I mean ever really wondered just how long a query of yours waited on stats to automatically update before running?
Have you ever been absolutely, positively sure that those gosh dang darn stats updates were putting your query on the trolley to Slowsville?
Your wishes will be 100% granted in SQL Server 2019.
This is a wait type that I’d consider useful but hopefully uncommon.
I’m going to be honest with you, dear readers. I’ve fallen out of like with wait stats.
Unless there’s a massive resource or blocking problem, they’re a bit bland.
Tuning a single query, I don’t look at them at all.
Sure, they can be a good detail when you’re painting an overall picture of a server, but they’re misleading a lot.
Erik makes a sound point. It’s usually a sound point when it reminds me of the Hayek quotation, “Mr. Keynes’s aggregates conceal the most fundamental mechanisms of change.”
What was the wait_type? Well, the obscure wait_type was called PREEMPTIVE_OS_PIPEOPS. What causes this wait? As it turns out, this is a generic wait that is caused by SQL pipe related activities such as xp_cmdshell.
Knowing this much information however does not get us to the root cause of this particular problem for this client. How do we get there? This is another case for Extended Events (XEvents).
Read on for two ways to approach this, both using Extended Events.
The secondary nodes may be configured using asynchronous or synchronous commit. With asynchronous commit, transaction considered to be committed and all locks were released when COMMIT log record is hardened on the primary node. SQL Server sends COMMIT record to secondary node; however, it does not wait for the confirmation that the record had been hardened in the log there.
This behavior changes when you use synchronous commit as shown in Figure 1. In this mode, SQL Server does not consider transaction to be committed until it receives the confirmation that COMMIT log record is hardened in the log on the secondary node. The transaction on primary will remain active with all locks held in place until this confirmation is received. The session on primary is suspended with HADR_SYNC_COMMIT wait type.
Click through for the full story.
I was contacted last week by someone who was confused about the WRITELOG wait type. They were seeing lots of these waits, with an average wait time of 18ms. The log was stored on a Raid-1 array, using locally-attached spinning disks in the server. They figured that by moving the log to Raid-1 array of SSDs, they’d reduce the WRITELOGwait time and get better workload throughput.
They did so and got better performance, but were very surprised to now see WRITELOG as the most frequent wait type on the server, even though the average wait time was less than 1ms, and asked me to explain.
Read on for Paul’s explanation of why this is not a scary situation, or is it particularly weird. SQL Server performance is a complicated thing and trying to limit it to one measure or one query can lead you down the wrong path.
Queries go through the cycle of the SPIDS / worker threads waiting in a series like this. A thread uses the resource e.g. CPU until it needs to yield to another that is waiting. It then moves to an unordered list of threads that are SUSPENDED. The next thread on the FIFO queue of threads waiting then becomes RUNNING. If a thread on the SUSPENDED list is notified that its resource is available, it becomes RUNNABLE and goes to the bottom of the queue.
Click through for an analogy using a microwave and plenty more.
When THREADPOOL strikes, even the best monitoring tools can have a bunch of blank spots hanging around in them.
If you’re on SQL Server 2016 or better, there are some helpful columns in sys.dm_exec_query_stats.
Erik also has advice to help you out if you are running into these waits.
At first, this statement might sound a bit confusing. Usually, we expect wait statistics to show us what a query is waiting on, whether it’s waiting on memory, loading pages from disk, or any of the other numerous wait types.
Once you start collecting wait statistics, you’ll have a lot of data to sort through. You might find waits like CX_PACKET, CX_CONSUMER, and PAGEIOLATCH. Surprisingly, these could mean that your databases aren’t well indexed.
This makes sense. At its core, wait stats tell you where SQL Server is hurting: where is the bottleneck. But just like a person at the doctor, SQL Server can only be so specific in how it relates this pain to you, and that specificity generally boils down to hardware components. The solution might be “get more hardware,” but as Arthur points out, writing better queries and using better indexes can mitigate those pains too.
So according to this DMV, there’s only 3 queries with memory grants, while the remaining 5 queries have to wait for space in this semaphore. This is where the wait type comes in. When a query is sitting as a waiter, it will display the wait type RESOURCE_SEMAPHORE.
This is one of the biggest performance-killing waits you can find, and there are several ways to tackle it in SQL Server, as well as adding more hardware.
Consider the following query execution scenario:
- You execute a SELECT query that triggers an automatic synchronous statistics update.
- The synchronous statistics update begins execution and your query waits (is essentially blocked) until the fresh statistics are generated.
- The query compilation and execution does not resume until the synchronous statistics update operation completes.
During this time, there are no external signs via common troubleshooting channels that the query is specifically waiting for the synchronous statistics update operation to complete. If the statistics update takes a long time (due to a large table and\or busy system), there is no easy way to determine root cause of the high duration.
This is now available in SQL Server 2019 CTP 2.1. Read the whole thing.