Scheduler stories: OLEDB, the external wait that isn’t preemptive

So I’ve been having this ongoing discussion with Lonny Niederstadt (b | t) recently, where he tries to make sense of how CheckDB performs, and I fixate on a possibly irrelevant detail. In other words, he talks over my head, and I talk under his feet. Seems fair to me.

Today is the day to air my funny bits, and with some luck Lonny will continue to take us to interesting places in his own explorations.

The thing about external waits

I’m going to go out on a limb and suggest that none of us are very clear about what external waits are. Code external to SQL Server? External to the CPU? Code that was dropped by aliens?

Previously I dug into preemptive waits in SQLOS, and to be honest, I equated “preemptive” with “external”. For the most part the two go hand in hand after all.

To recap, a preemptive wait isn’t necessarily a wait at all. What happens is that a worker needs to run some code that can’t be trusted to play by cooperative scheduling rules. And rather than put the SQLOS scheduler (and all its sibling workers) at the mercy of that code, the worker detaches itself from the scheduler and cedes control to a sibling runnable worker.

The time period from this moment until the worker returns to cooperative scheduling is labeled as a preemptive wait. During this time, one would hope that the thread did indeed sleep a bit, because it would be directly competing for CPU with its sibling through the mediation of the operating system scheduler. In other words, the time ascribed to a preemptive wait covers an unknown combination of working and sleeping.

In that blog post, I also covered the possibility of external waits getting nested: during the time where we’re executing code but counting each passing tick as external wait A, it is possible to declare another external wait B, and temporarily double count the same slice of time against both. Even more confusingly, we could temporarily dip back into cooperative scheduling while the external “wait” continues.

First, a fundamental premise. A wait type is just a label – a task name someone decided to fill in on a notional time card. Different pieces of code can use the same label for different things, or if we’re lucky, a given wait type is used in one place only, and its presence pinpoints the exact function that was running.

Today I’m only talking about the OLEDB wait as it manifests in CheckDB, although a similar story may pertain elsewhere. In case you didn’t read the title, OLEDB is an external wait type that isn’t preemptive. But what does this mean?

It means that some of what I said about preemptive waits still applies, most significantly the idea that code can actively be running while advertising itself as being in a wait. This can be seen as a slight slant on what the wait type measures: we are using an existing mechanism as a profiling tool that surfaces how much time is spend in a certain chunk of code.

However, in this case the worker doesn’t go preemptive, i.e. it doesn’t yield the scheduler to a sibling while it does the work advertised as a wait.

Here it really gets weird. This worker is cooperatively scheduled, and has a conscience that tells it not to hog the scheduler. Every so often, it will offer to yield, and if the scheduler accepts the offer the CheckDB worker will properly go to sleep, with this sleep time labeled as SOS_SCHEDULER_YIELD.

But at the same time, the clock is still ticking on the OLEDB wait!

This is an entirely new twist on double counting. We claim to be waiting, but are working, except that sometimes we do stop working, counting a bit of time against both OLEDB and SOS_SCHEDULER_YIELD.

I am not saying that this happens all the time, but this is the way that a certain branch of code is written, as least in SQL Server 2014. The OLEDB “wait” is declared within CQScanRmtScanNew::GetRowHelper(), and during this “wait” we get a call to CUtRowset::GetNextRows(), which itself calls CTRowsetInstance::FGetNextRow(). However, within GetNextRows(), after every 16 invocations a courtesy call is made to YieldAndCheckForAbort(), which may yield the scheduler with an SOS_SCHEDULER_YIELD wait.

To visualise broadly:

Visualisation of time spent and time measured

Bonus material: The little preemptive wait that wasn’t

The OLEDB wait is neatly encapsulated in an instance of the CAutoOledbWait class, which in turn contains an SOS_ExternalAutoWait, the same object used by preemptive waits.

Now if we look into SOS_ExternalAutoWait, it comes with three constructors. One gives us a bland UNKNOWN/MISCELLANEOUS wait, presumably on the historic premise that folks didn’t always want to bother categorising their wait activity. Another is fully parameterised, and can emit any supplied wait type. But the third one really catches one’s eye: it’s wired to emit PREEMPTIVE_OS_GETPROCADDRESS.

Clearly PREEMPTIVE_OS_GETPROCADDRESS must serve as a convenient “smoke break” wait type for certain callers, and I’d find it hard to believe that so many people really call GetProcAddress(). So on the premise that nothing in this external wait guarantees it is used preemptively, I am inclined to think that:

  1. When you see this particular wait, you have to read it as MISCELLANEOUS
  2. It ain’t necessarily preemptive

See you next time!

Unsung SQLOS: The SOS_UnfairMutexPair behind CMEMTHREAD waits

As with the droppings of the Questing Beast, we recognise synchronisation code paths by their emissions. But even when not leaving telltale fewmets, these creatures wander among us unseen, unsung, until shutdown doth us part.

The place of the SOS_UnfairMutexPair

Bob Dorr has done a great job of illustrating why thread-safe SQLOS memory objects need serialised access in How It Works: CMemThread and Debugging Them. This has been followed up by the “It just runs faster” coverage of dynamic memory partitioning.

Today I’ll be examining the SOS_UnfairMutexPair, the synchronisation object behind memory allocations. While I’m going to describe synchronisation as a standalone subject, it’s useful to think of it as the CMEMTHREAD wait; to the best of my knowledge nothing other than memory allocations currently uses this class.

For context, I have previously described a bunch of other synchronisation classes:

One picture which emerges from all these synchronisation flavours is that a developer can choose between busy waiting (eagerly burning CPU), politely going to sleep (thread rescheduling), or a blend between the two. As we’ll see the SOS_UnfairMutexPair goes for a peculiar combination, which was clearly tuned to work with the grain of SQLOS scheduling.

The shape of the object

With the exception of the central atomic lock member, everything comes in pairs here. The class models a pair of waitable objects, each having an associated pair of members to note which scheduler and task currently owns it:

Layout of the SOS_UnfairMutexPair (2016 incarnation)

Although it exposes semantics to acquire either both mutexes or just the second, in its memory allocation guise we always grab the pair, and it effectively acts as a single mutex. I’ll therefore restrict my description by only describing half of the pair.

Acquisition: broad outline

The focal point of the mutex’s state – in fact one might say the mutex itself – is the single Spinlock bit within the 32-bit lock member. Anybody who finds it zero, and manages to set it to one atomically, becomes the owner.

Additionally, if you express an interest in acquiring the lock, you need to increment the WaiterCount, whether or not you managed to achieve ownership at the first try. Finally, to release the lock, atomically set the spinlock to zero and decrement the WaiterCount; if the resultant WaiterCount is nonzero, wake up all waiters.

Now one hallmark of a light-footed synchronisation object is that it is very cheap to acquire in the non-contended case, and this class checks that box. If not owned, taking ownership (the method SOS_UnfairMutexPair::AcquirePair()) requires just a handful of instructions, and no looping. The synchronisation doesn’t get in the way until it is needed.

However, if the lock is currently owned, we enter a more complicated world within the SOS_UnfairMutexPair::LongWait() method. This broadly gives us a four-step loop:

  1. If the lock isn’t taken at this moment we re-check it, grab it, simultaneously increment WaiterCount, then exit triumphantly, holding aloft the prize.
  2. Fall back on only incrementing WaiterCount for now, if this is the first time around the loop and the increment has therefore not been done yet.
  3. Now wait on the EventInternal, i.e. yield the thread to the scheduler.
  4. Upon being woken up by the outgoing owner releasing the lock as described above, try again to acquire the lock. Repeat the whole loop.

The unfairness derives from the fact that there is no “first come, first served” rule, in other words the wait list isn’t a queue. This is not a very British class at all, but as we’ll see, there is a system within the chaos.

The finicky detail

Before giving up and waiting on the event, there is a bit of aggressive spinning on the spinlock. As is standard with spinlocks, spinning burns CPU on the optimistic premise that it wouldn’t have to do it for long, so it’s worth a go. However, the number of spin iterations is limited. Here is a slight simplification of the algorithm:

  • If the scheduler owning the lock is the ambient scheduler, restrict to a single spin.
  • Else, give it a thousand tries before sleeping.
  • Each spin involves first trying to grab both the lock and (if not yet done) incrementing WaiterCount. If that doesn’t work, just try and increment the WaiterCount.

This being of course the bit where the class knows a thing or two about SQLOS scheduling: If I am currently running, then no other worker on my scheduler can be running. But if another worker on my scheduler currently holds the lock, it can’t possibly wake up and progress towards releasing it unless *I* go to sleep. Mind you, this is already a edge case, because we’d hope that the owner of this kind of lock wouldn’t go to sleep holding it.

To see how scheduling awareness comes into play, I’m going to walk through a scenario involving contention on such a mutex. If some of the scheduling detail makes you frown, you may want to read Scheduler stories: The myth of the waiter list.

A chronicle of contention

In this toy scenario, we have two schedulers with two active workers each. Three of the four workers will at some point during their execution try and acquire the same mutex, and one of them will try twice. Time flows from left to right, and the numbered callouts are narrated below. A red horizontal bracket represents the period where a worker owns the mutex, which may be a while after the acquisition attempt started.

The mutex acquisition tango
  1. A1 wants to acquire the mutex and, finding it uncontended, gets it straight away.
  2. B2 tries to acquire it, but since it is held by A1, it gives up after a bit of optimistic spinning, going to sleep. This gives B1 a turn on the scheduler.
  3. A1 releases the mutex, and finding that there is a waiter, signals it. This moves B2 off the mutex’s waiter list and onto scheduler B’s runnable queue, so it will be considered eligible for running at the next scheduler yield point.
  4. B1 wants the mutex, and since it isn’t taken, grabs it. Even though B2 has been waiting for a while, it wasn’t running, and it’s just tough luck that B1 gets it first.
  5. A1 wants the mutex again, but now B1 is holding it, so A1 goes to sleep, yielding to A2.
  6. B1 releases the mutex and signals the waiter A1 – note that B2 isn’t waiting on the resource anymore, but is just in a signal wait.
  7. B1 reaches the end of its quantum and politely yields the scheduler. B2 is picked as the next worker to run, and upon waking, the first thing it does is to try and grab that mutex. It succeeds.
  8. A2 reaches a yield point, and now A1 can get scheduled, starting its quantum by trying to acquire the mutex. However, B2 is still holding it, and after some angry spinning, A2 is forced to go to sleep again, yielding to A1.
  9. B2 releases the mutex and signals the waiting A1, who will hopefully have better luck acquiring it when it wakes up again.

While this may come across as a bit complex, remember that an acquisition attempt (whether immediately successful or not) may also involve spinning on the lock bit. And this spinning manifests as “useful” work which doesn’t show up in spinlock statistics; the only thing that gets exposed is the CMEMTHREAD waiting between the moment a worker gives up and goes to sleep and the moment it is woken up. This may be followed by another bout of unsuccessful and unmeasured spinning.

All in all though, you can see that this unfair acquisition pattern keeps the protected object busy doling out its resource: in this case, an memory object providing blocks of memory. In an alternative universe, the mutex class may well have decided on its next owner at the moment that the previous owner releases it. However, this means that the allocator won’t do useful work until the chosen worker has woken up; in the meantime, the unlucky ones on less busy schedulers may have missed an opportunity to get woken up and do a successful acquire/release cycle. So while the behaviour may look unfair from the viewpoint of the longest waiter, it can turn out better for overall system throughput.

Of course, partitioning memory objects reduced the possibility of even having contention. But the fact remains: while any resources whatsoever are shared, we need to consider how they behave in contended scenarios.

Compare-and-swap trivia

Assuming we want the whole pair, as these memory allocations do, there are four atomic operations performed against the lock member:

  • Increment the waiter count: add 0x00010001
  • Increment the waiter count and grab the locks: add 0x80018001
  • Just grab the locks (after the waiter count was previously incremented): add 0x80008000
  • Release the locks and decrement the waiter count: deduct 0x80018001

For the first three, the usual multi-step pattern comes into play:

  1. Retrieve the current value of the lock member
  2. Add the desired value to it, or abandon the operation, e.g. if we find the lock bit set and we’re not planning to spin
  3. Perform the atomic compare-and-swap (lock cmpxchg instruction) to replace the current value with the new one as long as the current value has not changed since the retrieval in step 1
  4. Repeat if not successful

The release is simpler, since we know that the lock bits are set (we own it!) and there is no conditional logic. Here the operation is simple interlocked arithmetic, but two’s complement messes with your mind a bit: the arithmetic operation is the addition of 0x7ffe7fff. Not a typo: that fourth digit is an “e”!

This all comes down to thinking of the lock bit as a sign bit we need to overflow in order to set to 1. The higher one overflows out of the 32-bit space, but the lower one overflows into the lowest bit of the first count. To demonstrate, we expect 0x80018001 to turn to zero after applying this operation:

    8001 8001
  + 7ffe 7fff
    ---------
(1) 0000 0000

Final thoughts

So you thought we’ve reached the end of scheduling and bit twiddling? This may turn out to be a perfect opportunity to revisit waits, and to start exploring those memory objects themselves.

I’d like to thank Brian Gianforcaro (b | t) for feedback in helping me confirm some observations.

Context in perspective 4: On the street where you live

Although today’s post is loosely related to the esoterica of multiple virtual inheritance I unearthed in part 3, it is far more straightforward and goes no further than single inheritance. Spoiler alert: people come up with clever stuff.

Part 3 was a riff on the theme of finding the address of an object, given the address of an interface (vftable) within that object. This was made possible by a combination of member offsets known at compile time and offsets explicitly stored within the object. Now we move on to discover how the address of one object can be derived from the address of another, purely by convention and without relying on magic numbers known only to the compiler or stored in runtime structures. Sounds interesting?

I have often walked down this deck before
But the water always stayed beneath my neck before
It’s the first time I’ve had to scuba dive
When I’m down on the deck where you live.

Come dive with me

In Part 2, the last example was a function which optionally called commondelete as object disposal after the class destructor:

sqllang!CSecContextToken::`vector deleting destructor':
=======================================================
     mov   qword ptr [rsp+8],rbx
     push  rdi
     sub   rsp,20h
     mov   ebx,edx
     mov   rdi,rcx
     call  sqllang!CSecContextToken::~CSecContextToken
     test  bl,1
+-+- je    LabelX
| |
| |  { if low bit of original edx was set  
| ->     mov   rcx,rdi
|        call  sqllang!commondelete
|    }
|
LabelX:
+--> mov   rax,rdi
     mov   rbx,qword ptr [rsp+30h]
     add   rsp,20h
     pop   rdi
     ret

So what does commondelete() do? Well, quite simply it is a global function that releases a previously allocated block of memory starting at the supplied address. Prior to the construction of an object, we need to allocate a chunk of memory to store it in, and after its destruction, this memory must be given back to the pool of available memory. Forgetting to do the latter leads to memory leaks, not to mention getting grounded for a week.

Notionally we can imagine a global portfolio of active memory allocations, each chunk uniquely identified by its starting address. When we want memory, we ask the global memory manager to lend us some from the unused pool, and when we’re done with it, we hand it back to that memory manager, who carefully locks its internal structures during such operations, because we should only access mutable global state in a single-threaded manner, and…. Oops. No, no, double no. That is not how SQL Server does things, right?

Okay, we know that there are actually a variety of memory allocators out there. If nothing else, this avoid the single bottleneck problem. But now the question becomes one of knowing which allocator to return a chunk of memory to after we’re done with it.

One possible solution would be for the object which constructs a child object to store its own reference to the allocator, and this parent object is then the only object who is allowed to destroy its child object. However, this yields a system where all objects have to exist in a strict parent-child hierarchy, which is very restrictive.

As it turns out, many interesting SQL Server objects control their lifetime through reference counting. If object A wants to interact with object B, it first announces that interest, which increases the reference count on B. This serves as a signal that B can’t be disposed, i.e. the pointer held by A remains valid. Once done, A releases the reference to B, which decreases B’s reference count again. Ultimately, B can only be destroyed after its reference count has reached zero. One upshot of this is that objects can live independent lives, without forever being tied to the apron strings of a parent object.

From that given, the problem becomes this: an object playing in this ecosystem must carry around a reference to its memory allocator. Doing it explicitly is conceptually simple. However, it would be onerous, because this pointer would take up an eight-byte chunk of memory within the object itself, which can be a significant tax when you have a large number of small objects. Perhaps more significantly, it raises the complexity bar to playing along, because now all objects must be born with a perfectly-developed plan for their own eventual death, and they must implement standardised semantics for postmortem disposal of their bodies. That’s harsh, not to mention bug-prone.

Far better then would be a way for an outside agent to look at an object and know exactly where to press the Recycle button, although the location of that button is neither global nor stored within the target object.

Pleasant little kingdom

Imagine a perfectly rational urban design; American grid layout taken to the extreme. Say you live at #1137 Main Street and want to find the nearest dentist, dentistry being of particular importance in this kingdom. Well, the rule is simple: every house number divisible by 100 contains a dentist, and to find your local one you just replace the last two digits of your house number with zeros.

That is the relationship that objects have with their memory allocators under SQLOS, except that we are dealing with 8192-byte pages. Take the address of any object in memory, round that address down to the next lower page boundary, and you will find a page header that leads you directly or indirectly to the memory object (allocator) that owns the object’s memory; this object will happily receive the notification that it can put your chunk of memory back into the bank.

I’m skipping some detail around conditionals and an indirect path, but the below is the guts of how commondelete() takes an address and crafts a call to the owning memory object to deallocate that target object and recycle the corpse:

  mov   rdx, rcx
  and   rcx, 0FFFFFFFFFFFFE000h

  ; now rdx contain the address we want to free
  ; and rcx is the start of the containing page 

  mov   rcx, qword ptr [rcx+8]
  ; now rcx contains the 2nd qword on the page.
  ; This is the address of the memory object,
  ; aka pmo (pointer to memory object)

  mov   rax, qword ptr [rcx]
  ; 1st qword of object = pointer to vftable
  ; Now rax points to the vftable

  call   qword ptr [rax+28h]
  ; vftable is an array of (8-byte) function
  ; pointers. This calls the 6th one. Param 1
  ; (rcx) is the pmo. Param 2 (rdx) is the
  ; address we want to free.

See, assembler isn’t really that bad once you put comments in.

Show me

Let’s find ourselves some SQLOS objects. SOS_Schedulers are sitting ducks, because you can easily find their addresses from a DMV query, and they don’t suddenly fly away. And of course I have explored them before. Below from a sad little VM:

I’m getting scheduled in the morning

Got myself a few candidate addresses, so it’s time to break into song the debugger. I’m going to dump a section of memory in 8-byte chunks, and to make it more interesting, I’ll do so with the dps command, which assumes all the memory contents are pointers, and will call out any that it recognises from public symbols. Never mind that this regimented 8-byte view may be at odds with the underlying data’s shape – it’s just a convenient way to slice it.

Because I know where I’m heading, I’m rounding the starting address down to the start of that 8Kb page:

0:031> dps 40130000
00000000`40130000 00010002`00000000
00000000`40130008 00000000`4001e040
00000000`40130010 00000001`00000008
00000000`40130018 00000000`00000000
00000000`40130020 00000000`40188000
00000000`40130028 00000000`00000000
00000000`40130030 00000000`00000003
00000000`40130038 00000000`000010a0
00000000`40130040 00007ffb`edbe0ff8 sqldk!ThreadScheduler::`vftable'
00000000`40130048 00000000`40120048
00000000`40130050 00000000`40080170
00000000`40130058 00000000`00000003
00000000`40130060 00000000`40080170
00000000`40130068 00000000`399d3858
00000000`40130070 00000000`400204f8
00000000`40130078 00000014`00000000

Firstly, we have a beautiful piece of confirmation that the object starting at 0040 is indeed a scheduler, because its very first quadword contains a pointer to the ThreadScheduler vftable. But we knew that already 🙂

What I’d like to know is what the second quadword on the page, at 0008, is pointing to. Interesting, its address also ends in 0040…

Same thing then, let’s dump a bit of that, starting from the top of that page:

0:057> dps 4001e000
00000000`4001e000  00010002`00000000
00000000`4001e008  00000000`4001e040
00000000`4001e010  00000045`00000001
00000000`4001e018  00000000`00000000
00000000`4001e020  00000000`3a6e8000
00000000`4001e028  00000000`40188000
00000000`4001e030  00000000`00000001
00000000`4001e038  00000000`000001b0
00000000`4001e040  00007ffb`edbdc640 sqldk!CMemThread::`vftable'
00000000`4001e048  00000000`00000001
00000000`4001e050  00000000`00002000
00000000`4001e058  00000000`00000004
00000000`4001e060  00000000`40022200
00000000`4001e068  00000000`00000010
00000000`4001e070  00000000`40000280
00000000`4001e078  00000000`4001e040

Aha! On a freaking platter. The vftable symbol name confirms that the scheduler’s parent memory object is in fact a CMemThread<CMemObj>. Not only that, but if you look at the second slot, it seems that a memory object is its own owner!

But speaking of the vftable, since we’re now familiar with these creatures as simple arrays of function pointers, let’s dump a bit of it. The full thing is rather long; this is just to give you the idea:

0:057> dps 7ffb`edbdc640
00007ffb`edbdc640  00007ffb`edadc140 sqldk!IMemObj::QueryInterface
00007ffb`edbdc648  00007ffb`eda75f00 sqldk!IMemObj::AddRef
00007ffb`edbdc650  00007ffb`eda84d50 sqldk!IMemObj::Release
00007ffb`edbdc658  00007ffb`edb0ee40 sqldk!CMemThread::Alloc
00007ffb`edbdc660  00007ffb`edb0f0b0 sqldk!CMemThread::Realloc
00007ffb`edbdc668  00007ffb`eda75410 sqldk!CMemThread::Free
00007ffb`edbdc670  00007ffb`edb0f1d0 sqldk!CMemThread::GetSize
00007ffb`edbdc678  00007ffb`edb0f440 sqldk!CMemThread::DidAlloc

Recall that commondelete() calls the sixth entry, located 0x28 bytes from the start. Unsurprisingly, this is the Free() function. And look, the first three tell us that COM is spoken here.

Takeaway

This is not the time to get into the details of how memory objects actually work, but we sure got a nice little glimpse of what SQLOS does with the memory space. Also, the charming side of vftables was laid bare.

Although the assembler view might look daunting, we saw how a virtual method, in this case Free(), is called, using nothing more than the address of the vftable and the knowledge that the object residing there is (or is derived from) the base type exposing that method.

But let’s not lose sight of the “Context in perspective” goal. Here the context is the address of a single object, and the perspective is seeing it framed by convention within a memory page. By its placement in memory, the object gains the all-important implicit attribute of an owning memory object.

Further reading

Bob Dorr’s classic How it works: CMEMTHREAD and debugging them is definitely going to feature when I visit memory objects again.

Indirection indigestion, virtual function calls and SQLOS

One of Slava Oks’s classic posts from the 2005 era is
A new platform layer in SQL Server 2005 to exploit new hardware capabilities and their trends. I have occasionally revisited it as a kind of SQLOS manifesto, and some things which at first I found mystifying have become clearer over the years.

In many ways, it seems that the more recent SQLOSv2/SQLPAL work is a simple case of continuing with a project that has been organically evolving since the SQL Server 7 User Mode Scheduler, and rooted in classic Stonebraker: just how far can we assume control of core OS functions within an RDBMS process?
Continue reading “Indirection indigestion, virtual function calls and SQLOS”

Scheduler stories: The myth of the waiter list

‘Tis the season to be controversial, so let’s take a stroll down memory lane to Ken Henderson’s classic Inside the SQL Server 2000 User Mode Scheduler:

The waiter list maintains a list of workers waiting on a resource. When a UMS worker requests a resource owned by another worker, it puts itself on the waiter list for the resource and enters an infinite wait state for its associated event object. When the worker that owns the resource is ready to release it, it is responsible for scanning the list of workers waiting on the resource and moving them to the runnable list, as appropriate. And when it hits a yield point, it is responsible for setting the event of the first worker on the runnable list so that the worker can run. This means that when a worker frees up a resource, it may well undertake the entirety of the task of moving those workers that were waiting on the resource from the waiter list to the runnable list and signaling one of them to run.

John Tenniel's White Rabbit from "Alice in Wonderland"

The lists behind the legend

I have not gone as far as opening up my rusty copy of SQL Server 2000 to see how Ken’s description fits in there, but I am now pretty certain that the above quote has transmuted over the years into a common misunderstanding about SQLOS scheduling mechanics.

Now nothing Ken said is untrue or particularly out of date. It is just that we often hear “the waiter list” (by implication handling resource waits) described as an attribute of a scheduler, which is not the case.

Let’s revisit when the scheduler code runs, and what it does:

  • A worker will yield, either because it needs to wait for a resource, or because it is eaten up with guilt over reaching the end of its allotted quantum.
  • The act of yielding means that scheduler code (methods on the SOS_Scheduler class) gets invoked.
  • After a bit of housekeeping for the common good of all workers sharing the scheduler, control is transferred back to a worker to do its thing – this may even be the same worker who originally yielded.
  • The housekeeping consists of checking for aborted tasks, processing pending I/Os, and checking for I/O completions and timer list timeouts.

The single most important list that a scheduler owns is the collection of runnable workers, that is, the subset of workers belonging to this scheduler who are not waiting for anything other than CPU. This has variously been described as a list and a queue; I shall be using the term “runnable queue” by convention, but be aware that it is a data structure that has changed over the years and isn’t a simple queue.

A scheduler has one piece of “creative” interaction with this runnable queue, and it comes with only two variables:

  • When a context switch is requested by an outgoing worker owning the scheduler, the scheduler code has to choose which one of potentially multiple workers is going to be its next owner.
  • The incoming worker gets given a quantum expiry date, by which time it is expected to yield.

Core scheduler code running during context switching only dequeues runnable workers, and at such moments a given scheduler only looks at its own runnable queue. In contrast, code running all over the place, including in the context of workers belonging to other schedulers, may enqueue workers on to the runnable queue.

Time for a simple diagram:

Someone to watch over me

What I’m trying to get across here is that each instance of a waitable resource has its own wait list, and the scheduler has no interest in this, because a scheduler only acts upon its runnable queue. Seen from a different angle, once a worker is waiting on a resource, its scheduler doesn’t care, because it can’t and won’t manage the waiting logic of something like a latch. This splits the responsibilities neatly in two:

  • The synchronisation class guarding a resource (which inevitably will be built upon an EventInternal) stands watch over all the workers queueing up to have a ride on that resource. The act of granting access to a worker involves moving the worker from the wait list and getting it on to the runnable queue of that scheduler’s worker, and this is achieved by the synchronisation class.
  • The scheduler, in turn, doesn’t decide who is runnable, but it does get to pick which of the runnable workers (however they reached that state) runs next.

The I/O and timer lists

There are however two cases where the scheduler decides to make a worker runnable in the normal course of events. One is when a worker was waiting on I/O to complete, where periodic scheduler housekeeping is the mechanism by which SQLOS takes note of the I/O completion. At this point some workers who were on the I/O list may find themselves moved to the runnable queue just before the next worker is picked to be granted ownership of the scheduler – the lucky winner might be one of these workers, or it may be someone else who has been runnable for a while.

The second, and actually more interesting case, is the timer list. In its simplest use case, this is where you will find workers executing T-SQL WAITFOR statements. The list is neatly ordered by timer expiry date, and at each invocation of the scheduler context-switch housekeeping, workers whose timer expiry dates have now passed will be moved to the runnable queue.

What makes a timer list particularly interesting though, is when it implements a resource wait timeout, for instance a lock timeout. In this scenario we actually have a worker waiting on two things simultaneously: a resource and a timer. If the resource is acquired before the timer expires, all is good: the worker goes on to the runnable queue, and upon being woken up it finds a thumbs-up as the return value of its resource acquisition call.

However, should the timer expire before the resource has been acquired, the scheduler will actually venture forth and take the worker off that waiter list before making it runnable and setting an error return value as wake-up call. Think of it as every teenager’s worst nightmare: you’re not home by curfew, so Mom comes to your dodgy party to drag your sorry ass home. And then you wake up with a hangover and note stuck to your forehead reading “No cake for you”.

Whither next?

I tried to keep this comparatively high-level, but might take a nice little detour into the WorkerTimerRequest some day if time permits.

There you have it. Be home on time and have a thread-safe festive season.

The DMV diaries: Worker, task, request and session state

We have all been there. You believe that a certain status (e.g. is the order shipped?) lives in a simple database column, only to find that it comes from a view built on a view with all kinds of creative CASE statements. And it may look ugly, but at the end of the day, you have to admit that it successfully serves the purpose of exposing business data in the way that users expect to see it.

Guess what: The “V” in “DMV” exists for a similar reason. Today I’ll be whizzing through the various ways in which the status of a running piece of work is exposed to us in sys.dm_os_workers, sys.dm_os_tasks, sys.dm_exec_requests, and sys.dm_exec_sessions.
Continue reading “The DMV diaries: Worker, task, request and session state”

Scheduler stories: Going Preemptive

SQLOS is built upon the idea of cooperative, AKA non-preemptive, scheduling: out of any given collection of threads belonging to a scheduler, only one will own the scheduler at a given moment. To the degree that these cooperative threads represent the only work done by the underlying CPU, this means that the thread owning the scheduler really owns the CPU. Of course, a CPU will occasionally get side-tracked into doing other work, so the SQLOS scheduler as “virtual CPU” only represents a chunk of the real CPU, but we live in the expectation that this is a suitably large chunk.

John Tenniel's White Rabbit from "Alice in Wonderland"

It is understandable when such competition for the CPU comes from outside of SQL Server, but it can also be instigated from within SQL Server itself. This is the world of preemptive – or if you prefer, antisocial – scheduling.
Continue reading “Scheduler stories: Going Preemptive”

Scheduler stories: Interacting with the Windows scheduler

In the previous post, The joy of fiber mode, we saw how a fiber mode scheduler firmly controls which worker runs on a thread at a given moment. While it can’t positively ensure that the thread in question remains running all the time, the soul of the scheduler lives in that one thread, and as long as the thread runs, the scheduler gets invoked by its team of fiber workers, dispatching them in an appropriate order.
Continue reading “Scheduler stories: Interacting with the Windows scheduler”

Scheduler Stories: When does your scheduler run?

I am planning to burn a fair number of cycles on SQLOS scheduling internals for the foreseeable future, and with some luck, this turns into an interesting series. OS scheduling is already a subject that belongs “on the other side of the looking glass”, and this only gets more interesting when we look at user-mode SOS_Scheduler scheduling built on top of it.

If I don’t specifically mention a version, my frame of reference is SQL Server 2014. Yes, things changed since then, but the 2012-2014 scheduler is a good starting point, and the fundamental mechanisms I’ll initially cover have changed very little since the User Mode Scheduler (UMS) of SQL Server 7.0.
Continue reading “Scheduler Stories: When does your scheduler run?”

Unsung SQLOS: SOS_WaitableAddress

One of the more amusing words in the SQL Server synchronisation lexicon is “lightweight”. Locks bad. Nolocks good. Latches lightweight. The more spinlocks you eat, the more wait you lose!

If only things were that simple… But hey, I love the poetry of compromise. Check out the SOS_WaitableAddress for one of the many competing definitions of “lightweight”.
Continue reading “Unsung SQLOS: SOS_WaitableAddress”