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Category: Locks, Blocks, and Deadlocks

A Primer on Locking and Deadlocks

John McCormack explains locks and deadlocks:

Blocking is the real world impact of locks being taken on resources and other lock types being requested which are incompatible with the existing lock. You need to have locks in order to have blocking. In the scenario where a row is being updated, the lock type of IX or X means that a simultaneous read operation will be blocked until the data modification lock has been released. Similarly, data being read blocks data from being modified. Again, there are exceptions to these based on the isolation level used.

Blocking then is a perfectly natural occurrence within SQL Server. In fact, it is vital to maintain ACID transactions. On a well optimised system, it can be hard to notice and doesn’t cause problems.

All things in moderation, even blocking.

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Use a Separate Deadlock Extended Events Trace

Kendra Little explains why it makes sense to have an extended events trace specifically for deadlocks:

We recently had customer ask why SQL Monitor creates an Extended Events session to capture deadlock graphs, when SQL Server has a built-in system_health Extended Events trace which also captures deadlock information?

There are a couple of reasons why a dedicated trace is desirable for capturing deadlock graphs, whether you are rolling your own monitoring scripts or building a monitoring application. I like this question a lot because I feel it gets at an interesting tension/balance at the heart of monitoring itself.

Click through for the answer.

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Preventing Deadlocks on Key Lookups

Erik Darling talks about key lookups:

I go back and forth when it comes to Lookups.

On the one hand, I don’t think the optimizer uses them enough. There are times when hinting a nonclustered index, or re-writing a query to get it to use a nonclustered index can really help performance.

On the other hand, they can really exacerbate parameter sniffing problems, and can even lead to read queries blocking write queries. And quite often, they lead to people creating very wide indexes to make sure particular queries are covered.

Read on for one scenario around deadlocking due to key lookups.

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Detecting Spinlock Contention in SQL Server

Michael J. Swart walks us through spinlock contention:

When that occurred, the number of batch requests that the server could handle dropped significantly. So we saw more CPU use, but less work was getting done.

The high demand kept the CPU at 100% with no relief until the demand decreased. When that happened, the database seemed to recover. Throughput was restored and the database’s metrics became healthy again. During this trouble we looked at everything including the number of spins reported in the sys.dm_os_spinlock_stats dmv.

The spins and backoffs reported seemed extremely high, especially for the category “XVB_LIST”, but we didn’t really have a baseline to tell whether those numbers were problematic. Even after capturing the numbers and visualizing them we saw larger than linear increases as demand increased, but were those increases excessive?

Read on for the answer.

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When Altering a Table Blocks the Log Reader

Aaron Bertrand walks us through a painful scenario:

We recently performed a DDL operation against a SQL Server table – simply increasing the size of a varchar column – which should have been instantaneous. Instead, we killed the SQL Server process after observing 20 minutes of HARD_SYNC_COMMIT waits and a blocked replication log reader. Could this issue have been avoided? What went wrong?

I spotted the issue pretty quickly, but it’s easy to miss in a code review. Read the whole thing.

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Latching in SQL Server

Dan Jackson explains the concept of latching in SQL Server:

To start with, a basic definition: ‘Latches are lightweight synchronization objects, that are used by the storage engine of SQL Server to protect the internal memory structures’. Compare this with locks in SQL server, which are a transaction level construct to manage concurrency, latches work at the thread level to maintain data integrity within the internal memory structures. They are not exposed outside of the SQL Server Operating System (SQLOS). They are only managed by SQL Server itself, not by users (unlike locks that can be overridden via lock hints or changing isolation level). It is useful to keep in mind that a single transaction can use multiple threads at the same time.

Latching is a funny concept to me, in that I think people say “This must be a latching problem” far more than there actually is, but when there is a proper latching problem, it usually winds up being a pretty big deal.

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Locks in SQL Server

Dan Jackson provides us a primer on how SQL Server implements locking:

We have all heard of locks and can probably even name a few; shared or exclusive locks, for example. We notice them more when something goes wrong and we run into blocking or other performance problems, but what are locks and how do they work in SQL Server?

In this blog, I aim to give a basic answer to that question and provide you with an overview of the different lock modes in SQL Server and how it all works…

Let us make it clear from the off; locks are an essential part of SQL Server. In a multi-user system, there will be many users who wish to access the same resources at the same time. This means that SQL Server must have measures in place to handle concurrency and prevent adverse side effects. Locking is one of those measures.

Read the whole thing.

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