Category: Locks, Blocks, and Deadlocks

Alexander Arvidsson diagnoses an interesting problem:

I ran this several times to see if there was a pattern to the madness, and it turned out it was. All waits were concentrated in database ID 2 – TEMPDB. Many people perk up by now and jump to the conclusion that this is your garden variety SGAM/PFS contention – easily remedied with more TEMPDB files and a trace flag. But, alas- this was further inside the TEMPDB. The output from the query above gave me the exact page number, and plugging that into DBCC PAGE gives the metadata object ID.

His conclusion is to reduce temp table usage and/or use memory-optimized tables.  We solved this problem with replacing temp tables with memory-optimized TVPs in our most frequently-used procedures.

Kendra Little explains some of the rules behind lock escalation, including which locks don’t cause escalation:

Books Online has a good article about this, which explains a lot of the details about how many locks you need to take out to trigger lock escalation. Here are the (simplified) basics:

• The ‘magic’ number to trigger escalation for the first time is 5,000 locks on a single table reference

• Locks do NOT escalate from row level to page level. Row locks escalate to table. Page level locks also escalate to table level. In other words, forcing row level locking will not make it less likely to escalate locks to the table level, but rather it will do the opposite.

  • Note: for partitioned tables, you have the option to enable partition level escalation

• If you’re modifying data, the escalated table lock will be exclusive. That means nobody else can party with the table if lock escalation succeeds while you’re doing your work.

Not all locks count, though, and Kendra has provided a test to show this.

Kenneth Fisher tells a story of a deadlock:

Why does it matter that they were system sessions? The important thing to remember here is that these sessions can not be KILLed. So because they were holding locks on the database (And somehow even though it was in single user there were multiple sessions with locks in the database. Don’t ask me how.) I wasn’t able to get that exclusive access I needed.

Interestingly when I tried to do the ALTER instead of just hanging I immediately got a deadlock error. I spent a little while trying various things and searching through forums before I went for help on twitter using the #SQLHELP hashtag.

Read on for the answer, including how deadlock priorities saved the day.

Michael Swart explains what the “monitorLoop” attribute is on the blocked process report:

You won’t find too much explanation about that field in the official documentation but I believe I know what it means.

The blocked process report is closely tied to deadlock detection and it’s generated by the same process as the deadlock monitor. If you remember, the deadlock monitor runs frequently looking for deadlocks (which are just blocking chains in a circle). It runs every couple seconds when there are no deadlocks, and if it detects any, it runs a bit more frequently. Each time it runs it’s called a monitor loop. The monitorLoop is just a number that starts at zero when the server restarts and increments by one each time the monitor runs.

Read on for more details.

Kenneth Fisher explains deadlock priority:

Everyone deals with deadlocks from time to time. But sometimes we need to control who’s the deadlock victim and who isn’t. For example, I’m doing a big delete on a table in a 24×7 environment, I can’t afford downtime to do it so I’m doing my delete in small chunks to reduce transaction size and blocking time. My delete needs to happen but I’m in no hurry and I really can’t afford to deadlock some other transaction. So how do I make sure?

Or on the other hand, I’m running an update that absolutely has to happen right now. It’s going to take a bit and I can’t afford the time for it to be started over. A deadlock would be a disaster. What do I do?

That’s where deadlock priority comes into play.

Click through for the explanation.

Kenneth Fisher talks about fullbacks:

Blocking is just part of life I’m afraid. Because we have locks (and yes we have to have them, and no, NOLOCK doesn’t avoid them) we will have blocking. Typically it’s going to be very brief and you won’t even notice it. But sometimes you get a query or two blocked for long enough to cause a problem. Even more rarely you end up with a long chain of blocked sessions. Session 100, 101, and 102 are blocked by 67 which is blocked by 82, which is blocked by … Well, you get the idea. It can be very difficult to scan through all of those blocked sessions to find the root cause. That one or two session(s) that are actually causing the problem. So to that end I’ve written the following query. Among other things it will return any lead blockers, how many sessions are actually being blocked by it, and the total amount of time those sessions have been waiting. It will also give you the last piece of code run by the that particular session. Although be aware that won’t always tell you exactly what code caused the blocking.

Click through for the script.

Robert Bishop explains some of the basics behind transaction isolation levels:

Lost Updates

It is possible for two or more transactions to modify the same row. While the subsequent transactions are reading the data, the 1^st transaction commits its changes. Then the subsequent transaction makes its changes and commits, thereby possibly losing the changes committed by the 1^st transaction. In this scenario, the last transaction always wins.

Dirty Read

A dirty read is when a SELECT statement will read against a table that is currently being modified and not yet committed to the database. By default, SQL Server will protect against this on all isolation levels, except for Read Uncommitted or by using NOLOCK in your queries.

This is the first in a series.

Kevin Sookocheff diagrams how to implement optimistic concurrency for a server which uses HTTP requests to handle resources like files:

A conditional request is a request that may be executed differently depending on the value of specific HTTP headers. These headers define the precondition that must be true before the server should execute the request. With respect to entity tags, we have two options for making requests conditional.

1. If-Match: The request will succeed if the ETag of the remote resource is equal to the one listed in this header.
2. If-None-Match: The request will succeed if the ETag of the remote resource is different to each listed in this header.

By specifying the appropriate ETag and condition header, you can perform optimistic locking for concurrent operations on a resource. Let’s walk through an example of how this works in practice.

Read on for more details.