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From Adam Kocoloski <>
Subject Re: [DISCUSS] Improve load shedding by enforcing timeouts throughout stack
Date Fri, 26 Apr 2019 21:29:59 GMT
Hi Joan, great topic.

We don’t have enough realistic benchmarking data to be really specific yet, but my expectation
is that the aggregate size of the underlying KV pairs is at least as important as number of
documents in the batch. I have no doubt we’ll be able to ingest 1,000 1KB documents within
a single operation, but bump those up to 1MB each and it’ll be a different story.

I do expect our write throughput with FoundationDB to be quite healthy, and scalable. The
use of a separate transaction log allows the system to nicely accommodate shorts bursts of
heavy data ingestion.

On this topic, it’s also worth mentioning that FoundationDB allows us (if we want) to recover
the notion of a truly atomic batch write. FDB uses optimistic concurrency control underneath
so it’s not a situation where other writers get blocked like they do in CouchDB 1.x. If
we do use this feature then the atomic batch has to be under 10MB (including revision metadata
and any indexes). Batch operations that are not flagged as atomic can be split into separate
transactions, or grouped together for performance (I believe Paul’s current prototype defaults
to a separate transaction per doc in the batch, and submits them all in parallel).

Cheers, Adam

> On Apr 26, 2019, at 4:19 PM, Joan Touzet <> wrote:
> Hi Adam,
> I'll bring up a concern from a recent client with whom I engaged.
> They're on 1.x. On 1.x they have been doing 50k bulk update operations in a single request.
1.x doesn't time out. The updates are such that they guarantee that none will result in a
conflict or be rejected, so all 50k are accepted. They do this so it appears atomic to the
next reader - a read from another client can't occur in the middle of the big update, because
we have a single couch_file in 1.x.
> Obviously, in 2.x this doesn't work on two levels. First, there's multiple readers and
writers across a cluster, so the big bulk operation doesn't act as a blocker until it's finished
for any interposed reads. Second, you can't reliably finish 50k updates in a single batch
in a cluster anyway, because you'll probably hit the fabric timeout, if not other cluster
> As a general rule of thumb, I advise people to keep bulk document updates to no more
than batches of 1k at a time, with the understanding that in 2.x these are not treated as
an atomic transaction (and they weren't strictly that way in 1.x, either, but never mind that...)
> If we decide as a project that all operations must take less than 5 seconds, we're probably
going to have to reduce the bulk update batch size even further. I'm betting 100 would be
the upper bound on bulk updates.
> Is this going to impose a significant performance penalty on bulk ops?
> -Joan
>> On 2019-04-26 3:30 p.m., Adam Kocoloski wrote:
>> Hi all,
>> The point I’m on is that we should take advantage of this extra bit of information
that we acquire out-of-band (e.g. we just decide as a project that all operations take less
than 5 seconds) and come up with smarter / cheaper / faster ways of doing load shedding based
on that information.
>> For example, yes it could be interesting to use is_process_alive/1 to see if a client
is still hanging around, and have the gen_server discard the work otherwise. It might also
be too expensive to matter; I’m not sure anyone here has a good a priori sense of the cost
of that call. But I’d certainly wager it’s more expensive than calling timer:now_diff/2
in the server and discarding any requests that were submitted more than 5 seconds ago.
>> Most of our timeout / cleanup solutions to date have been focused top-down, without
making any assumptions about the behavior of the workers or servers underneath. I think we
should try to approach this problem bottoms-up, forcing every call to complete within 5 seconds
and handling timeouts correctly as they bubble up.
>> Adam
>>> On Apr 23, 2019, at 2:48 PM, Nick Vatamaniuc <> wrote:
>>> We don't spawn (/link) or monitor remote processes, just monitor the local
>>> coordinator process. That should cheaper performance-wise. It's also for
>>> relatively long running streaming fabric requests (changes, all_docs). But
>>> you're right, perhaps doing these for shorter requests (doc updates, doc
>>> GETs) might become noticeable. Perhaps a pool of reusable monitoring
>>> processes work there...
>>> For couch_server timeouts. I wonder if we can do a simpler thing and
>>> inspect the `From` part of each call and if the Pid is not alive drop the
>>> requestor at least avoid doing any expensive processing. For casts it might
>>> involve sending a sender Pid in the message. That doesn't address timeouts,
>>> just the case where the coordinating process went away while the message
>>> was stuck in the long message queue.
>>>> On Mon, Apr 22, 2019 at 4:32 PM Robert Newson <>
>>>> My memory is fuzzy, but those items sound a lot like what happens with
>>>> rex, that motivated us (i.e, Adam) to build rexi, which deliberately does
>>>> less than the stock approach.
>>>> --
>>>>  Robert Samuel Newson
>>>>> On Mon, 22 Apr 2019, at 18:33, Nick Vatamaniuc wrote:
>>>>> Hi everyone,
>>>>> We partially implement the first part (cleaning rexi workers) for all
>>>>> the
>>>>> fabric streaming requests. Which should be all_docs, changes, view map,
>>>>> view reduce:
>>>>> The pattern there is the following:
>>>>> - With every request spawn a monitoring process that is in charge of
>>>>> keeping track of all the workers as they are spawned.
>>>>> - If regular cleanup takes place, then this monitoring process is
>>>> killed,
>>>>> to avoid sending double the number of kill messages to workers.
>>>>> - If the coordinating process doesn't run cleanup and just dies, the
>>>>> monitoring process will performs cleanup on its behalf.
>>>>> Cheers,
>>>>> -Nick
>>>>> On Thu, Apr 18, 2019 at 5:16 PM Robert Samuel Newson <
>>>>> wrote:
>>>>>> My view is a) the server was unavailable for this request due to
>>>> the
>>>>>> other requests it’s currently dealing with b) the connection was
>>>> idle,
>>>>>> the client is not at fault.
>>>>>> B.
>>>>>>> On 18 Apr 2019, at 22:03, Done Collectively <>
>>>> wrote:
>>>>>>> Any reason 408 would be undesirable?
>>>>>>> On Thu, Apr 18, 2019 at 10:37 AM Robert Newson <>
>>>>>> wrote:
>>>>>>>> 503 imo.
>>>>>>>> --
>>>>>>>> Robert Samuel Newson
>>>>>>>>> On Thu, 18 Apr 2019, at 18:24, Adam Kocoloski wrote:
>>>>>>>>> Yes, we should. Currently it’s a 500, maybe there’s
something more
>>>>>>>> appropriate:
>>>>>>>>> Adam
>>>>>>>>>> On Apr 18, 2019, at 12:50 PM, Joan Touzet <>
>>>> wrote:
>>>>>>>>>> What happens when it turns out the client *hasn't*
timed out and
>>>> we
>>>>>>>>>> just...hang up on them? Should we consider at least
trying to send
>>>>>> back
>>>>>>>>>> some sort of HTTP status code?
>>>>>>>>>> -Joan
>>>>>>>>>>> On 2019-04-18 10:58, Garren Smith wrote:
>>>>>>>>>>> I'm +1 on this. With partition queries, we added
a few more
>>>> timeouts
>>>>>>>> that
>>>>>>>>>>> can be enabled which Cloudant enable. So having
the ability to
>>>> shed
>>>>>>>> old
>>>>>>>>>>> requests when these timeouts get hit would be
>>>>>>>>>>> Cheers
>>>>>>>>>>> Garren
>>>>>>>>>>> On Tue, Apr 16, 2019 at 2:41 AM Adam Kocoloski
>>>>>>>> wrote:
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>> For once, I’m coming to you with a topic
that is not strictly
>>>> about
>>>>>>>>>>>> FoundationDB :)
>>>>>>>>>>>> CouchDB offers a few config settings (some
of them
>>>> undocumented) to
>>>>>>>> put a
>>>>>>>>>>>> limit on how long the server is allowed to
take to generate a
>>>>>>>> response. The
>>>>>>>>>>>> trouble with many of these timeouts is that,
when they fire,
>>>> they do
>>>>>>>> not
>>>>>>>>>>>> actually clean up all of the work that they
initiated. A couple
>>>> of
>>>>>>>> examples:
>>>>>>>>>>>> - Each HTTP response coordinated by the “fabric”
>>>> spawns
>>>>>>>>>>>> several ephemeral processes via “rexi"
on different nodes in the
>>>>>>>> cluster to
>>>>>>>>>>>> retrieve data and send it back to the process
coordinating the
>>>>>>>> response. If
>>>>>>>>>>>> the request timeout fires, the coordinating
process will be
>>>> killed
>>>>>>>> off, but
>>>>>>>>>>>> the ephemeral workers might not be. In a
healthy cluster they’ll
>>>>>>>> exit on
>>>>>>>>>>>> their own when they finish their jobs, but
there are conditions
>>>>>>>> under which
>>>>>>>>>>>> they can sit around for extended periods
of time waiting for an
>>>>>>>> overloaded
>>>>>>>>>>>> gen_server (e.g. couch_server) to respond.
>>>>>>>>>>>> - Those named gen_servers (like couch_server)
responsible for
>>>>>>>> serializing
>>>>>>>>>>>> access to important data structures will
dutifully process
>>>> messages
>>>>>>>>>>>> received from old requests without any regard
for (of even
>>>> knowledge
>>>>>>>> of)
>>>>>>>>>>>> the fact that the client that sent the message
timed out long
>>>> ago.
>>>>>>>> This can
>>>>>>>>>>>> lead to a sort of death spiral in which the
gen_server is
>>>> ultimately
>>>>>>>>>>>> spending ~all of its time serving dead clients
and every client
>>>> is
>>>>>>>> timing
>>>>>>>>>>>> out.
>>>>>>>>>>>> I’d like to see us introduce a documented
maximum request
>>>> duration
>>>>>>>> for all
>>>>>>>>>>>> requests except the _changes feed, and then
use that
>>>> information to
>>>>>>>> aid in
>>>>>>>>>>>> load shedding throughout the stack. We can
audit the codebase
>>>> for
>>>>>>>>>>>> gen_server calls with long timeouts (I know
of a few on the
>>>> critical
>>>>>>>> path
>>>>>>>>>>>> that set their timeouts to `infinity`) and
we can design servers
>>>>>> that
>>>>>>>>>>>> efficiently drop old requests, knowing that
the client who made
>>>> the
>>>>>>>> request
>>>>>>>>>>>> must have timed out. A couple of topics for
>>>>>>>>>>>> - the “gen_server that sheds old requests”
is a very generic
>>>>>>>> pattern, one
>>>>>>>>>>>> that seems like it could be well-suited to
its own behaviour. A
>>>>>>>> cursory
>>>>>>>>>>>> search of the internet didn’t turn up any
prior art here, which
>>>>>>>> surprises
>>>>>>>>>>>> me a bit. I’m wondering if this is worth
bringing up with the
>>>>>> broader
>>>>>>>>>>>> Erlang community.
>>>>>>>>>>>> - setting and enforcing timeouts is a healthy
pattern for
>>>> read-only
>>>>>>>>>>>> requests as it gives a lot more feedback
to clients about the
>>>> health
>>>>>>>> of the
>>>>>>>>>>>> server. When it comes to updates things are
a little bit more
>>>> muddy,
>>>>>>>> just
>>>>>>>>>>>> because there remains a chance that an update
can be committed,
>>>> but
>>>>>>>> the
>>>>>>>>>>>> caller times out before learning of the successful
commit. We
>>>> should
>>>>>>>> try to
>>>>>>>>>>>> minimize the likelihood of that occurring.
>>>>>>>>>>>> Cheers, Adam
>>>>>>>>>>>> P.S. I did say that this wasn’t _strictly_
about FoundationDB,
>>>> but
>>>>>> of
>>>>>>>>>>>> course FDB has a hard 5 second limit on all
transactions, so it
>>>> is a
>>>>>>>> bit of
>>>>>>>>>>>> a forcing function :).Even putting FoundationDB
aside, I would
>>>> still
>>>>>>>> argue
>>>>>>>>>>>> to pursue this path based on our Ops experience
with the current
>>>>>>>> codebase.

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