What is Concurrency in SQL Server? What are the different Concurrency Problems?

What is Concurrency in SQL Server?

When we talk about transactions, one more thing which we need to handle is concurrency. Concurrency is nothing but is a situation where two users are trying to access the same information and while they are accessing the same information we do not want any kind of inconsistency result or abnormal behavior.

Databases are powerful systems and are potentially used by many users or applications at the same time. Allowing concurrent transactions is essential for performance but may introduce concurrency issues when two or more transactions are working with the same data at the same time.

Some of the common concurrency problems

• Dirty Reads
• Lost Updates
• Nonrepeatable Reads
• Phantom Reads

One way to solve all these concurrency problems is by allowing only one user to execute, only one transaction at any point in time. Imagine what could happen if you have a large database with several users who want to execute several transactions. All the transactions get queued and they may have to wait a long time before they could get a chance to execute their transactions. So you are getting poor performance and the whole purpose of having a powerful database system is defeated if you serialize access this way.

At this point you might be thinking, for best performance let us allow all transactions to execute concurrently. The problem with this approach is that it may cause all sorts of concurrency problems (i.e Dirty Reads, Lost Updates, Nonrepeatable Reads, Phantom Reads) if two or more transactions work with the same data at the same time.

1. Dirty Reads

A dirty read happens when one transaction is permitted to read data that has been modified by another transaction that has not yet been committed. In most cases this would not cause a problem. However, if the first transaction is rolled back after the second reads the data, the second transaction has dirty data that does not exist anymore.

Dirty Read Example : In the example below, Transaction 1, updates the value of ItemsInStock to 9. Then it starts to bill the customer. While Transaction 1 is still in progress, Transaction 2 starts and reads ItemsInStock value which is 9 at the moment. At this point, Transaction 1 fails because of insufficient funds and is rolled back. The ItemsInStock is reverted to the original value of 10, but Transaction 2 is working with a different value (i.e 10).



Transaction 1 : 
Begin Tran

Update tblInventory set ItemsInStock = 9 where Id=1

-- Billing the customer

Waitfor Delay '00:00:15'

-- Insufficient Funds. Rollback transaction

Rollback Transaction

Transaction 2 :

Set Transaction Isolation Level Read Uncommitted

Select * from tblInventory where Id=1

Read Uncommitted transaction isolation level is the only isolation level that has dirty read side effect. This is the least restrictive of all the isolation levels. When this transaction isolation level is set, it is possible to read uncommitted or dirty data. Another option to read dirty data is by using NOLOCK table hint. The query below is equivalent to the query in Transaction 2.

Select * from tblInventory (NOLOCK) where Id=1

2. Lost Updates

Lost update problem happens when 2 transactions read and update the same data. Let's understand this with an example. We will use the following table tblInventory for this example.



As you can see in the diagram below there are 2 transactions - Transaction 1 and Transaction 2. Transaction 1 starts first, and it is processing an order for 1 iPhone. It sees ItemsInStock as 10.

At this time Transaction 2 is processing another order for 2 iPhones. It also sees ItemsInStock as 10. Transaction 2 makes the sale first and updates ItemsInStock with a value of 8.

At this point Transaction 1 completes the sale and silently overwrites the update of Transaction 2. As Transaction 1 sold 1 iPhone it has updated ItemsInStock to 9, while it actually should have updated it to 7.



Example : The lost update problem example. Open 2 instances of SQL Server Management studio. From the first window execute Transaction 1 code and from the second window, execute Transaction 2 code. Transaction 1 is processing an order for 1 iPhone, while Transaction 2 is processing an order for 2 iPhones. At the end of both the transactions ItemsInStock must be 7, but we have a value of 9. This is because Transaction 1 silently overwrites the update of Transaction 2. This is called the lost update problem.

-- Transaction 1

Begin Tran

Declare @ItemsInStock int

Select @ItemsInStock = ItemsInStock

from tblInventory where Id=1

-- Transaction takes 10 seconds

Waitfor Delay '00:00:10'

Set @ItemsInStock = @ItemsInStock - 1

Update tblInventory

Set ItemsInStock = @ItemsInStock where Id=1

Print @ItemsInStock

Commit Transaction

-- Transaction 2

Begin Tran

Declare @ItemsInStock int

Select @ItemsInStock = ItemsInStock

from tblInventory where Id=1

-- Transaction takes 1 second

Waitfor Delay '00:00:1'

Set @ItemsInStock = @ItemsInStock - 2

Update tblInventory

Set ItemsInStock = @ItemsInStock where Id=1

Print @ItemsInStock

Commit Transaction

Both Read Uncommitted and Read Committed transaction isolation levels have the lost update side effect. Repeatable Read, Snapshot, and Serializable isolation levels does not have this side effect. If you run the above Transactions using any of the higher isolation levels (Repeatable Read, Snapshot, or Serializable) you will not have lost update problem. The repeatable read isolation level uses additional locking on rows that are read by the current transaction, and prevents them from being updated or deleted elsewhere. This solves the lost update problem.



For both the above transactions, set Repeatable Read Isolation Level. Run Transaction 1 first and then a few seconds later run Transaction 2. Transaction 1 completes successfully, but Transaction 2 competes with the following error.
Transaction was deadlocked on lock resources with another process and has been chosen as the deadlock victim. Rerun the transaction.

3. Nonrepeatable Reads
Non repeatable read problem happens when one transaction reads the same data twice and another transaction updates that data in between the first and second read of transaction one. 

We will use the following table tblInventory in this demo


The following diagram explains the problem : Transaction 1 starts first. Reads ItemsInStock. Gets a value of 10 for first read. Transaction 1 is doing some work and at this point Transaction 2 starts and UpdatesItemsInStock to 5. Transaction 1 then makes a second read. At this point Transaction 1 gets a value of 5, reulting in non-repeatable read problem.



Non-repeatable read example : Open 2 instances of SQL Server Management studio. From the first window execute Transaction 1 code and from the second window, execute Transaction 2 code. Notice that when Transaction 1 completes, it gets different values for read 1 and read 2, resulting in non-repeatable read.

-- Transaction 1

Begin Transaction

Select ItemsInStock from tblInventory where Id = 1

-- Do Some work

waitfor delay '00:00:10'

Select ItemsInStock from tblInventory where Id = 1

Commit Transaction

-- Transaction 2

Update tblInventory set ItemsInStock = 5 where Id = 1

Repeatable read or any other higher isolation level should solve the non-repeatable read problem.


Fixing non repeatable read concurrency problem : To fix the non-repeatable read problem, set transaction isolation level of Transaction 1 to repeatable read. This will ensure that the data that Transaction 1 has read, will be prevented from being updated or deleted elsewhere. This solves the non-repeatable read problem. 

When you execute Transaction 1 and 2 from 2 different instances of SQL Server management studio, Transaction 2 is blocked until Transaction 1 completes and at the end of Transaction 1, both the reads get the same value for ItemsInStock.

-- Transaction 1

Set transaction isolation level repeatable read

Begin Transaction

Select ItemsInStock from tblInventory where Id = 1

-- Do Some work

waitfor delay '00:00:10'

Select ItemsInStock from tblInventory where Id = 1

Commit Transaction

-- Transaction 2

Update tblInventory set ItemsInStock = 5 where Id = 1

4. Phantom Reads

Phantom read happens when one transaction executes a query twice and it gets a different number of rows in the result set each time. This happens when a second transaction inserts a new row that matches the WHERE clause of the query executed by the first transaction.

We will use the following table tblEmployees in this demo

Scrip to create the table tblEmployees

Create table tblEmployees

(

    Id int primary key,

    Name nvarchar(50)

)

Go

Insert into tblEmployees values(1,'Mark')

Insert into tblEmployees values(3, 'Sara')

Insert into tblEmployees values(100, 'Mary')

The following diagram explains the problem : Transaction 1 starts first. Reads from Emp table where Id between 1 and 3. 2 rows retrieved for first read. Transaction 1 is doing some work and at this point Transaction 2 starts and inserts a new employee with Id = 2. Transaction 1 then makes a second read. 3 rows retrieved for second read, reulting in phantom read problem.



Phantom read example : Open 2 instances of SQL Server Management studio. From the first window execute Transaction 1 code and from the second window, execute Transaction 2 code. Notice that when Transaction 1 completes, it gets different number of rows for read 1 and read 2, resulting in phantom read.

-- Transaction 1

Begin Transaction

Select * from tblEmployees where Id between 1 and 3

-- Do Some work

waitfor delay '00:00:10'

Select * from tblEmployees where Id between 1 and 3

Commit Transaction

-- Transaction 2

Insert into tblEmployees values(2, 'Marcus')

Serializable or any other higher isolation level should solve the phantom read problem.


Fixing phantom read concurrency problem : To fix the phantom read problem, set transaction isolation level of Transaction 1 to serializable. This will place a range lock on the rows between 1 and 3, which prevents any other transaction from inserting new rows with in that range. This solves the phantom read problem. 

When you execute Transaction 1 and 2 from 2 different instances of SQL Server management studio, Transaction 2 is blocked until Transaction 1 completes and at the end of Transaction 1, both the reads get the same number of rows.

-- Transaction 1

Set transaction isolation level serializable

Begin Transaction

Select * from tblEmployees where Id between 1 and 3

-- Do Some work

waitfor delay '00:00:10'

Select * from tblEmployees where Id between 1 and 3

Commit Transaction

-- Transaction 2

Insert into tblEmployees values(2, 'Marcus')