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Net, Part I, I briefly touched on the issue of currency errors and how ADO. In this article, we will focus on the different approaches to concurrency locking and discuss how you can handle the situations when they occur.Today's enterprise applications have one thing in common, multiple users accessing the system at the same time.Implementing your own application locks can be a challenging exercise, as well.In addition, you may need to provide a mechanism for reversing locks since it is very possible that someone may checkout a record and become unavailable for an extended period of time.On the other hand, one would consider pessimistic locking when the likelihood of a concurrency condition is high.This is usually true of management or workflow-oriented systems.In this type of scenario, you are bound to have users attempting to edit the same data at the same time, especially when there is a single data source associated with the application.This competition for data is known as a concurrency condition and can result in a lack of integrity in your database or worse, a loss of data. He is currently working on updating the payment terms associated with each of the customer accounts in the Widget Store Customer Database.
There are two basic approaches towards locking - optimistic and pessimistic.
Before or during an update, the application logic will check to see if the current record in the database has changed since you retrieved your copy of the record.
If it has, the app will generate an error causing the update transaction to be rolled back.
In optimistic locking, we allow multiple users to access the same record for edits, since we don't anticipate contention for data.
Here the "locking" happens after the user tries to save changes on top of someone else's changes.
Error: (09/12/2009 ) An error occurred when the request was processed on the remote computer.