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Thanks for the update and write up Arvid.
Piotrek Dear all,
I just wanted to follow-up on this long discussion thread by announcing
that we implemented unaligned checkpoints in Flink 1.11. If you experience
long end-to-end checkpointing duration, you should try out unaligned
checkpoints [1] if the following applies:
- Checkpointing is not bottlenecked by I/O (to state backend). Possible
reasons are: slow connections, rate limits, or huge operator or user state.
- You can attribute the long duration to slow data flow. An operator in
the pipeline is severely lagging behind and you can easily see it in Flink
Web UI.
- You cannot alleviate the problem by adjusting the degree of
parallelism to the slow operator, either because of temporal spikes or lags
or because you don’t control the application in a platform-as-a-service
architecture.
You can enable it in the flink-conf.yaml.
execution.checkpointing.unaligned: true
Or in your application:
env.getCheckpointConfig().enableUnalignedCheckpoints() (Java/Scala)
env.get_checkpoint_config().enable_unaligned_checkpoints() (Python)
Note that this relatively young feature still has a couple of limitations
that we resolve in future versions.
- You cannot rescale or change the job graph when starting from an
unaligned checkpoint; you have to take a savepoint before rescaling.
Savepoints are always aligned, independent of the alignment setting of
checkpoints. This feature has the highest priority and will be available in
upcoming releases.
- Flink currently does not support concurrent unaligned checkpoints.
However, due to the more predictable and shorter checkpointing times,
concurrent checkpoints might not be needed at all. However, savepoints can
also not happen concurrently to unaligned checkpoints, so they will take
slightly longer.
- SourceFunctions are user-defined, run a separate thread, and output
records under lock. When they block because of backpressure, the induced
checkpoints cannot acquire the lock and checkpointing duration increases.
We will provide SourceFunctions a way to also avoid blocking and implement
it for all sources in Flink core, but because the code is ultimately
user-defined, we have no way to guarantee non-blocking behavior.
Nevertheless, since only sources are affected, the checkpointing durations
are still much lower and most importantly do not increase with further
shuffles. Furthermore, Flink 1.11 also provides a new way to implement
sources (FLIP-27). This new source interface has a better threading model,
such that users do not create their own threads anymore and Flink can
guarantee non-blocking behavior for these sources.
- Unaligned checkpoints break with an implicit guarantee in respect to
watermarks during recovery. Currently, Flink generates the watermark as a
first step of recovery instead of storing the latest watermark in the
operators to ease rescaling. For unaligned checkpoints, this means that, on
recovery, Flink generates watermarks after it restores in-flight data. If
your pipeline uses an operator that applies the latest watermark on each
record, it will produce different results than for aligned checkpoints. If
your operator depends on the latest watermark being always available, then
the proper solution is to store the watermark in the operator state. To
support rescaling, watermarks should be stored per key-group in a
union-state. This feature has a high priority.
- Lastly, there is a conceptual weakness in unaligned checkpoints: when
an operator produces an arbitrary amount of outputs for a single input,
such as flatMap, all of these output records need to be stored into the
state for the unaligned checkpoint, which may increase the state size by
orders of magnitudes and slow down checkpointing and recovery. However,
since flatMap only needs alignment after a shuffle and rarely produces a
huge number of records for a single input, it’s more of a theoretic
problem.
Lastly, we also plan to improve the configurations, such that ultimately,
unaligned checkpoints will be the default configuration.
- Users will be able to configure a timeout, such that each operator
first tries to perform an aligned checkpoint. If the timeout is triggered,
it switches to an unaligned checkpoint. Since the timeout would only
trigger in the niche use cases that unaligned checkpoints addresses, it
would mostly perform an aligned checkpoint under no or low backpressure.
Thus, together with the previously mentioned fixes for the limitation, this
timeout would allow Flink to enable unaligned checkpoints by default.
- Another idea is to provide users to define a maximum state size for
the in-flight data. However, it might be hard for users to configure the
size correctly as it also requires to know how many buffers are used in the
respective application and it might be even harder to actually use the size
limit in a meaningful way.
- Lastly, to address the flatMap issue, there will be an option to
trigger the unaligned checkpoints on the last barrier of all input channels
instead of the first. Thus, there is still an alignment phase but it should
be rather quick as checkpoint barriers are still inserted at the head of
the output buffer queue. Conceptually, checkpoint barriers would still not
depend on the data flow.
We are currently preparing a blog post on this topic, from which I copied
some passages. We are happy to hear your feedback.
[1]
https://ci.apache.org/projects/flink/flink-docs-release-1.11/concepts/stateful-stream-processing.html#unaligned-checkpointing
On Wed, Dec 4, 2019 at 9:07 PM Thomas Weise <[hidden email]> wrote:
> Hi Arvid,
>
> Thanks for putting together the proposal [1]
>
> I'm planning to take a closer look in the next few days.
>
> Has any of the work been translated to JIRAs yet and what would be the
> approximate target release?
>
> Thanks,
> Thomas
>
>
> [1]
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-76%3A+Unaligned+Checkpoints
>
> On Wed, Oct 2, 2019 at 12:11 PM Arvid Heise <[hidden email]> wrote:
>
>> Sry incorrect link, please follow [1].
>>
>> [1]
>>
>> https://mail-archives.apache.org/mod_mbox/flink-dev/201909.mbox/%3CCAGZNd0FgVL0oDQJHpBwJ1Ha8QevsVG0FHixdet11tLhW2p-2hg%40mail.gmail.com%3E
>>
>> On Wed, Oct 2, 2019 at 3:44 PM Arvid Heise <[hidden email]> wrote:
>>
>> > FYI, we published FLIP-76 to address the issue and discussion has been
>> > opened in [1].
>> >
>> > Looking forward to your feedback,
>> >
>> > Arvid
>> >
>> > [1]
>> > https://mail-archives.apache.org/mod_mbox/flink-dev/201909.mbox/browser
>> >
>> > On Thu, Aug 15, 2019 at 9:43 AM Yun Gao <[hidden email]>
>> > wrote:
>> >
>> >> Hi,
>> >> Very thanks for the great points!
>> >>
>> >> For the prioritizing inputs, from another point of view, I think it
>> >> might not cause other bad effects, since we do not need to totally
>> block
>> >> the channels that have seen barriers after the operator has taking
>> >> snapshot. After the snapshotting, if the channels that has not seen
>> >> barriers have buffers, we could first logging and processing these
>> buffers
>> >> and if they do not have buffers, we can still processing the buffers
>> from
>> >> the channels that has seen barriers. Therefore, It seems prioritizing
>> >> inputs should be able to accelerate the checkpoint without other bad
>> >> effects.
>> >>
>> >> and @zhijiangFor making the unaligned checkpoint the only mechanism
>> >> for all cases, I still think we should allow a configurable timeout
>> after
>> >> receiving the first barrier so that the channels may get "drained"
>> during
>> >> the timeout, as pointed out by Stephan. With such a timeout, we are
>> very
>> >> likely not need to snapshot the input buffers, which would be very
>> similar
>> >> to the current aligned checkpoint mechanism.
>> >>
>> >> Best,
>> >> Yun
>> >>
>> >>
>> >> ------------------------------------------------------------------
>> >> From:zhijiang <[hidden email].INVALID>
>> >> Send Time:2019 Aug. 15 (Thu.) 02:22
>> >> To:dev <[hidden email]>
>> >> Subject:Re: Checkpointing under backpressure
>> >>
>> >> > For the checkpoint to complete, any buffer that
>> >> > arrived prior to the barrier would be to be part of the checkpointed
>> >> state.
>> >>
>> >> Yes, I agree.
>> >>
>> >> > So wouldn't it be important to finish persisting these buffers as
>> fast
>> >> as
>> >> > possible by prioritizing respective inputs? The task won't be able to
>> >> > process records from the inputs that have seen the barrier fast when
>> it
>> >> is
>> >> > already backpressured (or causing the backpressure).
>> >>
>> >> My previous understanding of prioritizing inputs is from task
>> processing
>> >> aspect after snapshot state. If from the persisting buffers aspect, I
>> think
>> >> it might be up to how we implement it.
>> >> If we only tag/reference which buffers in inputs be the part of state,
>> >> and make the real persisting work is done in async way. That means the
>> >> already tagged buffers could be processed by task w/o priority.
>> >> And only after all the persisting work done, the task would report to
>> >> coordinator of finished checkpoint on its side. The key point is how we
>> >> implement to make task could continue processing buffers as soon as
>> >> possible.
>> >>
>> >> Thanks for the further explannation of requirements for speeding up
>> >> checkpoints in backpressure scenario. To make the savepoint finish
>> quickly
>> >> and then tune the setting to avoid backpressure is really a pratical
>> case.
>> >> I think this solution could cover this concern.
>> >>
>> >> Best,
>> >> Zhijiang
>> >> ------------------------------------------------------------------
>> >> From:Thomas Weise <[hidden email]>
>> >> Send Time:2019年8月14日(星期三) 19:48
>> >> To:dev <[hidden email]>; zhijiang <[hidden email]>
>> >> Subject:Re: Checkpointing under backpressure
>> >>
>> >> -->
>> >>
>> >> On Wed, Aug 14, 2019 at 10:23 AM zhijiang
>> >> <[hidden email].invalid> wrote:
>> >>
>> >> > Thanks for these great points and disccusions!
>> >> >
>> >> > 1. Considering the way of triggering checkpoint RPC calls to all the
>> >> tasks
>> >> > from Chandy Lamport, it combines two different mechanisms together to
>> >> make
>> >> > sure that the trigger could be fast in different scenarios.
>> >> > But in flink world it might be not very worth trying that way, just
>> as
>> >> > Stephan's analysis for it. Another concern is that it might bring
>> more
>> >> > heavy loads for JobMaster broadcasting this checkpoint RPC to all the
>> >> tasks
>> >> > in large scale job, especially for the very short checkpoint
>> interval.
>> >> > Furthermore it would also cause other important RPC to be executed
>> >> delay to
>> >> > bring potentail timeout risks.
>> >> >
>> >> > 2. I agree with the idea of drawing on the way "take state snapshot
>> on
>> >> > first barrier" from Chandy Lamport instead of barrier alignment
>> >> combining
>> >> > with unaligned checkpoints in flink.
>> >> >
>> >> > > >>>> The benefit would be less latency increase in the channels
>> which
>> >> > already have received barriers.
>> >> > > >>>> However, as mentioned before, not prioritizing the inputs from
>> >> > which barriers are still missing can also have an adverse effect.
>> >> >
>> >> > I think we will not have an adverse effect if not prioritizing the
>> >> inputs
>> >> > w/o barriers in this case. After sync snapshot, the task could
>> actually
>> >> > process any input channels. For the input channel receiving the first
>> >> > barrier, we already have the obvious boundary for persisting buffers.
>> >> For
>> >> > other channels w/o barriers we could persist the following buffers
>> for
>> >> > these channels until barrier arrives in network. Because based on the
>> >> > credit based flow control, the barrier does not need credit to
>> >> transport,
>> >> > then as long as the sender overtakes the barrier accross the output
>> >> queue,
>> >> > the network stack would transport this barrier immediately no matter
>> >> with
>> >> > the inputs condition on receiver side. So there is no requirements to
>> >> > consume accumulated buffers in these channels for higher priority. If
>> >> so it
>> >> > seems that we will not waste any CPU cycles as Piotr concerns before.
>> >> >
>> >>
>> >> I'm not sure I follow this. For the checkpoint to complete, any buffer
>> >> that
>> >> arrived prior to the barrier would be to be part of the checkpointed
>> >> state.
>> >> So wouldn't it be important to finish persisting these buffers as fast
>> as
>> >> possible by prioritizing respective inputs? The task won't be able to
>> >> process records from the inputs that have seen the barrier fast when
>> it is
>> >> already backpressured (or causing the backpressure).
>> >>
>> >>
>> >> >
>> >> > 3. Suppose the unaligned checkpoints performing well in practice, is
>> it
>> >> > possible to make it as the only mechanism for handling all the
>> cases? I
>> >> > mean for the non-backpressure scenario, there are less buffers even
>> >> empty
>> >> > in input/output queue, then the "overtaking barrier--> trigger
>> snapshot
>> >> on
>> >> > first barrier--> persist buffers" might still work well. So we do not
>> >> need
>> >> > to maintain two suits of mechanisms finally.
>> >> >
>> >> > 4. The initial motivation of this dicussion is for checkpoint
>> timeout
>> >> in
>> >> > backpressure scenario. If we adjust the default timeout to a very big
>> >> > value, that means the checkpoint would never timeout and we only
>> need to
>> >> > wait it finish. Then are there still any other problems/concerns if
>> >> > checkpoint takes long time to finish? Althougn we already knew some
>> >> issues
>> >> > before, it is better to gather more user feedbacks to confirm which
>> >> aspects
>> >> > could be solved in this feature design. E.g. the sink commit delay
>> might
>> >> > not be coverd by unaligned solution.
>> >> >
>> >>
>> >> Checkpoints taking too long is the concern that sparks this discussion
>> >> (timeout is just a symptom). The slowness issue also applies to the
>> >> savepoint use case. We would need to be able to take a savepoint fast
>> in
>> >> order to roll forward a fix that can alleviate the backpressure (like
>> >> changing parallelism or making a different configuration change).
>> >>
>> >>
>> >> >
>> >> > Best,
>> >> > Zhijiang
>> >> > ------------------------------------------------------------------
>> >> > From:Stephan Ewen <[hidden email]>
>> >> > Send Time:2019年8月14日(星期三) 17:43
>> >> > To:dev <[hidden email]>
>> >> > Subject:Re: Checkpointing under backpressure
>> >> >
>> >> > Quick note: The current implementation is
>> >> >
>> >> > Align -> Forward -> Sync Snapshot Part (-> Async Snapshot Part)
>> >> >
>> >> > On Wed, Aug 14, 2019 at 5:21 PM Piotr Nowojski <[hidden email]>
>> >> > wrote:
>> >> >
>> >> > > > Thanks for the great ideas so far.
>> >> > >
>> >> > > +1
>> >> > >
>> >> > > Regarding other things raised, I mostly agree with Stephan.
>> >> > >
>> >> > > I like the idea of simultaneously starting the checkpoint
>> everywhere
>> >> via
>> >> > > RPC call (especially in cases where Tasks are busy doing some
>> >> synchronous
>> >> > > operations for example for tens of milliseconds. In that case every
>> >> > network
>> >> > > exchange adds tens of milliseconds of delay in propagating the
>> >> > checkpoint).
>> >> > > However I agree that this might be a premature optimisation
>> assuming
>> >> the
>> >> > > current state of our code (we already have checkpoint barriers).
>> >> > >
>> >> > > However I like the idea of switching from:
>> >> > >
>> >> > > 1. A -> S -> F (Align -> snapshot -> forward markers)
>> >> > >
>> >> > > To
>> >> > >
>> >> > > 2. S -> F -> L (Snapshot -> forward markers -> log pending
>> channels)
>> >> > >
>> >> > > Or even to
>> >> > >
>> >> > > 6. F -> S -> L (Forward markers -> snapshot -> log pending
>> channels)
>> >> > >
>> >> > > It feels to me like this would decouple propagation of checkpoints
>> >> from
>> >> > > costs of synchronous snapshots and waiting for all of the
>> checkpoint
>> >> > > barriers to arrive (even if they will overtake in-flight records,
>> this
>> >> > > might take some time).
>> >> > >
>> >> > > > What I like about the Chandy Lamport approach (2.) initiated from
>> >> > > sources is that:
>> >> > > > - Snapshotting imposes no modification to normal
>> processing.
>> >> > >
>> >> > > Yes, I agree that would be nice. Currently, during the alignment
>> and
>> >> > > blocking of the input channels, we might be wasting CPU cycles of
>> up
>> >> > stream
>> >> > > tasks. If we succeed in designing new checkpointing mechanism to
>> not
>> >> > > disrupt/block regular data processing (% the extra IO cost for
>> logging
>> >> > the
>> >> > > in-flight records), that would be a huge improvement.
>> >> > >
>> >> > > Piotrek
>> >> > >
>> >> > > > On 14 Aug 2019, at 14:56, Paris Carbone <[hidden email]
>> >
>> >> > wrote:
>> >> > > >
>> >> > > > Sure I see. In cases when no periodic aligned snapshots are
>> employed
>> >> > > this is the only option.
>> >> > > >
>> >> > > > Two things that were not highlighted enough so far on the
>> proposed
>> >> > > protocol (included my mails):
>> >> > > > - The Recovery/Reconfiguration strategy should strictly
>> >> > prioritise
>> >> > > processing logged events before entering normal task input
>> operation.
>> >> > > Otherwise causality can be violated. This also means dataflow
>> recovery
>> >> > will
>> >> > > be expected to be slower to the one employed on an aligned
>> snapshot.
>> >> > > > - Same as with state capture, markers should be forwarded
>> upon
>> >> > > first marker received on input. No later than that. Otherwise we
>> have
>> >> > > duplicate side effects.
>> >> > > >
>> >> > > > Thanks for the great ideas so far.
>> >> > > >
>> >> > > > Paris
>> >> > > >
>> >> > > >> On 14 Aug 2019, at 14:33, Stephan Ewen <[hidden email]>
>> wrote:
>> >> > > >>
>> >> > > >> Scaling with unaligned checkpoints might be a necessity.
>> >> > > >>
>> >> > > >> Let's assume the job failed due to a lost TaskManager, but no
>> new
>> >> > > >> TaskManager becomes available.
>> >> > > >> In that case we need to scale down based on the latest complete
>> >> > > checkpoint,
>> >> > > >> because we cannot produce a new checkpoint.
>> >> > > >>
>> >> > > >>
>> >> > > >> On Wed, Aug 14, 2019 at 2:05 PM Paris Carbone <
>> >> > [hidden email]>
>> >> > > >> wrote:
>> >> > > >>
>> >> > > >>> +1 I think we are on the same page Stephan.
>> >> > > >>>
>> >> > > >>> Rescaling on unaligned checkpoint sounds challenging and a bit
>> >> > > >>> unnecessary. No?
>> >> > > >>> Why not sticking to aligned snapshots for live
>> >> > > reconfiguration/rescaling?
>> >> > > >>> It’s a pretty rare operation and it would simplify things by a
>> >> lot.
>> >> > > >>> Everything can be “staged” upon alignment including replacing
>> >> > channels
>> >> > > and
>> >> > > >>> tasks.
>> >> > > >>>
>> >> > > >>> -Paris
>> >> > > >>>
>> >> > > >>>> On 14 Aug 2019, at 13:39, Stephan Ewen <[hidden email]>
>> wrote:
>> >> > > >>>>
>> >> > > >>>> Hi all!
>> >> > > >>>>
>> >> > > >>>> Yes, the first proposal of "unaligend checkpoints" (probably
>> two
>> >> > years
>> >> > > >>> back
>> >> > > >>>> now) drew a major inspiration from Chandy Lamport, as did
>> >> actually
>> >> > the
>> >> > > >>>> original checkpointing algorithm.
>> >> > > >>>>
>> >> > > >>>> "Logging data between first and last barrier" versus "barrier
>> >> > jumping
>> >> > > >>> over
>> >> > > >>>> buffer and storing those buffers" is pretty close same.
>> >> > > >>>> However, there are a few nice benefits of the proposal of
>> >> unaligned
>> >> > > >>>> checkpoints over Chandy-Lamport.
>> >> > > >>>>
>> >> > > >>>> *## Benefits of Unaligned Checkpoints*
>> >> > > >>>>
>> >> > > >>>> (1) It is very similar to the original algorithm (can be seen
>> an
>> >> an
>> >> > > >>>> optional feature purely in the network stack) and thus can
>> share
>> >> > > lot's of
>> >> > > >>>> code paths.
>> >> > > >>>>
>> >> > > >>>> (2) Less data stored. If we make the "jump over buffers" part
>> >> > timeout
>> >> > > >>> based
>> >> > > >>>> (for example barrier overtakes buffers if not flushed within
>> >> 10ms)
>> >> > > then
>> >> > > >>>> checkpoints are in the common case of flowing pipelines
>> aligned
>> >> > > without
>> >> > > >>>> in-flight data. Only back pressured cases store some in-flight
>> >> data,
>> >> > > >>> which
>> >> > > >>>> means we don't regress in the common case and only fix the
>> back
>> >> > > pressure
>> >> > > >>>> case.
>> >> > > >>>>
>> >> > > >>>> (3) Faster checkpoints. Chandy Lamport still waits for all
>> >> barriers
>> >> > to
>> >> > > >>>> arrive naturally, logging on the way. If data processing is
>> slow,
>> >> > this
>> >> > > >>> can
>> >> > > >>>> still take quite a while.
>> >> > > >>>>
>> >> > > >>>> ==> I think both these points are strong reasons to not change
>> >> the
>> >> > > >>>> mechanism away from "trigger sources" and start with CL-style
>> >> > "trigger
>> >> > > >>> all".
>> >> > > >>>>
>> >> > > >>>>
>> >> > > >>>> *## Possible ways to combine Chandy Lamport and Unaligned
>> >> > Checkpoints*
>> >> > > >>>>
>> >> > > >>>> We can think about something like "take state snapshot on
>> first
>> >> > > barrier"
>> >> > > >>>> and then store buffers until the other barriers arrive. Inside
>> >> the
>> >> > > >>> network
>> >> > > >>>> stack, barriers could still overtake and persist buffers.
>> >> > > >>>> The benefit would be less latency increase in the channels
>> which
>> >> > > already
>> >> > > >>>> have received barriers.
>> >> > > >>>> However, as mentioned before, not prioritizing the inputs from
>> >> which
>> >> > > >>>> barriers are still missing can also have an adverse effect.
>> >> > > >>>>
>> >> > > >>>>
>> >> > > >>>> *## Concerning upgrades*
>> >> > > >>>>
>> >> > > >>>> I think it is a fair restriction to say that upgrades need to
>> >> happen
>> >> > > on
>> >> > > >>>> aligned checkpoints. It is a rare enough operation.
>> >> > > >>>>
>> >> > > >>>>
>> >> > > >>>> *## Concerning re-scaling (changing parallelism)*
>> >> > > >>>>
>> >> > > >>>> We need to support that on unaligned checkpoints as well.
>> There
>> >> are
>> >> > > >>> several
>> >> > > >>>> feature proposals about automatic scaling, especially down
>> >> scaling
>> >> > in
>> >> > > >>> case
>> >> > > >>>> of missing resources. The last snapshot might be a regular
>> >> > > checkpoint, so
>> >> > > >>>> all checkpoints need to support rescaling.
>> >> > > >>>>
>> >> > > >>>>
>> >> > > >>>> *## Concerning end-to-end checkpoint duration and "trigger
>> >> sources"
>> >> > > >>> versus
>> >> > > >>>> "trigger all"*
>> >> > > >>>>
>> >> > > >>>> I think for the end-to-end checkpoint duration, an "overtake
>> >> > buffers"
>> >> > > >>>> approach yields faster checkpoints, as mentioned above (Chandy
>> >> > Lamport
>> >> > > >>>> logging still needs to wait for barrier to flow).
>> >> > > >>>>
>> >> > > >>>> I don't see the benefit of a "trigger all tasks via RPC
>> >> > concurrently"
>> >> > > >>>> approach. Bear in mind that it is still a globally coordinated
>> >> > > approach
>> >> > > >>> and
>> >> > > >>>> you need to wait for the global checkpoint to complete before
>> >> > > committing
>> >> > > >>>> any side effects.
>> >> > > >>>> I believe that the checkpoint time is more determined by the
>> >> state
>> >> > > >>>> checkpoint writing, and the global coordination and metadata
>> >> commit,
>> >> > > than
>> >> > > >>>> by the difference in alignment time between "trigger from
>> source
>> >> and
>> >> > > jump
>> >> > > >>>> over buffers" versus "trigger all tasks concurrently".
>> >> > > >>>>
>> >> > > >>>> Trying to optimize a few tens of milliseconds out of the
>> network
>> >> > stack
>> >> > > >>>> sends (and changing the overall checkpointing approach
>> completely
>> >> > for
>> >> > > >>> that)
>> >> > > >>>> while staying with a globally coordinated checkpoint will
>> send us
>> >> > > down a
>> >> > > >>>> path to a dead end.
>> >> > > >>>>
>> >> > > >>>> To really bring task persistence latency down to 10s of
>> >> milliseconds
>> >> > > (so
>> >> > > >>> we
>> >> > > >>>> can frequently commit in sinks), we need to take an approach
>> >> without
>> >> > > any
>> >> > > >>>> global coordination. Tasks need to establish a persistent
>> >> recovery
>> >> > > point
>> >> > > >>>> individually and at their own discretion, only then can it be
>> >> > frequent
>> >> > > >>>> enough. To get there, they would need to decouple themselves
>> from
>> >> > the
>> >> > > >>>> predecessor and successor tasks (via something like persistent
>> >> > > channels).
>> >> > > >>>> This is a different discussion, though, somewhat orthogonal to
>> >> this
>> >> > > one
>> >> > > >>>> here.
>> >> > > >>>>
>> >> > > >>>> Best,
>> >> > > >>>> Stephan
>> >> > > >>>>
>> >> > > >>>>
>> >> > > >>>> On Wed, Aug 14, 2019 at 12:37 PM Piotr Nowojski <
>> >> > [hidden email]>
>> >> > > >>> wrote:
>> >> > > >>>>
>> >> > > >>>>> Hi again,
>> >> > > >>>>>
>> >> > > >>>>> Zhu Zhu let me think about this more. Maybe as Paris is
>> >> writing, we
>> >> > > do
>> >> > > >>> not
>> >> > > >>>>> need to block any channels at all, at least assuming credit
>> base
>> >> > flow
>> >> > > >>>>> control. Regarding what should happen with the following
>> >> checkpoint
>> >> > > is
>> >> > > >>>>> another question. Also, should we support concurrent
>> checkpoints
>> >> > and
>> >> > > >>>>> subsuming checkpoints as we do now? Maybe not…
>> >> > > >>>>>
>> >> > > >>>>> Paris
>> >> > > >>>>>
>> >> > > >>>>> Re
>> >> > > >>>>> I. 2. a) and b) - yes, this would have to be taken into an
>> >> account
>> >> > > >>>>> I. 2. c) and IV. 2. - without those, end to end checkpoint
>> time
>> >> > will
>> >> > > >>>>> probably be longer than it could be. It might affect external
>> >> > > systems.
>> >> > > >>> For
>> >> > > >>>>> example Kafka, which automatically time outs lingering
>> >> > transactions,
>> >> > > and
>> >> > > >>>>> for us, the transaction time is equal to the time between two
>> >> > > >>> checkpoints.
>> >> > > >>>>>
>> >> > > >>>>> II 1. - I’m confused. To make things straight. Flink is
>> >> currently
>> >> > > >>>>> snapshotting once it receives all of the checkpoint barriers
>> >> from
>> >> > > all of
>> >> > > >>>>> the input channels and only then it broadcasts the checkpoint
>> >> > barrier
>> >> > > >>> down
>> >> > > >>>>> the stream. And this is correct from exactly-once
>> perspective.
>> >> > > >>>>>
>> >> > > >>>>> As far as I understand, your proposal based on Chandy Lamport
>> >> > > algorithm,
>> >> > > >>>>> is snapshotting the state of the operator on the first
>> >> checkpoint
>> >> > > >>> barrier,
>> >> > > >>>>> which also looks correct to me.
>> >> > > >>>>>
>> >> > > >>>>> III. 1. As I responded to Zhu Zhu, let me think a bit more
>> about
>> >> > > this.
>> >> > > >>>>>
>> >> > > >>>>> V. Yes, we still need aligned checkpoints, as they are easier
>> >> for
>> >> > > state
>> >> > > >>>>> migration and upgrades.
>> >> > > >>>>>
>> >> > > >>>>> Piotrek
>> >> > > >>>>>
>> >> > > >>>>>> On 14 Aug 2019, at 11:22, Paris Carbone <
>> >> [hidden email]>
>> >> > > >>> wrote:
>> >> > > >>>>>>
>> >> > > >>>>>> Now I see a little more clearly what you have in mind.
>> Thanks
>> >> for
>> >> > > the
>> >> > > >>>>> explanation!
>> >> > > >>>>>> There are a few intermixed concepts here, some how to do
>> with
>> >> > > >>>>> correctness some with performance.
>> >> > > >>>>>> Before delving deeper I will just enumerate a few things to
>> >> make
>> >> > > myself
>> >> > > >>>>> a little more helpful if I can.
>> >> > > >>>>>>
>> >> > > >>>>>> I. Initiation
>> >> > > >>>>>> -------------
>> >> > > >>>>>>
>> >> > > >>>>>> 1. RPC to sources only is a less intrusive way to initiate
>> >> > snapshots
>> >> > > >>>>> since you utilize better pipeline parallelism (only a small
>> >> subset
>> >> > of
>> >> > > >>> tasks
>> >> > > >>>>> is running progressively the protocol at a time, if
>> >> snapshotting is
>> >> > > >>> async
>> >> > > >>>>> the overall overhead might not even be observable).
>> >> > > >>>>>>
>> >> > > >>>>>> 2. If we really want an RPC to all initiation take notice of
>> >> the
>> >> > > >>>>> following implications:
>> >> > > >>>>>>
>> >> > > >>>>>> a. (correctness) RPC calls are not guaranteed to arrive
>> in
>> >> > every
>> >> > > >>>>> task before a marker from a preceding task.
>> >> > > >>>>>>
>> >> > > >>>>>> b. (correctness) Either the RPC call OR the first
>> arriving
>> >> > marker
>> >> > > >>>>> should initiate the algorithm. Whichever comes first. If you
>> >> only
>> >> > do
>> >> > > it
>> >> > > >>> per
>> >> > > >>>>> RPC call then you capture a "late" state that includes side
>> >> effects
>> >> > > of
>> >> > > >>>>> already logged events.
>> >> > > >>>>>>
>> >> > > >>>>>> c. (performance) Lots of IO will be invoked at the same
>> >> time on
>> >> > > >>>>> the backend store from all tasks. This might lead to high
>> >> > congestion
>> >> > > in
>> >> > > >>>>> async snapshots.
>> >> > > >>>>>>
>> >> > > >>>>>> II. Capturing State First
>> >> > > >>>>>> -------------------------
>> >> > > >>>>>>
>> >> > > >>>>>> 1. (correctness) Capturing state at the last marker sounds
>> >> > > incorrect to
>> >> > > >>>>> me (state contains side effects of already logged events
>> based
>> >> on
>> >> > the
>> >> > > >>>>> proposed scheme). This results into duplicate processing. No?
>> >> > > >>>>>>
>> >> > > >>>>>> III. Channel Blocking / "Alignment"
>> >> > > >>>>>> -----------------------------------
>> >> > > >>>>>>
>> >> > > >>>>>> 1. (performance?) What is the added benefit? We dont want a
>> >> > > "complete"
>> >> > > >>>>> transactional snapshot, async snapshots are purely for
>> >> > > failure-recovery.
>> >> > > >>>>> Thus, I dont see why this needs to be imposed at the expense
>> of
>> >> > > >>>>> performance/throughput. With the proposed scheme the whole
>> >> dataflow
>> >> > > >>> anyway
>> >> > > >>>>> enters snapshotting/logging mode so tasks more or less
>> snapshot
>> >> > > >>>>> concurrently.
>> >> > > >>>>>>
>> >> > > >>>>>> IV Marker Bypassing
>> >> > > >>>>>> -------------------
>> >> > > >>>>>>
>> >> > > >>>>>> 1. (correctness) This leads to equivalent in-flight
>> snapshots
>> >> so
>> >> > > with
>> >> > > >>>>> some quick thinking correct. I will try to model this later
>> and
>> >> > get
>> >> > > >>> back
>> >> > > >>>>> to you in case I find something wrong.
>> >> > > >>>>>>
>> >> > > >>>>>> 2. (performance) It also sounds like a meaningful
>> >> optimisation! I
>> >> > > like
>> >> > > >>>>> thinking of this as a push-based snapshot. i.e., the
>> producing
>> >> task
>> >> > > >>> somehow
>> >> > > >>>>> triggers forward a consumer/channel to capture its state. By
>> >> > example
>> >> > > >>>>> consider T1 -> |marker t1| -> T2.
>> >> > > >>>>>>
>> >> > > >>>>>> V. Usage of "Async" Snapshots
>> >> > > >>>>>> ---------------------
>> >> > > >>>>>>
>> >> > > >>>>>> 1. Do you see this as a full replacement of "full" aligned
>> >> > > >>>>> snapshots/savepoints? In my view async shanpshots will be
>> needed
>> >> > from
>> >> > > >>> time
>> >> > > >>>>> to time but not as frequently. Yet, it seems like a valid
>> >> approach
>> >> > > >>> solely
>> >> > > >>>>> for failure-recovery on the same configuration. Here's why:
>> >> > > >>>>>>
>> >> > > >>>>>> a. With original snapshotting there is a strong duality
>> >> between
>> >> > > >>>>>> a stream input (offsets) and committed side effects
>> >> (internal
>> >> > > >>>>> states and external commits to transactional sinks). While in
>> >> the
>> >> > > async
>> >> > > >>>>> version, there are uncommitted operations (inflight records).
>> >> Thus,
>> >> > > you
>> >> > > >>>>> cannot use these snapshots for e.g., submitting sql queries
>> with
>> >> > > >>> snapshot
>> >> > > >>>>> isolation. Also, the original snapshotting gives a lot of
>> >> potential
>> >> > > for
>> >> > > >>>>> flink to make proper transactional commits externally.
>> >> > > >>>>>>
>> >> > > >>>>>> b. Reconfiguration is very tricky, you probably know that
>> >> > better.
>> >> > > >>>>> Inflight channel state is no longer valid in a new
>> configuration
>> >> > > (i.e.,
>> >> > > >>> new
>> >> > > >>>>> dataflow graph, new operators, updated operator logic,
>> different
>> >> > > >>> channels,
>> >> > > >>>>> different parallelism)
>> >> > > >>>>>>
>> >> > > >>>>>> 2. Async snapshots can also be potentially useful for
>> >> monitoring
>> >> > the
>> >> > > >>>>> general health of a dataflow since they can be analyzed by
>> the
>> >> task
>> >> > > >>> manager
>> >> > > >>>>> about the general performance of a job graph and spot
>> >> bottlenecks
>> >> > for
>> >> > > >>>>> example.
>> >> > > >>>>>>
>> >> > > >>>>>>> On 14 Aug 2019, at 09:08, Piotr Nowojski <
>> [hidden email]
>> >> >
>> >> > > wrote:
>> >> > > >>>>>>>
>> >> > > >>>>>>> Hi,
>> >> > > >>>>>>>
>> >> > > >>>>>>> Thomas:
>> >> > > >>>>>>> There are no Jira tickets yet (or maybe there is something
>> >> very
>> >> > old
>> >> > > >>>>> somewhere). First we want to discuss it, next present FLIP
>> and
>> >> at
>> >> > > last
>> >> > > >>>>> create tickets :)
>> >> > > >>>>>>>
>> >> > > >>>>>>>> if I understand correctly, then the proposal is to not
>> block
>> >> any
>> >> > > >>>>>>>> input channel at all, but only log data from the
>> >> backpressured
>> >> > > >>> channel
>> >> > > >>>>> (and
>> >> > > >>>>>>>> make it part of the snapshot) until the barrier arrives
>> >> > > >>>>>>>
>> >> > > >>>>>>> I would guess that it would be better to block the reads,
>> >> unless
>> >> > we
>> >> > > >>> can
>> >> > > >>>>> already process the records from the blocked channel…
>> >> > > >>>>>>>
>> >> > > >>>>>>> Paris:
>> >> > > >>>>>>>
>> >> > > >>>>>>> Thanks for the explanation Paris. I’m starting to
>> understand
>> >> this
>> >> > > more
>> >> > > >>>>> and I like the idea of snapshotting the state of an operator
>> >> before
>> >> > > >>>>> receiving all of the checkpoint barriers - this would allow
>> more
>> >> > > things
>> >> > > >>> to
>> >> > > >>>>> happen at the same time instead of sequentially. As Zhijiang
>> has
>> >> > > pointed
>> >> > > >>>>> out there are some things not considered in your proposal:
>> >> > overtaking
>> >> > > >>>>> output buffers, but maybe those things could be incorporated
>> >> > > together.
>> >> > > >>>>>>>
>> >> > > >>>>>>> Another thing is that from the wiki description I
>> understood
>> >> that
>> >> > > the
>> >> > > >>>>> initial checkpointing is not initialised by any checkpoint
>> >> barrier,
>> >> > > but
>> >> > > >>> by
>> >> > > >>>>> an independent call/message from the Observer. I haven’t
>> played
>> >> > with
>> >> > > >>> this
>> >> > > >>>>> idea a lot, but I had some discussion with Nico and it seems
>> >> that
>> >> > it
>> >> > > >>> might
>> >> > > >>>>> work:
>> >> > > >>>>>>>
>> >> > > >>>>>>> 1. JobManager sends and RPC “start checkpoint” to all tasks
>> >> > > >>>>>>> 2. Task (with two input channels l1 and l2) upon receiving
>> RPC
>> >> > from
>> >> > > >>> 1.,
>> >> > > >>>>> takes a snapshot of it's state and:
>> >> > > >>>>>>> a) broadcast checkpoint barrier down the stream to all
>> >> channels
>> >> > > (let’s
>> >> > > >>>>> ignore for a moment potential for this barrier to overtake
>> the
>> >> > buffer
>> >> > > >>>>> output data)
>> >> > > >>>>>>> b) for any input channel for which it hasn’t yet received
>> >> > > checkpoint
>> >> > > >>>>> barrier, the data are being added to the checkpoint
>> >> > > >>>>>>> c) once a channel (for example l1) receives a checkpoint
>> >> barrier,
>> >> > > the
>> >> > > >>>>> Task blocks reads from that channel (?)
>> >> > > >>>>>>> d) after all remaining channels (l2) receive checkpoint
>> >> barriers,
>> >> > > the
>> >> > > >>>>> Task first has to process the buffered data after that it
>> can
>> >> > > unblock
>> >> > > >>> the
>> >> > > >>>>> reads from the channels
>> >> > > >>>>>>>
>> >> > > >>>>>>> Checkpoint barriers do not cascade/flow through different
>> >> tasks
>> >> > > here.
>> >> > > >>>>> Checkpoint barrier emitted from Task1, reaches only the
>> >> immediate
>> >> > > >>>>> downstream Tasks. Thanks to this setup, total checkpointing
>> >> time is
>> >> > > not
>> >> > > >>> sum
>> >> > > >>>>> of checkpointing times of all Tasks one by one, but more or
>> less
>> >> > max
>> >> > > of
>> >> > > >>> the
>> >> > > >>>>> slowest Tasks. Right?
>> >> > > >>>>>>>
>> >> > > >>>>>>> Couple of intriguing thoughts are:
>> >> > > >>>>>>> 3. checkpoint barriers overtaking the output buffers
>> >> > > >>>>>>> 4. can we keep processing some data (in order to not waste
>> CPU
>> >> > > cycles)
>> >> > > >>>>> after we have taking the snapshot of the Task. I think we
>> could.
>> >> > > >>>>>>>
>> >> > > >>>>>>> Piotrek
>> >> > > >>>>>>>
>> >> > > >>>>>>>> On 14 Aug 2019, at 06:00, Thomas Weise <[hidden email]>
>> >> wrote:
>> >> > > >>>>>>>>
>> >> > > >>>>>>>> Great discussion! I'm excited that this is already under
>> >> > > >>>>> consideration! Are
>> >> > > >>>>>>>> there any JIRAs or other traces of discussion to follow?
>> >> > > >>>>>>>>
>> >> > > >>>>>>>> Paris, if I understand correctly, then the proposal is to
>> not
>> >> > > block
>> >> > > >>> any
>> >> > > >>>>>>>> input channel at all, but only log data from the
>> >> backpressured
>> >> > > >>> channel
>> >> > > >>>>> (and
>> >> > > >>>>>>>> make it part of the snapshot) until the barrier arrives?
>> >> This is
>> >> > > >>>>>>>> intriguing. But probably there is also a benefit of to not
>> >> > > continue
>> >> > > >>>>> reading
>> >> > > >>>>>>>> I1 since that could speed up retrieval from I2. Also, if
>> the
>> >> > user
>> >> > > >>> code
>> >> > > >>>>> is
>> >> > > >>>>>>>> the cause of backpressure, this would avoid pumping more
>> data
>> >> > into
>> >> > > >>> the
>> >> > > >>>>>>>> process function.
>> >> > > >>>>>>>>
>> >> > > >>>>>>>> Thanks,
>> >> > > >>>>>>>> Thomas
>> >> > > >>>>>>>>
>> >> > > >>>>>>>>
>> >> > > >>>>>>>> On Tue, Aug 13, 2019 at 8:02 AM zhijiang <
>> >> > > [hidden email]
>> >> > > >>>>> .invalid>
>> >> > > >>>>>>>> wrote:
>> >> > > >>>>>>>>
>> >> > > >>>>>>>>> Hi Paris,
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> Thanks for the detailed sharing. And I think it is very
>> >> similar
>> >> > > with
>> >> > > >>>>> the
>> >> > > >>>>>>>>> way of overtaking we proposed before.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> There are some tiny difference:
>> >> > > >>>>>>>>> The way of overtaking might need to snapshot all the
>> >> > input/output
>> >> > > >>>>> queues.
>> >> > > >>>>>>>>> Chandy Lamport seems only need to snaphost (n-1) input
>> >> channels
>> >> > > >>> after
>> >> > > >>>>> the
>> >> > > >>>>>>>>> first barrier arrives, which might reduce the state sizea
>> >> bit.
>> >> > > But
>> >> > > >>>>> normally
>> >> > > >>>>>>>>> there should be less buffers for the first input channel
>> >> with
>> >> > > >>> barrier.
>> >> > > >>>>>>>>> The output barrier still follows with regular data
>> stream in
>> >> > > Chandy
>> >> > > >>>>>>>>> Lamport, the same way as current flink. For overtaking
>> way,
>> >> we
>> >> > > need
>> >> > > >>>>> to pay
>> >> > > >>>>>>>>> extra efforts to make barrier transport firstly before
>> >> outque
>> >> > > queue
>> >> > > >>> on
>> >> > > >>>>>>>>> upstream side, and change the way of barrier alignment
>> >> based on
>> >> > > >>>>> receiving
>> >> > > >>>>>>>>> instead of current reading on downstream side.
>> >> > > >>>>>>>>> In the backpressure caused by data skew, the first
>> barrier
>> >> in
>> >> > > almost
>> >> > > >>>>> empty
>> >> > > >>>>>>>>> input channel should arrive much eariler than the last
>> heavy
>> >> > load
>> >> > > >>>>> input
>> >> > > >>>>>>>>> channel, so the Chandy Lamport could benefit well. But
>> for
>> >> the
>> >> > > case
>> >> > > >>>>> of all
>> >> > > >>>>>>>>> balanced heavy load input channels, I mean the first
>> arrived
>> >> > > barrier
>> >> > > >>>>> might
>> >> > > >>>>>>>>> still take much time, then the overtaking way could still
>> >> fit
>> >> > > well
>> >> > > >>> to
>> >> > > >>>>> speed
>> >> > > >>>>>>>>> up checkpoint.
>> >> > > >>>>>>>>> Anyway, your proposed suggestion is helpful on my side,
>> >> > > especially
>> >> > > >>>>>>>>> considering some implementation details .
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> Best,
>> >> > > >>>>>>>>> Zhijiang
>> >> > > >>>>>>>>>
>> >> > > ------------------------------------------------------------------
>> >> > > >>>>>>>>> From:Paris Carbone <[hidden email]>
>> >> > > >>>>>>>>> Send Time:2019年8月13日(星期二) 14:03
>> >> > > >>>>>>>>> To:dev <[hidden email]>
>> >> > > >>>>>>>>> Cc:zhijiang <[hidden email]>
>> >> > > >>>>>>>>> Subject:Re: Checkpointing under backpressure
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> yes! It’s quite similar I think. Though mind that the
>> >> devil is
>> >> > > in
>> >> > > >>> the
>> >> > > >>>>>>>>> details, i.e., the temporal order actions are taken.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> To clarify, let us say you have a task T with two input
>> >> > channels
>> >> > > I1
>> >> > > >>>>> and I2.
>> >> > > >>>>>>>>> The Chandy Lamport execution flow is the following:
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> 1) T receives barrier from I1 and...
>> >> > > >>>>>>>>> 2) ...the following three actions happen atomically
>> >> > > >>>>>>>>> I ) T snapshots its state T*
>> >> > > >>>>>>>>> II) T forwards marker to its outputs
>> >> > > >>>>>>>>> III) T starts logging all events of I2 (only) into a
>> buffer
>> >> M*
>> >> > > >>>>>>>>> - Also notice here that T does NOT block I1 as it does in
>> >> > aligned
>> >> > > >>>>>>>>> snapshots -
>> >> > > >>>>>>>>> 3) Eventually T receives barrier from I2 and stops
>> recording
>> >> > > events.
>> >> > > >>>>> Its
>> >> > > >>>>>>>>> asynchronously captured snapshot is now complete:
>> {T*,M*}.
>> >> > > >>>>>>>>> Upon recovery all messages of M* should be replayed in
>> FIFO
>> >> > > order.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> With this approach alignment does not create a deadlock
>> >> > situation
>> >> > > >>>>> since
>> >> > > >>>>>>>>> anyway 2.II happens asynchronously and messages can be
>> >> logged
>> >> > as
>> >> > > >>> well
>> >> > > >>>>>>>>> asynchronously during the process of the snapshot. If
>> there
>> >> is
>> >> > > >>>>>>>>> back-pressure in a pipeline the cause is most probably
>> not
>> >> this
>> >> > > >>>>> algorithm.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> Back to your observation, the answer : yes and no. In
>> your
>> >> > > network
>> >> > > >>>>> model,
>> >> > > >>>>>>>>> I can see the logic of “logging” and “committing” a final
>> >> > > snapshot
>> >> > > >>>>> being
>> >> > > >>>>>>>>> provided by the channel implementation. However, do mind
>> >> that
>> >> > the
>> >> > > >>>>> first
>> >> > > >>>>>>>>> barrier always needs to go “all the way” to initiate the
>> >> Chandy
>> >> > > >>>>> Lamport
>> >> > > >>>>>>>>> algorithm logic.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> The above flow has been proven using temporal logic in my
>> >> phd
>> >> > > thesis
>> >> > > >>>>> in
>> >> > > >>>>>>>>> case you are interested about the proof.
>> >> > > >>>>>>>>> I hope this helps a little clarifying things. Let me
>> know if
>> >> > > there
>> >> > > >>> is
>> >> > > >>>>> any
>> >> > > >>>>>>>>> confusing point to disambiguate. I would be more than
>> happy
>> >> to
>> >> > > help
>> >> > > >>>>> if I
>> >> > > >>>>>>>>> can.
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>> Paris
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>>> On 13 Aug 2019, at 13:28, Piotr Nowojski <
>> >> [hidden email]
>> >> > >
>> >> > > >>>>> wrote:
>> >> > > >>>>>>>>>>
>> >> > > >>>>>>>>>> Thanks for the input. Regarding the Chandy-Lamport
>> >> snapshots
>> >> > > don’t
>> >> > > >>>>> you
>> >> > > >>>>>>>>> still have to wait for the “checkpoint barrier” to
>> arrive in
>> >> > > order
>> >> > > >>> to
>> >> > > >>>>> know
>> >> > > >>>>>>>>> when have you already received all possible messages from
>> >> the
>> >> > > >>> upstream
>> >> > > >>>>>>>>> tasks/operators? So instead of processing the “in flight”
>> >> > > messages
>> >> > > >>>>> (as the
>> >> > > >>>>>>>>> Flink is doing currently), you are sending them to an
>> >> > “observer”?
>> >> > > >>>>>>>>>>
>> >> > > >>>>>>>>>> In that case, that’s sounds similar to “checkpoint
>> barriers
>> >> > > >>>>> overtaking
>> >> > > >>>>>>>>> in flight records” (aka unaligned checkpoints). Just for
>> us,
>> >> > the
>> >> > > >>>>> observer
>> >> > > >>>>>>>>> is a snapshot state.
>> >> > > >>>>>>>>>>
>> >> > > >>>>>>>>>> Piotrek
>> >> > > >>>>>>>>>>
>> >> > > >>>>>>>>>>> On 13 Aug 2019, at 13:14, Paris Carbone <
>> >> > > [hidden email]>
>> >> > > >>>>>>>>> wrote:
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> Interesting problem! Thanks for bringing it up Thomas.
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> Ignore/Correct me if I am wrong but I believe
>> >> Chandy-Lamport
>> >> > > >>>>> snapshots
>> >> > > >>>>>>>>> [1] would help out solve this problem more elegantly
>> without
>> >> > > >>>>> sacrificing
>> >> > > >>>>>>>>> correctness.
>> >> > > >>>>>>>>>>> - They do not need alignment, only (async) logging for
>> >> > > in-flight
>> >> > > >>>>>>>>> records between the time the first barrier is processed
>> >> until
>> >> > the
>> >> > > >>> last
>> >> > > >>>>>>>>> barrier arrives in a task.
>> >> > > >>>>>>>>>>> - They work fine for failure recovery as long as logged
>> >> > records
>> >> > > >>> are
>> >> > > >>>>>>>>> replayed on startup.
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> Flink’s “alligned” savepoints would probably be still
>> >> > necessary
>> >> > > >>> for
>> >> > > >>>>>>>>> transactional sink commits + any sort of reconfiguration
>> >> (e.g.,
>> >> > > >>>>> rescaling,
>> >> > > >>>>>>>>> updating the logic of operators to evolve an application
>> >> etc.).
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> I don’t completely understand the “overtaking” approach
>> >> but
>> >> > if
>> >> > > you
>> >> > > >>>>> have
>> >> > > >>>>>>>>> a concrete definition I would be happy to check it out
>> and
>> >> help
>> >> > > if I
>> >> > > >>>>> can!
>> >> > > >>>>>>>>>>> Mind that Chandy-Lamport essentially does this by
>> logging
>> >> > > things
>> >> > > >>> in
>> >> > > >>>>>>>>> pending channels in a task snapshot before the barrier
>> >> arrives.
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> -Paris
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>> [1]
>> >> > > >>> https://en.wikipedia.org/wiki/Chandy%E2%80%93Lamport_algorithm
>> >> > > >>>>> <
>> >> > > >>>>>>>>>
>> >> https://en.wikipedia.org/wiki/Chandy%E2%80%93Lamport_algorithm
>> >> > >
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>>> On 13 Aug 2019, at 10:27, Piotr Nowojski <
>> >> > [hidden email]
>> >> > > >
>> >> > > >>>>> wrote:
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>> Hi Thomas,
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>> As Zhijiang has responded, we are now in the process
>> of
>> >> > > >>> discussing
>> >> > > >>>>> how
>> >> > > >>>>>>>>> to address this issue and one of the solution that we are
>> >> > > discussing
>> >> > > >>>>> is
>> >> > > >>>>>>>>> exactly what you are proposing: checkpoint barriers
>> >> overtaking
>> >> > > the
>> >> > > >>> in
>> >> > > >>>>>>>>> flight data and make the in flight data part of the
>> >> checkpoint.
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>> If everything works well, we will be able to present
>> >> result
>> >> > of
>> >> > > >>> our
>> >> > > >>>>>>>>> discussions on the dev mailing list soon.
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>> Piotrek
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> On 12 Aug 2019, at 23:23, zhijiang <
>> >> > > [hidden email]
>> >> > > >>>>> .INVALID>
>> >> > > >>>>>>>>> wrote:
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Hi Thomas,
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Thanks for proposing this concern. The barrier
>> alignment
>> >> > > takes
>> >> > > >>>>> long
>> >> > > >>>>>>>>> time in backpressure case which could cause several
>> >> problems:
>> >> > > >>>>>>>>>>>>> 1. Checkpoint timeout as you mentioned.
>> >> > > >>>>>>>>>>>>> 2. The recovery cost is high once failover, because
>> much
>> >> > data
>> >> > > >>>>> needs
>> >> > > >>>>>>>>> to be replayed.
>> >> > > >>>>>>>>>>>>> 3. The delay for commit-based sink is high in
>> >> exactly-once.
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> For credit-based flow control from release-1.5, the
>> >> amount
>> >> > of
>> >> > > >>>>>>>>> in-flighting buffers before barrier alignment is reduced,
>> >> so we
>> >> > > >>> could
>> >> > > >>>>> get a
>> >> > > >>>>>>>>> bit
>> >> > > >>>>>>>>>>>>> benefits from speeding checkpoint aspect.
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> In release-1.8, I guess we did not suspend the
>> channels
>> >> > which
>> >> > > >>>>> already
>> >> > > >>>>>>>>> received the barrier in practice. But actually we ever
>> did
>> >> the
>> >> > > >>>>> similar thing
>> >> > > >>>>>>>>>>>>> to speed barrier alighment before. I am not quite
>> sure
>> >> that
>> >> > > >>>>>>>>> release-1.8 covers this feature. There were some relevant
>> >> > > >>> discussions
>> >> > > >>>>> under
>> >> > > >>>>>>>>> jira [1].
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> For release-1.10, the community is now discussing the
>> >> > > feature of
>> >> > > >>>>>>>>> unaligned checkpoint which is mainly for resolving above
>> >> > > concerns.
>> >> > > >>> The
>> >> > > >>>>>>>>> basic idea
>> >> > > >>>>>>>>>>>>> is to make barrier overtakes the output/input buffer
>> >> queue
>> >> > to
>> >> > > >>>>> speed
>> >> > > >>>>>>>>> alignment, and snapshot the input/output buffers as part
>> of
>> >> > > >>> checkpoint
>> >> > > >>>>>>>>> state. The
>> >> > > >>>>>>>>>>>>> details have not confirmed yet and is still under
>> >> > discussion.
>> >> > > >>>>> Wish we
>> >> > > >>>>>>>>> could make some improvments for the release-1.10.
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> [1] https://issues.apache.org/jira/browse/FLINK-8523
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Best,
>> >> > > >>>>>>>>>>>>> Zhijiang
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>
>> ------------------------------------------------------------------
>> >> > > >>>>>>>>>>>>> From:Thomas Weise <[hidden email]>
>> >> > > >>>>>>>>>>>>> Send Time:2019年8月12日(星期一) 21:38
>> >> > > >>>>>>>>>>>>> To:dev <[hidden email]>
>> >> > > >>>>>>>>>>>>> Subject:Checkpointing under backpressure
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Hi,
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> One of the major operational difficulties we observe
>> >> with
>> >> > > Flink
>> >> > > >>>>> are
>> >> > > >>>>>>>>>>>>> checkpoint timeouts under backpressure. I'm looking
>> for
>> >> > both
>> >> > > >>>>>>>>> confirmation
>> >> > > >>>>>>>>>>>>> of my understanding of the current behavior as well
>> as
>> >> > > pointers
>> >> > > >>>>> for
>> >> > > >>>>>>>>> future
>> >> > > >>>>>>>>>>>>> improvement work:
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Prior to introduction of credit based flow control in
>> >> the
>> >> > > >>> network
>> >> > > >>>>>>>>> stack [1]
>> >> > > >>>>>>>>>>>>> [2], checkpoint barriers would back up with the data
>> for
>> >> > all
>> >> > > >>>>> logical
>> >> > > >>>>>>>>>>>>> channels due to TCP backpressure. Since Flink 1.5,
>> the
>> >> > > buffers
>> >> > > >>> are
>> >> > > >>>>>>>>>>>>> controlled per channel, and checkpoint barriers are
>> only
>> >> > held
>> >> > > >>>>> back for
>> >> > > >>>>>>>>>>>>> channels that have backpressure, while others can
>> >> continue
>> >> > > >>>>> processing
>> >> > > >>>>>>>>>>>>> normally. However, checkpoint barriers still cannot
>> >> > "overtake
>> >> > > >>>>> data",
>> >> > > >>>>>>>>>>>>> therefore checkpoint alignment remains affected for
>> the
>> >> > > channel
>> >> > > >>>>> with
>> >> > > >>>>>>>>>>>>> backpressure, with the potential for slow
>> checkpointing
>> >> and
>> >> > > >>>>> timeouts.
>> >> > > >>>>>>>>>>>>> Albeit the delay of barriers would be capped by the
>> >> maximum
>> >> > > >>>>> in-transit
>> >> > > >>>>>>>>>>>>> buffers per channel, resulting in an improvement
>> >> compared
>> >> > to
>> >> > > >>>>> previous
>> >> > > >>>>>>>>>>>>> versions of Flink. Also, the backpressure based
>> >> checkpoint
>> >> > > >>>>> alignment
>> >> > > >>>>>>>>> can
>> >> > > >>>>>>>>>>>>> help the barrier advance faster on the receiver side
>> (by
>> >> > > >>>>> suspending
>> >> > > >>>>>>>>>>>>> channels that have already delivered the barrier). Is
>> >> that
>> >> > > >>>>> accurate
>> >> > > >>>>>>>>> as of
>> >> > > >>>>>>>>>>>>> Flink 1.8?
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> What appears to be missing to completely unblock
>> >> > > checkpointing
>> >> > > >>> is
>> >> > > >>>>> a
>> >> > > >>>>>>>>>>>>> mechanism for checkpoints to overtake the data. That
>> >> would
>> >> > > help
>> >> > > >>> in
>> >> > > >>>>>>>>>>>>> situations where the processing itself is the
>> bottleneck
>> >> > and
>> >> > > >>>>>>>>> prioritization
>> >> > > >>>>>>>>>>>>> in the network stack alone cannot address the barrier
>> >> > delay.
>> >> > > Was
>> >> > > >>>>>>>>> there any
>> >> > > >>>>>>>>>>>>> related discussion? One possible solution would be to
>> >> drain
>> >> > > >>>>> incoming
>> >> > > >>>>>>>>> data
>> >> > > >>>>>>>>>>>>> till the barrier and make it part of the checkpoint
>> >> instead
>> >> > > of
>> >> > > >>>>>>>>> processing
>> >> > > >>>>>>>>>>>>> it. This is somewhat related to asynchronous
>> processing,
>> >> > but
>> >> > > I'm
>> >> > > >>>>>>>>> thinking
>> >> > > >>>>>>>>>>>>> more of a solution that is automated in the Flink
>> >> runtime
>> >> > for
>> >> > > >>> the
>> >> > > >>>>>>>>>>>>> backpressure scenario only.
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> Thanks,
>> >> > > >>>>>>>>>>>>> Thomas
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>> [1]
>> >> > > >>> https://flink.apache.org/2019/06/05/flink-network-stack.html
>> >> > > >>>>>>>>>>>>> [2]
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>
>> >> > > >>>>>
>> >> > > >>>
>> >> > >
>> >> >
>> >>
>> https://docs.google.com/document/d/1chTOuOqe0sBsjldA_r-wXYeSIhU2zRGpUaTaik7QZ84/edit#heading=h.pjh6mv7m2hjn
>> >> > > >>>>>>>>>>>>>
>> >> > > >>>>>>>>>>>>
>> >> > > >>>>>>>>>>>
>> >> > > >>>>>>>>>>
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>>>
>> >> > > >>>>>>>
>> >> > > >>>>>>
>> >> > > >>>>>
>> >> > > >>>>>
>> >> > > >>>
>> >> > > >>>
>> >> > > >
>> >> > >
>> >> > >
>> >> >
>> >> >
>> >>
>> >>
>> >>
>>
>
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Arvid Heise | Senior Java Developer
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