It feels like his thread may be a bit off-track. Rather than focusing on the semantics of the existing methods -- which have been noted to be meet many existing use cases -- it would be helpful to focus on more on the reason you are looking for something with different semantics.
Some possibilities (I'm not sure which one you are trying to do): 1. Clean-up some external, global resource, that was initialized once during the startup of the pipeline. If this is the case, how are you ensuring it was really only initialized once (and not once per worker, per thread, per instance, etc.)? How do you know when the pipeline should release it? If the answer is "when it reaches step X", then what about a streaming pipeline? 2. Finalize some resources that are used within some region of the pipeline. While, the DoFn lifecycle methods are not a good fit for this (they are focused on managing resources within the DoFn), you could model this on how FileIO finalizes the files that it produced. For instance: a) ParDo generates "resource IDs" (or some token that stores information about resources) b) "Require Deterministic Input" (to prevent retries from changing resource IDs) c) ParDo that initializes the resources d) Pipeline segments that use the resources, and eventually output the fact they're done e) "Require Deterministic Input" f) ParDo that frees the resources By making the use of the resource part of the data it is possible to "checkpoint" which resources may be in use or have been finished by using the require deterministic input. This is important to ensuring everything is actually cleaned up. 3. Some other use case that I may be missing? If it is this case, could you elaborate on what you are trying to accomplish? That would help me understand both the problems with existing options and possibly what could be done to help. -- Ben On Sun, Feb 18, 2018 at 9:56 AM Romain Manni-Bucau <rmannibu...@gmail.com> wrote: > 2018-02-18 18:36 GMT+01:00 Eugene Kirpichov <kirpic...@google.com>: > >> "Machine state" is overly low-level because many of the possible reasons >> can happen on a perfectly fine machine. >> If you'd like to rephrase it to "it will be called except in various >> situations where it's logically impossible or impractical to guarantee that >> it's called", that's fine. Or you can list some of the examples above. >> > > Sounds ok to me > > >> >> The main point for the user is, you *will* see non-preventable situations >> where it couldn't be called - it's not just intergalactic crashes - so if >> the logic is very important (e.g. cleaning up a large amount of temporary >> files, shutting down a large number of VMs you started etc), you have to >> express it using one of the other methods that have stricter guarantees >> (which obviously come at a cost, e.g. no pass-by-reference). >> > > FinishBundle has the exact same guarantee sadly so not which which other > method you speak about. Concretely if you make it really unreliable - this > is what best effort sounds to me - then users can use it to clean anything > but if you make it "can happen but it is unexpected and means something > happent" then it is fine to have a manual - or auto if fancy - recovery > procedure. This is where it makes all the difference and impacts the > developpers, ops (all users basically). > > >> >> On Sun, Feb 18, 2018 at 9:16 AM Romain Manni-Bucau <rmannibu...@gmail.com> >> wrote: >> >>> Agree Eugene except that "best effort" means that. It is also often used >>> to say "at will" and this is what triggered this thread. >>> >>> I'm fine using "except if the machine state prevents it" but "best >>> effort" is too open and can be very badly and wrongly perceived by users >>> (like I did). >>> >>> >>> Romain Manni-Bucau >>> @rmannibucau <https://twitter.com/rmannibucau> | Blog >>> <https://rmannibucau.metawerx.net/> | Old Blog >>> <http://rmannibucau.wordpress.com> | Github >>> <https://github.com/rmannibucau> | LinkedIn >>> <https://www.linkedin.com/in/rmannibucau> | Book >>> <https://www.packtpub.com/application-development/java-ee-8-high-performance> >>> >>> 2018-02-18 18:13 GMT+01:00 Eugene Kirpichov <kirpic...@google.com>: >>> >>>> It will not be called if it's impossible to call it: in the example >>>> situation you have (intergalactic crash), and in a number of more common >>>> cases: eg in case the worker container has crashed (eg user code in a >>>> different thread called a C library over JNI and it segfaulted), JVM bug, >>>> crash due to user code OOM, in case the worker has lost network >>>> connectivity (then it may be called but it won't be able to do anything >>>> useful), in case this is running on a preemptible VM and it was preempted >>>> by the underlying cluster manager without notice or if the worker was too >>>> busy with other stuff (eg calling other Teardown functions) until the >>>> preemption timeout elapsed, in case the underlying hardware simply failed >>>> (which happens quite often at scale), and in many other conditions. >>>> >>>> "Best effort" is the commonly used term to describe such behavior. >>>> Please feel free to file bugs for cases where you observed a runner not >>>> call Teardown in a situation where it was possible to call it but the >>>> runner made insufficient effort. >>>> >>>> On Sun, Feb 18, 2018, 9:02 AM Romain Manni-Bucau <rmannibu...@gmail.com> >>>> wrote: >>>> >>>>> 2018-02-18 18:00 GMT+01:00 Eugene Kirpichov <kirpic...@google.com>: >>>>> >>>>>> >>>>>> >>>>>> On Sun, Feb 18, 2018, 2:06 AM Romain Manni-Bucau < >>>>>> rmannibu...@gmail.com> wrote: >>>>>> >>>>>>> >>>>>>> >>>>>>> Le 18 févr. 2018 00:23, "Kenneth Knowles" <k...@google.com> a écrit : >>>>>>> >>>>>>> On Sat, Feb 17, 2018 at 3:09 PM, Romain Manni-Bucau < >>>>>>> rmannibu...@gmail.com> wrote: >>>>>>>> >>>>>>>> If you give an example of a high-level need (e.g. "I'm trying to >>>>>>>> write an IO for system $x and it requires the following initialization >>>>>>>> and >>>>>>>> the following cleanup logic and the following processing in between") >>>>>>>> I'll >>>>>>>> be better able to help you. >>>>>>>> >>>>>>>> >>>>>>>> Take a simple example of a transform requiring a connection. Using >>>>>>>> bundles is a perf killer since size is not controlled. Using teardown >>>>>>>> doesnt allow you to release the connection since it is a best effort >>>>>>>> thing. >>>>>>>> Not releasing the connection makes you pay a lot - aws ;) - or >>>>>>>> prevents you >>>>>>>> to launch other processings - concurrent limit. >>>>>>>> >>>>>>> >>>>>>> For this example @Teardown is an exact fit. If things die so badly >>>>>>> that @Teardown is not called then nothing else can be called to close >>>>>>> the >>>>>>> connection either. What AWS service are you thinking of that stays open >>>>>>> for >>>>>>> a long time when everything at the other end has died? >>>>>>> >>>>>>> >>>>>>> You assume connections are kind of stateless but some (proprietary) >>>>>>> protocols requires some closing exchanges which are not only "im >>>>>>> leaving". >>>>>>> >>>>>>> For aws i was thinking about starting some services - machines - on >>>>>>> the fly in a pipeline startup and closing them at the end. If teardown >>>>>>> is >>>>>>> not called you leak machines and money. You can say it can be done >>>>>>> another >>>>>>> way...as the full pipeline ;). >>>>>>> >>>>>>> I dont want to be picky but if beam cant handle its components >>>>>>> lifecycle it can be used at scale for generic pipelines and if bound to >>>>>>> some particular IO. >>>>>>> >>>>>>> What does prevent to enforce teardown - ignoring the interstellar >>>>>>> crash case which cant be handled by any human system? Nothing >>>>>>> technically. >>>>>>> Why do you push to not handle it? Is it due to some legacy code on >>>>>>> dataflow >>>>>>> or something else? >>>>>>> >>>>>> Teardown *is* already documented and implemented this way >>>>>> (best-effort). So I'm not sure what kind of change you're asking for. >>>>>> >>>>> >>>>> Remove "best effort" from the javadoc. If it is not call then it is a >>>>> bug and we are done :). >>>>> >>>>> >>>>>> >>>>>> >>>>>>> Also what does it mean for the users? Direct runner does it so if a >>>>>>> user udes the RI in test, he will get a different behavior in prod? Also >>>>>>> dont forget the user doesnt know what the IOs he composes use so this >>>>>>> is so >>>>>>> impacting for the whole product than he must be handled IMHO. >>>>>>> >>>>>>> I understand the portability culture is new in big data world but it >>>>>>> is not a reason to ignore what people did for years and do it wrong >>>>>>> before >>>>>>> doing right ;). >>>>>>> >>>>>>> My proposal is to list what can prevent to guarantee - in the normal >>>>>>> IT conditions - the execution of teardown. Then we see if we can handle >>>>>>> it >>>>>>> and only if there is a technical reason we cant we make it >>>>>>> experimental/unsupported in the api. I know spark and flink can, any >>>>>>> unknown blocker for other runners? >>>>>>> >>>>>>> Technical note: even a kill should go through java shutdown hooks >>>>>>> otherwise your environment (beam enclosing software) is fully unhandled >>>>>>> and >>>>>>> your overall system is uncontrolled. Only case where it is not true is >>>>>>> when >>>>>>> the software is always owned by a vendor and never installed on customer >>>>>>> environment. In this case it belongd to the vendor to handle beam API >>>>>>> and >>>>>>> not to beam to adjust its API for a vendor - otherwise all unsupported >>>>>>> features by one runner should be made optional right? >>>>>>> >>>>>>> All state is not about network, even in distributed systems so this >>>>>>> is key to have an explicit and defined lifecycle. >>>>>>> >>>>>>> >>>>>>> Kenn >>>>>>> >>>>>>> >>>>>>> >>>
