SQL Server Deadlocks

Understanding and Avoiding Them

Deadlocks are a common problem in all relational database systems that can lead to poor performance and even data loss (in some special cases). A deadlock occurs when two or more transactions are waiting for each other to release a resource, such as a database row or page, that they both need to complete their work. Process A is waiting on process B and process B is waiting on process A – we have a deadlock!

SQL Server has a built-in mechanism to detect deadlocks and resolve them automatically. When a deadlock is detected, SQL Server chooses one of the transactions as a victim and rolls it back, allowing the other transactions to proceed. However, this can result in lost work and inconsistent data.

To avoid deadlocks, it’s important to understand the conditions that can lead to them. One common cause is locking too many resources for too long. For example, if one transaction locks a row and then tries to lock another row that is already locked by another transaction, a deadlock can occur. To prevent this, it’s important to use the smallest possible scope for locking, such as row-level locking instead of page-level or table-level locking. (this can also be caused by lock-escalation)

In addition, it’s important to keep transactions as short as possible to minimize the time that resources are locked. This can be achieved by breaking long transactions into smaller ones, by releasing locks as soon as they are no longer needed, adding indexing which can cause transactions to complete quickly or even taking locks early in a transaction that you know will be locked later in a multi-statement transaction.

Vroom Performance Suite provides comprehensive tracking and analysis of deadlocks. These tools can help identify the transactions and resources involved in a deadlock, and provide insights into how to prevent them from occurring in the future.

Want some more details?

Ok, you asked!

Deadlocks occur when two or more transactions are waiting for each other to release a resource, such as a database row or page, that they both need to complete their work.

The cause of a deadlock can typically be traced back to two main factors: resource contention and inconsistent locking.

Resource contention

Resource contention occurs when multiple transactions are attempting to access the same resource at the same time. For example, if one transaction has locked a row and then tries to lock another row that is already locked by another transaction, a deadlock can occur. This is because each transaction is waiting for the other to release the locked resource, resulting in a circular waiting pattern.

Inconsistent locking

Inconsistent locking occurs when transactions acquire locks in a different order. For example, if transaction A locks resource X and then tries to lock resource Y, while transaction B locks resource Y and then tries to lock resource X, a deadlock can occur. This is because both transactions are waiting for the other to release the resource that they need to proceed, resulting in a circular waiting pattern.

It’s important to note that deadlocks can also occur due to other factors such as long-running transactions or lock timeouts, but resource contention and inconsistent locking are the most common causes. To prevent deadlocks, it’s important to use appropriate locking strategies, establish consistent lock ordering, and keep transactions as short as possible. Additionally, monitoring and troubleshooting tools can help identify and resolve deadlocks in SQL Server.

Want to mitigate deadlocks?

Use appropriate locking strategies: Use the smallest possible scope for locking, such as row-level locking instead of page-level or table-level locking. Avoid using excessive locking hints like NOLOCK or READ UNCOMMITTED that can increase the likelihood of deadlocks.

Keep transactions as short as possible: Break long transactions into smaller ones and release locks as soon as they are no longer needed to minimize the time that resources are locked.

Monitor and troubleshoot deadlocks: These tools can help identify the transactions and resources involved in a deadlock, and can provide insights into how to prevent them from occurring in the future.

Use isolation levels appropriately: Use the appropriate isolation level for each transaction to balance concurrency and consistency. For example, if you need high concurrency, you might consider using the READ COMMITTED SNAPSHOT isolation level instead of the default READ COMMITTED isolation level.

Consider enabling READ_COMMITTED_SNAPSHOT. This allows multiple transactions to access and update the same resource concurrently without blocking each other.

Should I do any deep dives on these strategies? Let me know, I’d be happy to dig in!