Introduction to Data Concurrency in ADO.NET

See Also

Responding to Database Update Errors| Optimistic Concurrency | DBConcurrencyException Class | Handling Concurrency Errors | Implementing Optimistic Concurrency with Dynamic SQL | Implementing Optimistic Concurrency with Stored Procedures

When multiple users attempt to modify data at the same time, controls need to be established in order to prevent one user's modifications from adversely affecting modifications from simultaneous users. The system of handling what happens in this situation is called concurrency control.

Types of Concurrency Control

In general, there are three common ways to manage concurrency in a database:

- Pessimistic concurrency control - a row is unavailable to users from the time the record is fetched until it is updated in the database.
- Optimistic concurrency control - a row is unavailable to other users only while the data is actually being updated. The update examines the row in the database and determines whether any changes have been made. Attempting to update a record that has already been changed results in a concurrency violation.
- "Last in wins" - a row is unavailable to other users only while the data is actually being updated. However, no effort is made to compare updates against the original record; the record is simply written out, potentially overwriting any changes made by other users since you last refreshed the records.

Pessimistic Concurrency

Pessimistic concurrency is typically used for two reasons. First, in some situations there is high contention for the same records. The cost of placing locks on the data is less than the cost of rolling back changes when concurrency conflicts occur.

Pessimistic concurrency is also useful for situations where it is detrimental for the record to change during the course of a transaction. A good example is an inventory application. Consider a company representative checking inventory for a potential customer. You typically want to lock the record until an order is generated, which would generally flag the item with a status of ordered and remove it from available inventory. If no order is generated, the lock would be released so that other users checking inventory get an accurate count of available inventory.

However, pessimistic concurrency control is not possible in a disconnected architecture. Connections are open only long enough to read the data or to update it, so locks cannot be sustained for long periods. Moreover, an application that holds onto locks for long periods is not scalable.

Note If your underlying data source supports transactions, you can simulate pessimistic concurrency by updating your data within a transaction. For more information, see Transactions in ADO.NET.

Optimistic Concurrency

In optimistic concurrency, locks are set and held only while the database is being accessed. The locks prevent other users from attempting to update records at the same instant. The data is always available except for the exact moment that an update is taking place. For more information, see Optimistic Concurrency.

When an update is attempted, the original version of a changed row is compared against the existing row in the database. If the two are different, the update fails with a concurrency error. It is up to you at that point to reconcile the two rows, using business logic that you create.

Last in Wins

With "last in wins," no check of the original data is made and the update is simply written to the database. It is understood that the following scenario can occur:

- User A fetches a record from the database.
- User B fetches the same record from the database, modifies it, and writes the updated record back to the database.
- User A modifies the 'old' record and writes it back to the database.

In the above scenario, the changes User B made were never seen by User A. Be sure that this situation is acceptable if you plan to use the "last in wins" approach of concurrency control.

Concurrency Control in ADO.NET and Visual Studio .NET

ADO.NET and Visual Studio .NET use optimistic concurrency, because the data architecture is based on disconnected data. Therefore, you need to add business logic to resolve issues with optimistic concurrency.

If you choose to use optimistic concurrency, there are two general ways to determine if changes have occurred: the version approach (true version numbers or date-time stamps) and the saving all values approach.

Version Number Approach

In the version number approach, the record to be updated must have a column that contains a date-time stamp or version number. The date-time stamp or a version number is saved on the client when the record is read. This value is then made part of the update.

One way to handle concurrency is to update only if value in the WHERE clause matches the value on the record. The SQL representation of this approach is:

UPDATE Table1 SET Column1 = @newvalue1, Column2 = @newvalue2

WHERE DateTimeStamp = @origDateTimeStamp

Alternatively, the comparison can be made using the version number:

UPDATE Table1 SET Column1 = @newvalue1, Column2 = @newvalue2

WHERE RowVersion = @origRowVersionValue

If the date-time stamps or version numbers match, the record in the data store has not changed and can be safely updated with the new values from the dataset. An error is returned if they don't match. You can write code to implement this form of concurrency checking in Visual Studio .NET. You will also have to write code to respond to any update conflicts. To keep the date-time stamp or version number accurate, you need to set up a trigger on the table to update it when a change to a row occurs.

Saving All Values Approach

An alternative to using a date-time stamp or version number is to get copies of all the fields when the record is read. The DataSet object in ADO.NET maintains two versions of each modified record: an original version (that was originally read from the data source) and a modified version, representing the user updates. When attempting to write the record back to the data source, the original values in the data row are compared against the record in the data source. If they match, it means that the database record has not changed since it was read. In that case, the changed values from the dataset are successfully written to the database.

Each data adapter command has a parameters collection for each of its four commands (DELETE, INSERT, SELECT, and UPDATE). Each command has parameters for both the original values, as well as the current (or modified) values.

Note Adding new records (the INSERT command) only requires the current values since no original record exists and removing records (the DELETE command) only requires the original values in order to locate the record to delete.

The following example shows the command text for a dataset command that updates a typical Customers table. The command is specified for dynamic SQL and optimistic concurrency.

UPDATE Customers SET CustomerID = @currCustomerID, CompanyName = @currCompanyName, ContactName = @currContactName,

ContactTitle = currContactTitle, Address = @currAddress, City = @currCity,

PostalCode = @currPostalCode, Phone = @currPhone, Fax = @currFax

WHERE (CustomerID = @origCustomerID) AND (Address = @origAddress OR @origAddress IS NULL AND Address IS NULL) AND (City = @origCity OR @origCity IS NULL AND City IS NULL)

AND (CompanyName = @origCompanyName OR @origCompanyName IS NULL AND CompanyName IS NULL) AND (ContactName = @origContactName OR @origContactName IS NULL AND ContactName IS NULL) AND (ContactTitle = @origContactTitle OR @origContactTitle IS NULL AND ContactTitle IS NULL)

AND (Fax = @origFax OR @origFax IS NULL AND Fax IS NULL) AND (Phone = @origPhone OR @origPhone IS NULL AND Phone IS NULL) AND (PostalCode = @origPostalCode OR @origPostalCode IS NULL AND PostalCode IS NULL);

SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address, City,

PostalCode, Phone, Fax

FROM Customers WHERE (CustomerID = @currCustomerID)

Note that the nine SET statement parameters represent the current values that will be written to the database, whereas the nine WHERE statement parameters represent the original values that are used to locate the original record.

The first nine parameters in the SET statement correspond to the first nine parameters in the parameters collection. These parameters would have their SourceVersion property set to Current.

The next nine parameters in the WHERE statement are used for optimistic concurrency. These placeholders would correspond to the next nine parameters in the parameters collection, and each of these parameters would have their SourceVersion property set to Original.

The SELECT statement is used to refresh the dataset after the update has occurred. It is generated when you set the Refresh the DataSet option in the Advanced SQL Generations Options dialog box.

Note The above SQL uses named parameters, whereas oleDbDataAdapter commands use question marks (?) as parameter placeholders.

By default Visual Studio will create these parameters for you if you select the Optimistic Currency option in the DataAdapter Configuration Wizard. It is up to you to add code to handle the errors based upon your own business requirements. ADO.NET provides a DBConcurrencyException object that returns the row that violates the concurrency rules. For more information, see Handling Concurrency Errors.

See Also

Responding to Database Update Errors| Optimistic Concurrency | DBConcurrencyException Class | Handling Concurrency Errors | Implementing Optimistic Concurrency with Dynamic SQL | Implementing Optimistic Concurrency with Stored Procedures