Updating records in dataset

The effect you will see is that the fields are left blank, which is not very helpful because you don't know which record has been deleted. This means there are no controls to prevent two users from editing the same record at the same time.

(This was not the behavior in the first version of ADOExpress, which displayed the field values of deleted records.) The ingenuity you need in order to solve the function ADOUpdates Pending(ADOData Set: TCustom ADOData Set): boolean; var Clone: TADOData Set; begin Clone := TADOData Set. The first user to save their changes will succeed; the second user's attempt to update the same record might fail.

One such status is fg Pending Records, which includes all records that have been modified but not yet applied. As such, the attitude is that all users can edit any record at any time, and you deal with the consequences of conflicts between different users' updates to the same records when the changes are saved.

So, to allow the user to look through all the changes they have made so far, you need only execute two lines: Naturally, the result set will now include the records that have been deleted. Thus, conflicts are considered an exception to the rule.

In an ADO join, each field object knows which underlying table it belongs to.

If you update a field in the Products table and post the change, then a SQL statements are generated, one for each table.

You can specify that deletes refer to just the Products table and not to Suppliers using the following line of code: When you use batch updates, any changes you make to your records can be made in memory; later, the entire "batch" of changes can be submitted as one operation.

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This approach is particularly useful for highlighting records in different colors in a grid or showing their status on a status bar.Updates Pending then Can Close := (Message Dlg('Updates are still pending' #13 'Close anyway? In this section, we'll look at optimistic locking, not only because it is the preferred locking type for medium- to high-throughput transactions, but also because it is the locking scheme employed by batch updates.', mt Confirmation, [mb Yes, mb No], 0) = mr Yes); end; filters based on the status of the record. Optimistic locking assumes there is a low probability that users will attempt to update the same records at the same time and that a conflict is unlikely.For example, the Join Data example is built around an ADODataset component that uses the previous SQL join.If you run it, you can edit one of the fields and save the changes (by moving off the record).This behavior is essential for briefcase applications (discussed later in the chapter) and web applications, where there is no permanent connection to the database and, therefore, no way to implement pessimistic locking.In contrast with pessimistic locking, optimistic locking has the additional considerable benefit that resources are consumed only momentarily; therefore, the average resource usage is much lower, making the database more scalable. Assume you have an ADOData Set connected to the Customer table of the .This would be the case in a briefcase application (which we will return to in the section "The Briefcase Model"), but it can also be the case in web applications that use another ADO technology, Remote Data Services (RDS).You can enable batch updates in any ADO dataset by setting to cl Use Client, because batch updates are managed by ADO's cursor engine.Run the program twice (it is the Batch Updates example if you don't want to rebuild it) and begin editing a record in the first copy of the program.Although for the sake of simplicity I'll demonstrate a conflict using just a single machine, the scenario and subsequent events are unchanged when using multiple machines: As with many ADO error messages, the exact message you receive will depend not only on the version of ADO you are using but also on how closely you followed the example.

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