This step of the VIDEO TUTORIAL will show case a series of steps on how to implement optimistic concurrency in web applications. In many web applications, there will be instances where two users who have similar roles, may concurrently work on a single record. Under these circumstances, how to save one user’s changes to the database and alert the other user about these database changes will be an important implementation challenge. This first step of this video tutorial series will look at on how to implement optimistic concurrency and what triggers an optimistic concurrency violation or exception. For detailed information and source code for this step, please refer to the original article.

This step of the VIDEO TUTORIAL will outline the strategy to implement optimistic concurrency in the Data Tutorials project under consideration by creating a separate data access layer that supports optimistic concurrency. This is accomplished by creating a new typed dataset named NorthwindOptimisticConcurrency to the App_Code folder. A new Products Table Adapter is created using the Table Adapter Query Configuration wizard that supports optimistic concurrency features and is named as ProductsOptimisticConcurrency table adapter and is added to the newly created typed dataset. In addition FillByProductId( ) and GetProductByProductId( ) are also added to this new table adapter. For detailed information and source code for this step, please refer to the original article.

This step of the VIDEO TUTORIAL will demonstrate on how to create a business logic layer that will become a wrap around the newly created data access layer in the previous step that supports the optimistic concurrency features. This is achieved by adding a new class file to the App_Code’s BLL folder titled as ProdutsOptimisticConcurrencyBLL.cs. A Delete and Update overload methods that take the optimistic concurrency features into consideration also added to the newly created ProductsOptimisticConcurrency table adapter. In addition, two patterns known as DBDirect as well as DB Batch Patterns are examined in deleting and updating product tables in the database. For detailed information and source code for this step, please refer to the original article.