thanks Endre and Victor.
my code is much much cleaner now actually just 8 java lines and a
Throttler:
I was just wondering: I had to code my own throttler or is there any in
core?
final static class Tick {}
public static <T> Flow<T,T, BoxedUnit> createFlow(final long throttleSecs) {
Flow<T, T, BoxedUnit> sourceflow = Flow.<T>create();
Flow<T,Pair<T,Tick>, BoxedUnit> flow = Flow.fromGraph(
GraphDSL.create(builder -> {
final FlowShape<T, T> source = builder.add(sourceflow);
Source<Tick, Cancellable> tickSource =
Source.tick(FiniteDuration.apply(0, "millis"),
FiniteDuration.apply(throttleSecs, "millis"), new Tick());
final FanInShape2<T, Tick, Pair<T, Tick>> zipper =
builder.add(Zip.create());
SourceShape<Tick> tickSourceShape = builder.add(tickSource);
builder.from(source).toInlet(zipper.in0());
builder.from(tickSourceShape).toInlet(zipper.in1());
return FlowShape.of(source.in(), zipper.out());
}));
return flow.map(Pair::first);
}
Am Montag, 8. Februar 2016 12:35:35 UTC+1 schrieb drewhk:
>
> It might or might not be a problem. I am just pointing out the effects of
> buffer. There are at lest three different approaches possible here:
>
> - no buffers at all, keep the pipeline fused: polling only happens on
> need, and always returns fresh data:
>
> poller.throttle.mapConcat(identity)
>
> - want prefetch for better throughput, paying the price of potentially
> stale data:
>
> poller.throttle.mapConcat.buffer // can use .viaAsync to make consumer
> stages concurrent
>
> - want to poll independently of downstream demand, but not too often
>
> poller.throttle.conflate(<keep newest>).mapConcat(identity)
>
> Any of these work, with different opertional semantics.
>
> -Endre
>
> On Mon, Feb 8, 2016 at 12:29 PM, Viktor Klang <[email protected]
> <javascript:>> wrote:
>
>> How is that a problem? OP only wanted to make sure that the external
>> system wasn't polled too often.
>>
>> On Mon, Feb 8, 2016 at 12:20 PM, Endre Varga <[email protected]
>> <javascript:>> wrote:
>>
>>> Ah, you meant Backpressure. But then what I originally said is true.
>>> Just think about it:
>>>
>>> - buffer requests
>>> - buffer is enough to contain the next batch emitted by mapConcat
>>> - buffer hence stores some result
>>> - downstream now asks for next batch, but 3 hours later
>>> - emitted result is now 3 hours old
>>>
>>> -Endre
>>>
>>> On Mon, Feb 8, 2016 at 12:05 PM, Viktor Klang <[email protected]
>>> <javascript:>> wrote:
>>>
>>>> What? How would anything be dropped if buffer has Backpressure as
>>>> OverflowStrategy?
>>>>
>>>> On Mon, Feb 8, 2016 at 11:56 AM, Endre Varga <[email protected]
>>>> <javascript:>> wrote:
>>>>
>>>>>
>>>>>
>>>>> On Mon, Feb 8, 2016 at 11:53 AM, Viktor Klang <[email protected]
>>>>> <javascript:>> wrote:
>>>>>
>>>>>> If the Buffer has Backpressure as overflow strategy I don't see how
>>>>>> it decouples upstream from downstream.
>>>>>>
>>>>>
>>>>> That is a dangerous move though, since you put the buffer *after* the
>>>>> mapConcat, so this means that dropping will be independent of the batch
>>>>> boundaries. I.e. the buffer might hold 1 full batch and the half, dopping
>>>>> the other half. I think in this case it is better to use a more flexible
>>>>> tool there and "batcher" seems to be the right one (it is a conflate-like
>>>>> op with capacity, so can implement "smart" buffers). Or, mapConcat should
>>>>> not be used here. I guess it depends on the use case.
>>>>>
>>>>> -Endre
>>>>>
>>>>>
>>>>>>
>>>>>> On Mon, Feb 8, 2016 at 11:52 AM, Endre Varga <[email protected]
>>>>>> <javascript:>> wrote:
>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Sun, Feb 7, 2016 at 9:49 PM, Viktor Klang <[email protected]
>>>>>>> <javascript:>> wrote:
>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Sun, Feb 7, 2016 at 2:17 PM, <[email protected] <javascript:>>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Hi Victor,
>>>>>>>>> thank you for your reply and here are my remarks :
>>>>>>>>>
>>>>>>>>> Point 1. You have a source of "events" and the only way you know
>>>>>>>>> if there are any events, is if you ask for events
>>>>>>>>>
>>>>>>>>> exactly
>>>>>>>>>
>>>>>>>>> Point 2.You want to consume events from this source
>>>>>>>>>
>>>>>>>>> Yes
>>>>>>>>>
>>>>>>>>> Point 3) You only need to consume events from the source if there
>>>>>>>>> is demand from "downstream"
>>>>>>>>>
>>>>>>>>> It is the other way round. The source logically pushes the events
>>>>>>>>> downstream.
>>>>>>>>> Ideally as soon as theses Events arrive I would like them to be
>>>>>>>>> pushed downstream. So its more a push scenario.
>>>>>>>>> The source pushes as many Events as the downstream processes can
>>>>>>>>> handle.
>>>>>>>>> (But I have to limit myself for polling the database at a rate of
>>>>>>>>> 2-5 seconds because of hardware reasons)
>>>>>>>>>
>>>>>>>>
>>>>>>>> You only want to send data if the downstream can handle it, and the
>>>>>>>> source knows that by keeping track of downstream demand.
>>>>>>>>
>>>>>>>>
>>>>>>>>>
>>>>>>>>> Point 4) Does the source of events ever end, and how do you know?
>>>>>>>>>
>>>>>>>>> No the source never ends. External Systems always insert new Event
>>>>>>>>> records into the database
>>>>>>>>>
>>>>>>>>> Point 5. can you ask for a specified number of events or does
>>>>>>>>> polling imply reading all available events?
>>>>>>>>>
>>>>>>>>> No I can ask for a specified number of events.
>>>>>>>>>
>>>>>>>>> Here is a concrete business case:
>>>>>>>>> 1) External systems want Email Messages to be emailed to Users.
>>>>>>>>> 2) They insert Email Events (Records with email-address, content,
>>>>>>>>> user_id,etc) into a Email Table (log-table)
>>>>>>>>> 3) Email-Send-Service sends these Emails over the wire
>>>>>>>>> 4) Acknowledge-Service logs the Email-Send Event and cleans up
>>>>>>>>> the Email Table (log-table).
>>>>>>>>>
>>>>>>>>> So I can set up a Stream: Email-Source -> Email-Send-Service -
>>>>>>>>> Acknowledge-Service .
>>>>>>>>>
>>>>>>>>> I am now considering two ways of doing it and are hoping for your
>>>>>>>>> advice (-:
>>>>>>>>> 1) create the following
>>>>>>>>> Email-Source (select * from Email limit 1000) ->
>>>>>>>>> Email-Send-Service -> Acknowledge-Service
>>>>>>>>> and materialize this stream every two seconds
>>>>>>>>>
>>>>>>>>> 2) Set up a custom source which polls forever
>>>>>>>>> Polling-Neverending-Email-Source (select * from Email limit
>>>>>>>>> 1000 every two seconds inside the Actor) -> Email-Send-Service ->
>>>>>>>>> Acknowledge-Service
>>>>>>>>>
>>>>>>>>
>>>>>>>> Sounds like you should be able to, construct your source as
>>>>>>>> something like this:
>>>>>>>>
>>>>>>>> <poller> + <throttle> + <mapConcat(identity) + <buffer>
>>>>>>>>
>>>>>>>> This means that the polling gets throttled, and the mapConcat is if
>>>>>>>> you read more than 1 event per poll and the buffer is there to make
>>>>>>>> sure
>>>>>>>> that the demand that gets to the poller is > 1 to increase throughput.
>>>>>>>>
>>>>>>>
>>>>>>> On the other hand buffer detaches the upstream, so the poller will
>>>>>>> be called even when there is no downstream demand, causing it to return
>>>>>>> potentially stale data from the buffer if there are long pauses in
>>>>>>> downstream consumption. So this is a tradeoff, not necessarily a bad
>>>>>>> one,
>>>>>>> but one to be aware of.
>>>>>>>
>>>>>>> -Endre
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Background: I am building up with Akka Streams a inhouse toolkit
>>>>>>>>> which deals with many ESB typical processes.
>>>>>>>>> The above usecase profits not so much from throughput (actually
>>>>>>>>> the users could live with some delay) but more from
>>>>>>>>> reusing stream components and having a nice clear Flow DSL.
>>>>>>>>>
>>>>>>>>> Many Greetings
>>>>>>>>> John
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Am Sonntag, 7. Februar 2016 13:05:59 UTC+1 schrieb √:
>>>>>>>>>>
>>>>>>>>>> Hi John!
>>>>>>>>>>
>>>>>>>>>> I think I can help you, but I have some follow-on questions :)
>>>>>>>>>>
>>>>>>>>>> On Sun, Feb 7, 2016 at 12:52 PM, <[email protected]> wrote:
>>>>>>>>>>
>>>>>>>>>>> Hi Victor,
>>>>>>>>>>> I know you love simple elegant code but
>>>>>>>>>>> I looked at unfoldAsync and I don't see that it solves the
>>>>>>>>>>> usecase I have in mind.
>>>>>>>>>>>
>>>>>>>>>>> I'll try to explain why because I am not sure if I am
>>>>>>>>>>> overlooking something obvious?
>>>>>>>>>>>
>>>>>>>>>>> An external system writes events into a log table. Since this is
>>>>>>>>>>> a non-reactive-sql-database the consumer needs to poll the log
>>>>>>>>>>> table (for
>>>>>>>>>>> example every 2 seconds) for new events.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> (Why) does it need to poll the log table if there is no demand
>>>>>>>>>> for events?
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> To convert this scenario into a streaming source using
>>>>>>>>>>> unfoldAsync
>>>>>>>>>>> I need to implement a polling loop inside the future so that
>>>>>>>>>>> Future.success gets only called when new events are inserted in
>>>>>>>>>>> the log
>>>>>>>>>>> table.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> This seems much like a technical aspect rather than a requirement.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> If I don't use polling the future would send 0 Events upstream
>>>>>>>>>>> and the stream would come to an end?
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Events go downstream, or did I misunderstand something?
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> That's why I like using instead of unfoldAsync an Actor like
>>>>>>>>>>> JobManager
>>>>>>>>>>> <http://doc.akka.io/docs/akka-stream-and-http-experimental/2.0.3/java/stream-integrations.html>.
>>>>>>>>>>>
>>>>>>>>>>> as an Source. Within the Actor I can be more fine grained and use
>>>>>>>>>>> the
>>>>>>>>>>> scheduler to implement the polling logic.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Let's take a step back, what are the actual requirements?
>>>>>>>>>>
>>>>>>>>>> 1. You have a source of "events" and the only way you know if
>>>>>>>>>> there are any events, is if you ask for events
>>>>>>>>>> 2. You want to consume events from this source
>>>>>>>>>> 3. You only need to consume events from the source if there is
>>>>>>>>>> demand from "downstream"
>>>>>>>>>> 4. Does the source of events ever end, and how do you know?
>>>>>>>>>> 5. can you ask for a specified number of events or does polling
>>>>>>>>>> imply reading all available events?
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Many Greetings
>>>>>>>>>>> John
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Am Mittwoch, 3. Februar 2016 23:10:15 UTC+1 schrieb √:
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> http://doc.akka.io/api/akka-stream-and-http-experimental/2.0.3/?_ga=1.45749860.1579561034.1353497989#akka.stream.scaladsl.Source$
>>>>>>>>>>>>
>>>>>>>>>>>> On Wed, Feb 3, 2016 at 11:06 PM, <[email protected]> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> where do I find unfold/unfoldAsync ? I looked at
>>>>>>>>>>>>> http://doc.akka.io/docs/akka-stream-and-http-experimental/2.0.3/stages-overview.html
>>>>>>>>>>>>> ?
>>>>>>>>>>>>> Many Greetings
>>>>>>>>>>>>> John
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> Am Mittwoch, 3. Februar 2016 20:51:17 UTC+1 schrieb √:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> I don't see why you'd need to write a custom GraphStage for
>>>>>>>>>>>>>> this.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> unfold/unfoldAsync paired with a buffer with an appropriate
>>>>>>>>>>>>>> dropping policy should work, no?
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> On Wed, Feb 3, 2016 at 8:47 PM, clca <[email protected]>
>>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Yes this is close to what I need to do.
>>>>>>>>>>>>>>> The code in the onPull method is something like
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> val m = ReadFromService(...)
>>>>>>>>>>>>>>> if(m != null)
>>>>>>>>>>>>>>> push(out, m)
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> in a traditional app reading would be done in a loop
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> while(true) {
>>>>>>>>>>>>>>> val m = ReadFromService(...)
>>>>>>>>>>>>>>> //do something with the new message
>>>>>>>>>>>>>>> }
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> So I'll add a mechanism in the Source to keep polling the
>>>>>>>>>>>>>>> external service.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Thanks!
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> On Wednesday, February 3, 2016 at 12:55:16 AM UTC-8,
>>>>>>>>>>>>>>> [email protected] wrote:
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> I've done something similar.
>>>>>>>>>>>>>>>> I adapted this JobManager
>>>>>>>>>>>>>>>> <http://doc.akka.io/docs/akka-stream-and-http-experimental/2.0.3/java/stream-integrations.html>.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> When no data is available( for example when it recieves a
>>>>>>>>>>>>>>>> Request(16)
>>>>>>>>>>>>>>>> Messag) it starts a" polling Actor" which polls an external
>>>>>>>>>>>>>>>> Database for
>>>>>>>>>>>>>>>> more data.
>>>>>>>>>>>>>>>> Does this help?
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Am Mittwoch, 3. Februar 2016 08:33:16 UTC+1 schrieb clca:
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> I searched through the topics but I could not find any
>>>>>>>>>>>>>>>>> example on how to pull from a Source in the case where data
>>>>>>>>>>>>>>>>> is coming in
>>>>>>>>>>>>>>>>> bursts. I built a customized Source that read from an
>>>>>>>>>>>>>>>>> external source. Data
>>>>>>>>>>>>>>>>> is coming in bursts, the flow can stop for a while so I need
>>>>>>>>>>>>>>>>> to keep
>>>>>>>>>>>>>>>>> pulling the Source in such a way I can keep reading data (the
>>>>>>>>>>>>>>>>> actual read
>>>>>>>>>>>>>>>>> process is done in the old poll fashion). I guess I need
>>>>>>>>>>>>>>>>> something like a
>>>>>>>>>>>>>>>>> KeepAlive type of mechanism for the data stream.
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> BTW: Fantastic job with Akka, Akka Stream & Akka HTTP!
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>> Thanks
>>>>>>>>>>>>>>>>> Claudio
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> --
>>>>>>>>>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>>>>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
>>>>>>>>>>>>>>> >>>>>>>>>> Search the archives:
>>>>>>>>>>>>>>> https://groups.google.com/group/akka-user
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>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> --
>>>>>>>>>>>>>> Cheers,
>>>>>>>>>>>>>> √
>>>>>>>>>>>>>>
>>>>>>>>>>>>> --
>>>>>>>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
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>>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> --
>>>>>>>>>>>> Cheers,
>>>>>>>>>>>> √
>>>>>>>>>>>>
>>>>>>>>>>> --
>>>>>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
>>>>>>>>>>> >>>>>>>>>> Search the archives:
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>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> --
>>>>>>>>>> Cheers,
>>>>>>>>>> √
>>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
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>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> --
>>>>>>>> Cheers,
>>>>>>>> √
>>>>>>>>
>>>>>>>> --
>>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
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>>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>> >>>>>>>>>> Check the FAQ:
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>>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Cheers,
>>>>>> √
>>>>>>
>>>>>> --
>>>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>> >>>>>>>>>> Check the FAQ:
>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
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>>>>>>
>>>>>
>>>>> --
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>>>>> >>>>>>>>>> Check the FAQ:
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>>>>>
>>>>
>>>>
>>>>
>>>> --
>>>> Cheers,
>>>> √
>>>>
>>>> --
>>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
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>>>>
>>>
>>> --
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>>
>>
>>
>> --
>> Cheers,
>> √
>>
>> --
>> >>>>>>>>>> Read the docs: http://akka.io/docs/
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>
>
--
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>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
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