Paul’s process gives you info on every instance of a wait the query experienced and it’s very easy to aggregate those results to see the top waits and their total effect on a query. Quite often though, you don’t need a lot of detail. You don’t need to know every wait, just the top several. If you are already generating the actual query plan to have a in-depth look at the plan, wouldn’t it be nice if the query wait stats were already in there for you?
Now they are. In SQL Server 2016 (I’m told it came in SP1, but I don’t have a non-SP1 instance to verify that), the actual execution plan includes the top waits for the query execution in the plan. You can see them by clicking on the left-most (first) operator in the plan and viewing the Properties (shortcut F4). It will list the top waits right there in the properties dialog for you.
Getting single-query wait stats in the execution plan makes life so much simpler.
Last week I was sent an email question about the cause of LOGMGR_RESERVE_APPEND waits, and in Monday’s Insider newsletter I wrote a short explanation. It’s a very unusual wait to see as the highest wait on a server, and in fact it’s very unusual to see it at all.
It happens when a thread is generating a log record and needs to write it into a log block, but there’s no space in the log to do so. The thread first tries to grow the log, and if it fails, and the database is in the simple recovery mode, then it waits for 1 second to see if log clearing/truncation can happen in the meantime and free up some space. (Note that when I say ‘simple recovery mode’, this also included a database in full or bulk_logged, but where a full backup has not been taken – i.e. the database is operating in what’s called pseudo-simple.)
Read on for more details and a repro script.
This tells me about the waits since my last reboot or since a manual reset of the stats. It’s probably why you should do at least time-based analysis or reset the wait stats before starting, that is if you are interested in something time specific or if you want to understand certain workloads at a given time.
So the other option is that you could go down the session level route. With the session based analysis I took the query and changed it slightly to query sys.dm_exec_session_waits_stats and also pull back the session_id that I am interested in.
I had no idea this was available, and it’s something that I’ve wanted for a very long time, so that’s excellent.
Wait Stats is my “go-to” thing, when you want to dig into performance issues everyone knows you will probably end up using sys.dm_os_wait_stats. You cannot use this in the Azure world, you have to use a DMV that is scoped to the database level. I think this would be a nice idea to have with the “earth” based SQL Servers – the ability to return information about all the waits encountered by threads that executed at the database level.
The connect item can be found at this link: https://connect.microsoft.com/SQLServer/feedback/details/2647332/sys-dm-db-wait-stats-dmv?tduid=(262281c4c73a682498780643b77e80d1)(256380)(2459594)(TnL5HPStwNw-KjxCoz0pGWobbq7q1MQTIw)()
I like this idea.
In this case I was looking for PREEMPTIVE_COM_RELEASE, and sys.dm_xe_map_values tells me that on my 2014 RTM instance it has an index of 01d4 hexadecimal. Crazy as it sounds, I’m going to do a simple search through the code to look for places that magic number is used. As a two-byte (word) pattern we’ll get lots of false positives, but fortunately wait types are internally doublewords, with only one bit set in the high-order word. In other words, we’re going to look for the pattern 000101d4, 000201d4, 000401d4 and so forth up to 800001d4. Ignore the meaning of when which bit is going to be set; with only sixteen permutations, it’s quick enough to try them all.
Let’s focus on sqllang as the likely source – the below would apply to any other module too.
This post reminds me that my debugger skills aren’t very good.
So here are two different ways that we can use SQL Servers wait statistics for troubleshooting purposes. Both views give us really useful information but both have different purposes. If we wanted to look back over time then the sys.dm_os_wait_stats will give us a view of wait time totals. Typically we would capture the information via a scheduled job and analyse the data for spikes during periods where issues might be suspected.
For performing real-time analysis of wait statistics then we should base queries on the sys.dm_os_waiting_tasks view where we can see accurate wait duration values as they are happening within our instance.
In my opinion wait statistics are the most important piece of information when troubleshooting SQL Server so learning about the different types is vital for anyone using SQL. Thankfully there is a wealth of really useful information about wait statistics out there; I’ve listed some of my favourite posts below.
Click through for an example, as well as links to more resources.
With an instance of SQL Server regardless of using IaaS or on-premise, you would want to focus on all the waits that are occurring in your instance because the resources are dedicated to you.
In database as a service (DaaS), Microsoft gives you a special DMV that makes troubleshooting performance in Azure easier than any other competitor. This feature is the dm_db_wait_stats DMV. This DMV allows us specifically to get the details behind why our queries are waiting within our database and not the shared environment. Once again it is worth repeating, wait statistics for our database in a shared environment.
Click through for a stored procedure John has provided to collect wait stats in a Waits schema.
I do love wait stats!
If you listened to the performance tuning methodology I outlined in an earlier episode, you saw how important I think wait stats are for troubleshooting performance.
If you missed that episode, it’s called Lost in Performance Tuning. (I’ve got an outline of the discussion in the blog post, as always.)
I agree with Kendra’s advice that buying a vendor tool is the right choice here, whenever it’s possible. It’s fairly likely that you’ll spend more money creating (and maintaining) your own scaled-down version of a vendor tool than biting the bullet and paying for a packaged product.
I present to the community a comprehensive library of all wait types and latch classes that have existed since SQL Server 2005 (yes, it includes 2016 waits and latches).
The idea is that over time, this website will have the following information about all wait types and latch classes:
What they mean
When they were added
How they map into Extended Events (complete for all entries already)
Example call stacks of where they occur inside SQL Server
Email link for feedback and questions
It’s not complete yet, but entries are thorough.
A question came up in class today about easily seeing the degree of parallelism for parallel query plans, so I’ve updated my waiting tasks script to pull in the dop field from sys.dm_exec_query_memory_grants. Here it is for your use.
This is a good one to have in your grab bag of scripts.