6 Ways of Doing Locking in .NET (Pessimistic and Optimistic)

Introduction

This article talks about 6 ways of locking in. NET. It starts with concurrency problems and then discusses 3 ways of doing optimistic locking. As optimistic locking does not solve the concurrency issues from roots, it introduces pessimistic locking. It then moves ahead to explain how isolation levels can help us implement pessimistic locking. Each isolation level is explained with a sample demonstration to make concepts clearer.

This is a small Ebook for all my .NET friends which covers topics like WCF, WPF, WWF, Ajax, Core .NET, SQL, Entity Framework, Design patterns, Agile, etc you can download the same from here, or else you can catch me on my daily free training @ from here

Why do we need locking?

In a multi-user environment, it's possible that multiple users can update the same record at the same time causing confusion between users. This issue is termed concurrency.

How can we solve concurrency problems?

Concurrency problems can be solved by implementing a proper "Locking strategy". Locks prevent action on a resource from being performed when some other resource is already performing some action on it.

What kind of confusion is caused by concurrency?

There are 4 kinds of major problems caused because of concurrency, the table below shows the details.

So how can we solve the above problems?

By using optimistic or pessimistic locking, this article discusses the same.

What is Optimistic locking?

As the name suggests "optimistic" assumes that multiple transactions will work without affecting each other. In other words, no locks are enforced while doing optimistic locking. The transaction just verifies that no other transaction has modified the data. In case of modification, the transaction is rolled back.

How does optimistic lock work?

You can implement optimistic locking in numerous ways but the fundamentals of implementing optimistic locking remain the same. It's a 5 step process as shown below.

• Record the current timestamp.
• Start changing the values.
• Before updating check whether anyone else has changed the values by checking the old time stamp and new timestamp.
• If it's not equal rollbacks or else commits.

What are the different solutions by which we can implement optimistic locking?

There are 3 primary ways by which we can implement optimistic locking-in. NET.

• Datasets: Datasets by default implement optimistic locking. They do a check of old values and new values before updating.
• Timestamp Data type: Create a timestamp data type in your table and while updating check if the old timestamp is equal to the new timestamp.
• Check old and new values: Fetch the values, make the changes and while doing the final updates check if the old value and current values in the database are equal. If they are not equal then rollback or else commit the values.

Solution number 1. Datasets

As said in the previous section, the dataset handles optimistic concurrency by itself. Below is a simple snapshot where we held the debug point on the Adapter's update function and then changed the value from the SQL Server. When we ran the "update" function by removing the breakpoint it threw a "Concurrency" exception error as shown below.

If you run the profiler at the back end you can see it fires the update statement checking the current values and the old values are then the same.

EXEC sp_executesql N'
    UPDATE [tbl_items] 
    SET [AuthorName] = @p1 
    WHERE (
        [Id] = @p2 
        AND ((@p3 = 1 AND [ItemName] IS NULL) OR ([ItemName] = @p4))
        AND ((@p5 = 1 AND [Type] IS NULL) OR ([Type] = @p6))
        AND ((@p7 = 1 AND [AuthorName] IS NULL) OR ([AuthorName] = @p8))
        AND ((@p9 = 1 AND [Vendor] IS NULL) OR ([Vendor] = @p10))
    )',
    N'
    @p1 nvarchar(11), 
    @p2 int, 
    @p3 int, 
    @p4 nvarchar(4), 
    @p5 int, 
    @p6 int, 
    @p7 int, 
    @p8 nvarchar(18), 
    @p9 int, 
    @p10 nvarchar(2)
    ',
    @p1 = N'this is new',
    @p2 = 2,
    @p3 = 0,
    @p4 = N'1001',
    @p5 = 0,
    @p6 = 3,
    @p7 = 0,
    @p8 = N'This is Old Author',
    @p9 = 0,
    @p10 = N'kk'

In this scenario we were trying to change the field value "AuthorName" to "This is new" but while updating it makes a check with the old value "This is the old author". Below is the downsized code snippet of the above SQL which shows the comparison with the old value.

,@p8 = N'This is Old Author'

Solution number 2. Use timestamp data type

The other way of doing optimistic locking is by using the 'TimeStamp' data type of SQL Server. Timestamp automatically generates a unique binary number every time you update the SQL Server data. Timestamp data types are for versioning your record updates.

To implement optimistic locking we first fetch the old 'TimeStamp' value and when we are trying to update we check if the old timestamp is equal to the current time stamp as shown in the below code snippet.

UPDATE tbl_items
SET itemname = @itemname
WHERE CurrentTimestamp = @OldTimeStamp

We then check if any updates have happened, in case updates have not happened then we raise a serious error '16' using SQL Server 'raise error' as shown in the below code snippet.

IF (@@ROWCOUNT = 0)
BEGIN
    RAISEERROR('Hello some else changed the value', 16, 10)
END

If any concurrency violation takes place you should see the error propagated when you call 'ExecuteNonQuery' to the client side as shown in the below figure.

Solution number 3. Check old values and new values

Many times we would like to check concurrency on only certain fields and omit fields like identity etc. For that kind of scenario, we can check the old value and the new value of the updated fields as shown in the below code snippet.

UPDATE tbl_items 
SET itemname = @itemname 
WHERE itemname = @OldItemNameValue

But it looks like by using optimistic locking concurrency problems are not really solved.

Yes, you said right. By using optimistic locking you only detect the concurrency problem. To solve concurrency issues from the roots themselves we need to use pessimistic locking. Optimistic is like prevention while pessimistic locking is actually the cure.

What is pessimistic locking?

Pessimistic locking assumes that concurrency/collision issues will happen so a lock is placed on the records and then data is updated.

How can we do pessimistic locking?

We can do pessimistic locking by specifying "IsolationLevel" in SQL Server stored procedures, ADO.NET level, or by using transaction scope object.

What kind of locks can be acquired by using pessimistic locking?

There are 4 kinds of locks you can acquire Shared, Exclusive, Update, and intent. The first two are actual locks while the other two are hybrid locks and markers.