Auditing Data Changes in the Entity Framework: Part 2 – Simon Ince's Blog
This is how change tracking works when properties of a tracked entity are . Entity Framework uses a single value to record whether the properties stored inside. Here, you will learn how Entity Framework tracks changes on entities during their life time. Entity Framework supports automatic change tracking of the loaded. Entity Framework change tracking is often something that doesn't require too much thought from the app developer. However, change tracking.
Working With Change Tracking Proxy in Entity Framework
Here's how to do it, what's required to set it up, and some drawbacks of this method. Background Entity Framework tracks changes made to entities when those entities are loaded from the Context. So, if we load an entity and modify it, like so: Find 2 ; movie. SaveChanges When the call to SaveChanges is made, Entity Framework is aware of what values have changed, what the new values are, and what the original values are.
Change Tracking in Entity Framework
We need to access this information to accomplish the change tracking we want. Setup For this demo, let's assume we have the following entities and context: Implementing Change Tracking For this demo, we're going to store all changes made to any entity in a single data table. Said table can be represented by this entity: Part of recording "which entity changed" is both which table changed e.
In our implementation, we will need both of these for proper, thorough auditing. Performance of change-tracking proxies The Performance of change-tracking proxies may be both advantageous and disadvantageous. Performance depends on what we do with the entities.
Change-tracking proxies are more useful and provide good performance when many entities are being tracked and changes are made to some of them. In snapshot change tracking, the system needs to scan and compare all entities to detect changes. With change tracking proxies, every change is detected immediately without the scanning of entities.
Now consider just the reverse scenario. There are several changes being made on tracked entities. There is an extra cost of recording changes made on the entities in this case, so performance will be worse.
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- Change Tracking in Entity Framework
Assuming 16, sales order records, this bit of code would generate 32, queries to retrieve the child customers and orders. Yet the original code ran for more than 6 hours.
What happens is that processing starts fast, but then slowly starts slowing down, getting slower and slower as the loop count goes up. The first thought we had is that this was slow because of SQL, but checking the SQL Profiler logs it was easy to see that the queries were operating in the nearly immeasurable millisecond range even once the loop starts slowing down.
We could see however that the interval between database queries was increasing drastically.
Watch your DbContext and Change Tracking! In short the problem is dbContext bloat. In this case the context is getting bloated with a lot of records — and worse records that we have no intention of updating.
There are a few simple solutions to this problem: While the first instantiation of a large dbContext like the one used here can be very slow, subsequent instantiation is not. You should not be afraid to create multiple dbContexts or re-create an existing dbContext to provide isolation or clear out change state if you need it.
One other real issue with dbContext is that it has no way to clear out the change tree.