of work and you can use single context instance for that. If you have scenario where last edit wins you should not have problems with this until somebody else deletes record which current user edits. Additionally after saving or cancelling changes you should dispose current context and load data again - this will ensure that you really have fresh data for next unit of work.
Context offers some features to refresh data but it only refreshes data previously loaded (without relations) so for example new unsaved records will be still included.
Perhaps you can also read about MS Sync framework and local data cache.
Sounds to me like your users could have a copy (cached) of the data for an indefinate period of time. The longer the users are using cached data the greater the odds that they could become disconnected from the database connection in DbContext. My guess is EF doesn't handle this well and you probably want to deal with that. (e.g. occaisionally connected architecture). I would expect implementing that may solve many of your issues.
Sorry about the title - hopefully the question will make clear what I want to know, then maybe someone can suggest a better title and I'll edit it!
We have a domain model. Part of this model is a collection of "Assets" that the user currently has. The user can then create "Actions" that are possible future changes to the state of these "Assets". At present, these actions have an "Apply" method and a reference to their associated "Asset". This "Apply" method makes a modification to the "Asset" and returns it.
At various points in the code, we need to pull back a list of assets with any future dated actions applied. However, we often need to do this within the scope of an NHibernate transaction and therefore when the transaction is committed the changes to the "Asset" will be saved as well - but we don't want them to be.
We've been through various ways of doing this
Cloning a version of the "Asset" (so that it is disconnected from Nhibernate) and then applying the "Action" and returning this cloned copy.
Actually using Nhibernate to disconnect the object before returning it
Obviously these each have various (massive!) downsides.
Any ideas? Let me know if this question requires further explanation and what on earth I should change the title to!
It's been a while since I had any NHibernate fun, but could you retrieve the Assets using a second NHibernate session? Changes made to the Asset will then not be saved when the transaction on the first session commits.
You could manage this with NHibernate using ISession.Evict(obj) or similar techniques, but honestly it sounds like you're missing a domain concept. I would model this as:
var asset = FetchAsset();
var proposedAsset = asset.ApplyActionsToClone();
The proposedAsset would be a clone of the original asset with the actions applied to it. This cloned object would be disconnected from NHibernate and therefore not persisted when the Unit of Work commits. If applying the actions is expensive, you could even do the following:
asset.ApplyProposedChanges(proposedAsset);
I have been working around a similar problem where performance was also an issue, thus it was not possible to re-load the aggregate using a secondary (perhaps stateless) session. And because the entities that needed to be changed "temporarily" where very complex, I could not easily clone them.
What I ended up with was "manually" rolling back the changes to what would be the assets in your case. It turned out to work well. We stored each action applied to the entity as a list of events (in memory that is). After use the events could be re-read and each change could be rolled back by a counter-action.
If it's only a small variety of actions that can be applied, I would say it's easily manageable to create a counter-action for each, or else it might be possible to create a more generic mechanism.
We had only four actions, so we went for the manual edition.
Sounds like you want to use a Unit of Work wrapper, so you can commit or revert changes as needed.