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Jisun changes the product name to "Chai Tea" and clicks the Update button. At this point in time, the database has the values "Chai Tea," the category Beverages, the supplier Exotic Liquids, and so on for this particular product.

However, the Grid View on Sam's screen still shows the product name in the editable Grid View row as "Chai".

For example, imagine that two users, Jisun and Sam, were both visiting a page in our application that allowed visitors to update and delete the products through a Grid View control.

Both click the Edit button in the Grid View around the same time.

For example, if a user locks a record for editing and then leaves for the day before unlocking it, no other user will be able to update that record until the original user returns and completes his update.

Therefore, in situations where pessimistic concurrency is used, there's typically a timeout that, if reached, cancels the lock.

The , that DB direct methods were those that accepts a list of scalar values as input parameters (rather than a strongly-typed Data Row or Data Table instance).

Or, between when a user loads a page and when they click the Delete button, another user may have modified the contents of that record.

Figure 4: Specify the Data to Retrieve Using an Ad-Hoc SQL Statement (Click to view full-size image) On the following screen, enter the SQL query to use to retrieve the product information. Discontinued = discontinued End Sub _ Public Function Update Product( By Val product Name As String, By Val supplier ID As Nullable(Of Integer), _ By Val category ID As Nullable(Of Integer), By Val quantity Per Unit As String, _ By Val unit Price As Nullable(Of Decimal), By Val units In Stock As Nullable(Of Short), _ By Val units On Order As Nullable(Of Short), By Val reorder Level As Nullable(Of Short), _ By Val discontinued As Boolean, By Val product ID As Integer, _ _ By Val original_product Name As String, _ By Val original_supplier ID As Nullable(Of Integer), _ By Val original_category ID As Nullable(Of Integer), _ By Val original_quantity Per Unit As String, _ By Val original_unit Price As Nullable(Of Decimal), _ By Val original_units In Stock As Nullable(Of Short), _ By Val original_units On Order As Nullable(Of Short), _ By Val original_reorder Level As Nullable(Of Short), _ By Val original_discontinued As Boolean, _ By Val original_product ID As Integer) _ As Boolean ' STEP 1: Read in the current database product information Dim products As _ Northwind Optimistic Concurrency.

Let's use the exact same SQL query used for the SELECT Product ID, Product Name, Supplier ID, Category ID, Quantity Per Unit, Unit Price, Units In Stock, Units On Order, Reorder Level, Discontinued, (SELECT Category Name FROM Categories WHERE Categories. Category ID) as Category Name, (SELECT Company Name FROM Suppliers WHERE Suppliers. Supplier ID) as Supplier Name FROM Products Table Adapter in the Original DAL (Click to view full-size image) Before moving onto the next screen, click the Advanced Options button. Products Optimistic Concurrency Data Table = _ Adapter.

Rather than extend our existing DAL's Table Adapters to use optimistic concurrency (which would necessitate changing the BLL to accommodate), let's instead create a new Typed Data Set named Business Logic Layer class that has the appropriate modifications to support the optimistic concurrency DAL.

Once this groundwork has been laid, we'll be ready to create the ASP. To create a new Typed Data Set, right-click on the .

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