I agree with Michael, I don't really understand what is actually needed
here, it is too big wall of text :) But from what I understand, I second
Michael's assesment is that you probably are after eventsourcing and
akka-persistence.


-Endre

On Mon, May 9, 2016 at 7:28 PM, Michael Frank <syntaxjoc...@gmail.com>
wrote:

> It would help if your problem statement was more concrete.  however, in my
> vague understanding of the problem, it seems like event sourcing would be
> an appropriate way to model your business logic:
> http://martinfowler.com/eaaDev/EventSourcing.html
>
> if that is the case, then i think using akka persistence and cluster
> sharding would be a good starting point.  your 'state changes' sound like
> Persistent Actors.  the problem of knowing whether messages have been
> processed or not sounds like it would be solved with persistent actor
> recovery (
> http://doc.akka.io/docs/akka/2.4.4/scala/persistence.html#Recovery).
>
> -Michael
>
>
> On 05/09/16 09:56, kraythe wrote:
>
> Thats the thing, if there were humans with inboxes I could have a staff
> call them on the phone and check. :) Reprocessing the messages is a pretty
> simple solution IF the messages were small in number. When you get to the
> point where there are literally millions of events the problem gets a bit
> more difficult to manage. If there are 10 million messages to process and
> the messages could take 10 minutes to process, if I check again 1 minute
> later and 8 million of the records still show unprocessed and then I add
> those 8 million back to the queue, now I have 16 million more messages to
> process. Then the next phase, 6 million, added to the queue -2 million
> processed, the is now 20 million messages and so on. by the time I am done
> with the original set, Ill have another 30 million messages to process, all
> of which are a waste of computing power because they do nothing. Clearly
> that I would like to avoid. Also setting the time to be for sure how long
> we need to process the first 10 million is not an option because the time
> and the number of messages are both variables that are unknown.
>
> Right now I put the messages that need to be processed in a map with a key
> and the process that runs every minute checks for messages not processed.
> Then it compares those ids against those in the map, if they are in the map
> it doesn't resubmit them. However, this doesn't seem to be a very Akkaesque
> solution to the problem. I am looking for ideas on how to handle it without
> using the map but it may be that I have to continue using the map to load
> the message queues.
>
>
> On Monday, May 9, 2016 at 2:33:54 AM UTC-5, √ wrote:
>>
>> I'm quite sure that inspecting the mbox will be costlier than
>> reprocessing at those sizes.
>>
>> Come up with two different solutions that you could perform between
>> humans having mailboxes. Pick the best of those.
>>
>> --
>> Cheers,
>> √
>> On May 8, 2016 5:15 PM, "kraythe" <kra...@gmail.com> wrote:
>>
>>> I have a process that has to manage a large amount of data. I want to
>>> make the process reactive but it has to process every data element. The
>>> data is stored in Hazelcast in a map (which is backed by a database but
>>> that detail is irrelevant) and the data is stageful. At each state change
>>> something has to be done either to the data or related data. So if we go
>>> from State A to State B we might have to do something to another object in
>>> the process in a transactional manner. When the data is in state A a
>>> process finds the data and submits it to a map. Right now I have another
>>> thread reading from the map on intervals that are timed and if there is
>>> data in the map it processes the next entry in the map and so on.
>>>
>>> I would like to turn this process into an Akka actor process but the
>>> main stumbling block is to know what is already in the queue. Say I have 1m
>>> objects to process. At each interval the objects are checked if they can
>>> change state and if they can then they are put in the map to process. The
>>> problem is there could be a ton of these objects and they might take longer
>>> to process than the check interval. Furthermore, although it would not be
>>> damaging to the data it would be immensely wasteful to put them into the
>>> queue to process twice. Finally if the server crashed or something happened
>>> I would want to put them back into the queue if they are still in state A
>>> and should move to state B. Right now I can get the key set of the map and
>>> not submit them to the process if they are already in the map. If, instead,
>>> I change the system to Akka, then that ability changes. Whenever an object
>>> needs to change state, I would put it in a message inbox to an actor to
>>> process but I have no way to know what is already in that inbox so it makes
>>> the processing of the messages less durable. If a transaction fails or node
>>> fails I won't know that certain objects need to be processed again. Right
>>> now I can search the store, get the objects to process, remove all the ones
>>> in the queue and then put only the missing ones in the queue. I don't know
>>> how I could architect this with akka.
>>>
>>> What I would be looking for is some means to inspect an inbox to know if
>>> a message has already been enqueued and should not be enqueued again.
>>>
>>> Any suggestions on how I could architect a solution to this problem?
>>> --
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-- 
Akka Team
Typesafe - Reactive apps on the JVM
Blog: letitcrash.com
Twitter: @akkateam

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