Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add allocator for memory backpressure #108

Merged
merged 6 commits into from Oct 27, 2020
Merged

Conversation

hannahhoward
Copy link
Collaborator

Goals

With slow receiving peers, we can sometimes make major memory allocators in a selector traversal if the blocks we're traversing aren't being sent. We would like to slow down traversals with backpressure to prevent global allocations from going over a certain amount

Implementation

  • Establish an allocator that will allocate and deallocate, against both a global total and a per peer total. The allocate command returns a channel when the allocation can be safely completed under both the global and per peer max (if it can be done currently under the global and per peer max the channel will read immediately)
  • When deallocating, prioritize in the following order:
    • peers where pending next allocation will go under per peer max for that peer
    • if there are multiple that meet this criteria, prioritize peer with oldest pending allocation
  • hook deallocator into notification system on peer responder sender
  • add options for configuring allocator

Copy link
Member

@Stebalien Stebalien left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I'm generally concerned here about never releasing allocations in some cases.

  • Message sending fails.
  • Peer disconnects.

This could cause us to slowly slow down then stop.

The main solution I can think of is a finalizer. That is, pass the block into the allocator and get back a "tracked block". The "tracked block" would have some form of "deallocate" method that would, at a minimum, be called on free.

allocResponse := prs.allocator.AllocateBlockMemory(prs.p, blkSize)
select {
case <-prs.ctx.Done():
return false
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Hm. can't this cause us to never release the memory?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

There are two cases this could happen -- first is if the whole graphsync instance shuts down, in which case, who cares.

The second is if the peer itself shuts down. I am working on a fix for this now.

responsemanager/allocator/allocator.go Outdated Show resolved Hide resolved
add tests of large file processing to benchmarks
add an allocator that manages global memory allocations on responder and blocks peerresponsesenders
as needed
@hannahhoward
Copy link
Collaborator Author

hannahhoward commented Oct 27, 2020

@Stebalien this should now be ready for review, I think.

The main addition I've added is the removal of allocations for a peer when it disconnects. You can see this in the ReleasePeerMemory method on the allocator. (I also removed allocation when blocksize = 0 case why block for nothing)

So regarding your comment:

  • if message send fails, a notification is still sent, and published, which triggers a freeing of relevant memory
  • if a peer disconnects, we now free ALL memory for that peer if any is allocated

Also, I felt it was pretty important to prove to myself that we've actually solved the allocation problem, so you can see I've made some changes in the benchmarks. Specifically, I have a large file transfer test (1GB). I've run it both as it currently stands -- with 128MB max for allocations (artificially low) and regular (with 4GB default, which means no back pressure during the request). Note that the connection bandwidth in the test is extremely slow -- so not much data is sent over the wire in the 10 seconds the test runs. At the time the test stops, minus backpressure, we should have created the conditions that triggered the memory issue people are seeing: the selector traversal is done, and we've queued up all the response messages but very few have gone out. With backpressure, the selector traversal should be held up, so that only some of the blocks have been read out of the blockstore, and we've only queued up messages up to the memory limit.

So, here's the results:

Without backpressure:
profile002

With backpressure:
profile001

I've outlined the area where you can see the different results are as expected. Note that I had to use Badger to replicate this case with the in memory data store reading blocks has no allocation penalty.

Copy link
Member

@Stebalien Stebalien left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I haven't reviewed everything but this looks reasonable. I guess my main concerns are:

  1. This may lead to a lot of work/allocations per block sent.
  2. Related, we're playing a lot of games with channels just to avoid a lock. A single mutex would likely be faster and have less code.

Comment on lines 30 to 31
const defaultTotalMaxMemory = uint64(4 * 1 << 30)
const defaultMaxMemoryPerPeer = uint64(1 << 30)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

These defaults seem way too high. I'd expect something on the order of megabytes. (e.g., 8MiB per peer, total of 128MiB). That should be more than enough, right?

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

(ideally we'd profile the affects on performance somehow)

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I'm thinking 256 / 16MB. I just don't want the jittery ness of holding up a selector traversal to end up with a pipe that's not maxed out. I could be super wrong? (seems like a thing that definitely merits profiling in the future)

done := make(chan struct{}, 1)
select {
case <-a.ctx.Done():
responseChan <- errors.New("context closed")
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

a.ctx.Err()?

responseChan := make(chan error, 1)
select {
case <-a.ctx.Done():
responseChan <- errors.New("context closed")
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

return a.ctx.Err()?

responseChan := make(chan error, 1)
select {
case <-a.ctx.Done():
responseChan <- errors.New("context closed")
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

ditto.

func (a *Allocator) Start() {
go func() {
a.run()
a.cleanup()
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

nit: Any reason not to move this into run() as a defer? (then just invoke go a.run() here)

Comment on lines 158 to 159
for a.processNextPendingAllocation() {
}
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

The external loop here is strange.

@@ -383,6 +394,14 @@ func (prs *peerResponseSender) FinishWithCancel(requestID graphsync.RequestID) {
}

func (prs *peerResponseSender) buildResponse(blkSize uint64, buildResponseFn func(*responsebuilder.ResponseBuilder), notifees []notifications.Notifee) bool {
if blkSize > 0 {
allocResponse := prs.allocator.AllocateBlockMemory(prs.p, blkSize)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Do we have a max request limit? IIRC, we do so this shouldn't be a huge issue. However, in the future, we should consider something like:

  1. Take a ticket to allow allocating. We'd have limits (per-peer and total) on the number of outstanding tickets.
  2. Load the block.
  3. Allocate space.
  4. Release the ticket.

The ticket effectively measures the maximum amount of space we might need. Then we can convert to a real allocation to free up that space.

Comment on lines 399 to 403
select {
case <-prs.ctx.Done():
return false
case <-allocResponse:
}
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

ultra-stylistic-nit-you-should-probably-ignore:

select {
case <-prs.allocator.AllocateBlockMemory(prs.p, blkSize):
case <-prs.ctx.Done():
    return false
}

refactor allocator to remove go routine and address a few PR comments
Copy link
Member

@Stebalien Stebalien left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

Comment on lines 30 to 31
const defaultTotalMaxMemory = uint64(1 << 28)
const defaultMaxMemoryPerPeer = uint64(1 << 24)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

nit: Personally, I think in MiB, GiB, etc. I'd find these easier to read as uint64(256<<20) and uint64(16<<20).

responsemanager/allocator/allocator.go Outdated Show resolved Hide resolved
@hannahhoward hannahhoward merged commit 034465b into master Oct 27, 2020
@aschmahmann aschmahmann mentioned this pull request Feb 18, 2021
73 tasks
@mvdan mvdan deleted the feat/memory-backpressure branch December 15, 2021 14:16
marten-seemann pushed a commit that referenced this pull request Mar 2, 2023
* feat(benchmarks): add rudimentary benchmarks

Add a benchmarking framework to measure data transfer performance
Also update graphsync

* fix(benchmarks): setup accurate heap profiling

* ci(circle): update to go 1.14

* style(lint): cleanup imports
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

2 participants