[concurrency-interest] Upcoming jdk9 j.u.c JEP

Viktor Klang viktor.klang at gmail.com
Mon Aug 10 07:38:57 EDT 2015


#define initiator

On Mon, Aug 10, 2015 at 12:00 PM, Oleksandr Otenko <
oleksandr.otenko at oracle.com> wrote:

> The direction of the data flow is not important, so upstream vs downstream
> are irrelevant. The important aspect is the control flow.
>
> There are push-streams and there are pull-streams. The error should
> propagate to the initiator.
>
> Alex
>
>
> On 24/07/2015 08:12, Roland Kuhn wrote:
>
> Hi Greg,
>
> my reply has obviously opened two different discussions (namely “why are
> things as they are?” and “what is the suggested change all about”), I think
> it would be most fruitful if we stash the first one for now and come back
> to it after the second one has been understood better—at least by myself.
> That will put us into a better situation for judging the big picture.
>
> Considering the flow of data from the DB via application and framework
> processors into the Servlet container, at any point along this line
> failures can happen. The component emitting the failure will use whatever
> means it has outside of Reactive Streams to log/audit/monitor and provide
> metrics, I assume that that is just part of all reasonable code; the
> database will do that, the application will do it, the framework will
> probably allow the application to configure how to do that, and the
> application server will be configured how to do that. This means that
> everyone can debug their own failures.
>
> Data are flowing towards the Servlet (destined for whichever client made
> the request) and it is important to signal abnormal termination differently
> from normal termination, hence the onError propagation in this direction.
> This also allows downstream components to see failures coming from
> upstream, but this is a byproduct of needing to generate the right kind of
> final response to the external client. Now the interesting question is: why
> would the database need to know that some downstream component choked on
> the data it emitted? How exactly would this information be used by the
> database or its operators/programmers? Arguably the data exist and are
> “correct” by definition, guarded by Java types, and any validation errors
> that occur are not stream failures (cf. this definition
> <http://www.reactivemanifesto.org/glossary#Failure>) and should be
> treated as normal data elements and sent downstream (or filtered out,
> depending on the requirements & protocol).
>
> I am deliberately painting with high contrast colors here in order to
> better understand what exactly it is that you want to achieve instead of
> just discussing the proposed solution, thanks for your patience!
>
> Regards,
>
> Roland
>
> 24 jul 2015 kl. 08:31 skrev Greg Wilkins < <gregw at webtide.com>
> gregw at webtide.com>:
>
> Roland,
>
> thanks for the response.
>
> But I don't understand why you consider a terminal exception being
> notified upstream as a data flow?   It is data, but it is not a flow
> because it is terminal and cannot be used as a back channel.
>
> Implementations of the API are already required to send data upstream:
> Cancellation is a terminal boolean data state that must be sent upstream,
> and request(int) is a flow of integers that must be sent upstream [and as
> an aside, it is not beyond imagination that request(int) will be misused as
> a back channel for data - hey it might even get used to send an error code
> immediately prior/post to a cancel! ]
>
> Thus I don't see that there is any significant additional complexity with
> that cancellation having a reason associated with it.   Implementations
> must already support upward bound data and any sequencing and/or race
> conditions that exist with cancel(Throwable) also exist with just cancel().
>
> I also dispute that a Subscriber will be under the control of the
> Publisher.     In the example cited and application is providing a
> Processor, that is using a Publisher provided by a 3rd party database and
> an Subscriber provided by the Servlet container, with perhaps some
> framework provided Processors for serialization.   In this example there is
> the possibility of components from at least 4 difference code sources being
> combined in a chain that crosses deployment administration boundaries of:
> database, application and server.     The log & cancel handling of errors
> is going to be very difficult because many different log mechanism may be
> in use and access may not be easily achieved.  ie applications developers
> may not have full viability of database logs or servlet container logs.
>
> The type of error I'm concerned about are all terminal style errors and
> not intended to be a back flow of data, nor acknowledgement of messages
> sent.   It is probably that the implementers of cancel(Throwable) would
> just log, cancel themselves and pass on the cancel(Throwable) to any of
> their Subscripions.   However the point being that would allow the reason
> for the failure to cross the administrative boundaries so that it can be
> known to all.
>
> I think that any argument that can be made for not sending a Throwable
> upstream can equally be made for not sending one downstream (or for not
> having any exceptions in the java language).   Exceptions are very rarely
> handled in any meaningful way, but are extremely useful for passing details
> of a failure so that they may be known to all who may need to know.
>
> Without exceptions  I'm imagining many many  stack over flow questions
> like "Why was my Subscription cancelled?" followed by obligatory "RTFLog
> Stupid!" responses!
>
> cheers
>
>
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> On 24 July 2015 at 15:55, Roland Kuhn < <rk at rkuhn.info>rk at rkuhn.info>
> wrote:
>
>> Hi Greg,
>>
>> the reasoning behind the asymmetric RS design is that this communication
>> primitive targets unidirectional communication, bidirectional conversations
>> would utilize two such streams running in opposite directions. This means
>> that for a single stream data elements (of which onError is but a special
>> one) flow downstream and only demand flows upstream. Publishers only need
>> to know about when and if to produce the next element(s), hence we didn’t
>> see a use-case for propagating more information than “N elements needed”
>> and “no more elements needed”.
>>
>> If a single Reactive Stream could transport data upstream then we would
>> need to implement back-pressure on that back channel as well, leading to
>> the same complexity as having two RS running in opposite directions.
>> Another reason why we made this separation lies in not burdening the API
>> designers of conforming implementations with an impossible task: the
>> combinators offered on stream transformation APIs flow with the (English)
>> language from left to right and describe sequences of transformation stages
>> but with data flowing upstream there would be the need for also describing
>> how to handle that—even if it is “only” an error channel—and since these
>> data flow in the opposite direction there would be no natural way to write
>> this down.
>>
>> Learning about the reason behind cancellation seems geared towards
>> recovery in the sense that the Publisher would then construct and attach a
>> different Subscriber afterwards—please let me know if you have something
>> else in mind—and if you want to do that then the Subscriber will in any
>> case be under the Publisher’s control and can use a different channel to
>> communicate the onError signal back to the data source. Since that channel
>> would transport data it would be a separate one flowing in the opposite
>> direction as mentioned above, at least conceptually; with a single element
>> like you describe it could well be a simpler callback mechanism and might
>> not need full back-pressure.
>>
>> I hope this clarifies some of the background behind the RS design. Please
>> share more of your intended use of an error back-channel so that we can
>> understand what exactly the upstream components would do with that data in
>> the example case you mention.
>>
>> Regards,
>>
>> Roland
>>
>> 24 jul 2015 kl. 00:35 skrev Greg Wilkins < <gregw at webtide.com>
>> gregw at webtide.com>:
>>
>>
>>
>> On 24 July 2015 at 00:23, Doug Lea < <dl at cs.oswego.edu>dl at cs.oswego.edu>
>> wrote:
>>
>>>
>>> * Reactive-stream users may be disappointed that we do not include any
>>> net/IO-based Flow.Publisher/Subscriber classes, considering that
>>> reactive-streams are mainly motivated by net-based frameworks.  The
>>> reasons for triaging these out are that (1) IO generally falls outside
>>> of java.util.concurrent (2) Most net-based frameworks seem to use
>>> custom data representation etc (e.g., JSON) that are even further out
>>> of scope.  However class SubmissionPublisher can be used as an adaptor
>>> to turn just about any kind of source into a Publisher, so provides a
>>> nearly universal way of constructing a good non-custom Publisher even
>>> from IO-based sources.  (Also notice that SubmissionPublisher can
>>> serve as the basis of other actor-like frameworks, including those
>>> turning off back-pressure by calling
>>> subscription.request(Long.MAX_VALUE) in onSubscribe).
>>>
>>>
>>
>> Doug et al,
>>
>> The Jetty project has been experimenting with the reactive streams API:
>> <https://github.com/jetty-project/jetty-reactive>
>> https://github.com/jetty-project/jetty-reactive albiet not with the
>> JDK-9 version of it, but inspired by the proposed inclusion of it.
>>
>> We very much like the API and what it can bring to our space.  We don't
>> see that it needs direct IO support and that it's power is actually
>> bridging domains with a good asynchronous model that supports flow
>> control.
>>
>> We've also begun some preliminary discussions about developing RS based
>> proposal for the Servlet 4.0 specification.    Currently the Servlet API
>> does well support asynchronous IO and behaviour, but the API is deceptively
>> difficult to use correctly and gives no support for back pressure.   With
>> RS's we can envisage solutions that look like:
>>
>>    - A database provides a RS Producer that provides the large results
>>    of a query asynchronously from a remote database server
>>    - Some business logic is encapsulated as a RS Processor subscribed to
>>    the database producer
>>    - Some framework provided  Porocessors subscribe to the business
>>    logic Processor to perform a chain of functions such as serialization,
>>    compression
>>    - A container provided Subscriber terminates the chain and sends the
>>    resulting byte out over HTTP/HTTP2 or Websocket.   The flow control
>>    mechanisms of these protocols would be the basis of the RS back pressure.
>>
>> In such solutions, a full HTTP/2 flow control window would result in back
>> pressure on the remote database server, allowing threadless waiting without
>> unlimited queuing of data.
>>
>> However, we have a significant concern with the API in that we do not
>> like it's error handling design.  Specifically that it is asymmetric and an
>> error in the middle of a chain of processors can be propagated downstream
>> with onError(Throwable) but can only be propagated upstream with cancel().
>>
>> We believe that cancel without reason is an insufficient semantic to
>> build a robust ecosystem of RS Processors that can be used to build
>> applications.   Consider the above example, it would be ideal if the object
>> serialization was handled by a 3rd party Processor (let's say
>> JSONEncodingProcessor). If the business logic erroneously sent an
>> non-jsonable object, or if the JSON converter was incorrectly configured
>> then the JSONEcondiingProcessor could encounter an error during its
>> onNext(Object item) handling and it's only permitted handling of that is to
>> cancel the stream, without explanation.
>>
>> I have raised this as an issue on the RS github and it the current
>> recommendation is to log and cancel:
>> <https://github.com/reactive-streams/reactive-streams-jvm/issues/271#issuecomment-121974544>
>> https://github.com/reactive-streams/reactive-streams-jvm/issues/271#issuecomment-121974544
>> However I believe that log and cancel is a insufficient semantic.   Logging
>> in assembled applications is often fraught as each component provider will
>> fight over which logging framework is best.  RS chains may cross
>> jurisdictional boundaries and logs may not even be readily available.
>>
>> The solution we see is to replace/augment cancel() with either
>> cancel(Throwable reason) or an upstream onError(Throwable reason).  I
>> acknowledge that the passed reason may not always be meaningful to the
>> upstream processors and publishers, but it is better to ignore a
>> meaningless reason than to be ignorant of a meaningful one.
>>
>> When considering this API, we have to look beyond usages that work well
>> and consider usages that will fail well also!
>>
>> cheers
>>
>> --
>> Greg Wilkins < <gregw at webtide.com>gregw at webtide.com>
>>
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>>
>> --
>> I'm a physicist: I have a basic working knowledge of the universe and
>> everything it contains!
>>     - Sheldon Cooper (The Big Bang Theory)
>>
>>
>
> --
> I'm a physicist: I have a basic working knowledge of the universe and
> everything it contains!
>     - Sheldon Cooper (The Big Bang Theory)
>
>
>
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-- 
Cheers,
√
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