Greg - if one uses the current Akka Persistence with eventstore as the backend, is it possible/what are the challenges in getting safe 'process managers' to work as one would expect? I would think you'd want event store feeding a different Akka Persistence processor.
On Wed, Aug 20, 2014 at 2:10 PM, Ashley Aitken <amait...@gmail.com> wrote: > > Whilst we are talking about s... process managers I would like to include > this simple way of understanding them I found on the web: "Process Managers > produce commands and consume events, whereas Aggregate Roots consume > commands and produce events." The truth is a bit more complicated I > believe in that Process Managers can also consume commands (e.g. to stop > the process). > > Further, whilst I would like to accept Roland's view that both commands > and events can be communicated by sending messages (since, as he suggests, > it would make things a lot simpler and lighter on the write side), I am > concerned that there are use-cases for process managers that involve them > listening for events from ARs they have not sent a command message to. Can > anyone confirm/deny? > > Thanks, > Ashley. > > > > On Wednesday, 20 August 2014 23:01:41 UTC+8, Greg Young wrote: > >> further explanation http://soa.dzone.com/news/are-sagas-and- >> workflows-same-t >> >> >> On Wed, Aug 20, 2014 at 10:39 AM, Greg Young <gregor...@gmail.com> wrote: >> >> I held the same issue with ms pnp >> >> Clarifying the terminology >> >> The term saga is commonly used in discussions of CQRS to refer to a piece >> of code that coordinates and routes messages between bounded contexts and >> aggregates. However, for the purposes of this guidance we prefer to use the >> term process manager to refer to this type of code artifact. There are two >> reasons for this: >> >> There is a well-known, pre-existing definition of the term saga that has >> a different meaning from the one generally understood in relation to CQRS. >> The term process manager is a better description of the role performed by >> this type of code artifact. >> >> Although the term saga is often used in the context of the CQRS pattern, >> it has a pre-existing definition. We have chosen to use the term process >> manager in this guidance to avoid confusion with this pre-existing >> definition. >> >> The term saga, in relation to distributed systems, was originally defined >> in the paper "Sagas" by Hector Garcia-Molina and Kenneth Salem. This paper >> proposes a mechanism that it calls a saga as an alternative to using a >> distributed transaction for managing a long-running business process. The >> paper recognizes that business processes are often comprised of multiple >> steps, each of which involves a transaction, and that overall consistency >> can be achieved by grouping these individual transactions into a >> distributed transaction. However, in long-running business processes, using >> distributed transactions can impact on the performance and concurrency of >> the system because of the locks that must be held for the duration of the >> distributed transaction. >> >> >> On Wed, Aug 20, 2014 at 10:31 AM, Roland Kuhn <goo...@rkuhn.info> wrote: >> >> >> 20 aug 2014 kl. 16:16 skrev Greg Young <gregor...@gmail.com>: >> >> Please stop using the terminology of "saga" and replace usage with >> "process manager" what people (largely influenced by nservicebus call a >> saga is actually a process manager and a saga is a different pattern). Its >> bad enough the .net community does this the last thing we need is for the >> akka community to start doing the same :) >> >> >> Sure, but please do educate us as to the right use of these two words so >> we persist the correct definitions in the list archives. My main question >> is: what is that other pattern that shall be called a Saga? >> >> Regards, >> >> Roland >> >> >> >> >> On Wed, Aug 20, 2014 at 4:16 AM, Roland Kuhn <goo...@rkuhn.info> wrote: >> >> >> 19 aug 2014 kl. 18:59 skrev Ashley Aitken <amai...@gmail.com>: >> >> On Tuesday, 19 August 2014 21:14:17 UTC+8, rkuhn wrote: >> >> >> 18 aug 2014 kl. 18:01 skrev Ashley Aitken <amai...@gmail.com>: >> >> I believe Akka needs to allow actors to: >> >> >> (i) persist events with as much information as efficiently possible on >> the write side to allow the store to facilitate the read side extracting >> them according to what criteria is needed, >> >> This is a convoluted way of saying that Events must be self-contained, >> right? In that case: check! >> >> >> No, I don't think so. As I understand it now, the only thing the event >> store knows about each event is the persistenceId and a chunk of opaque >> data. It doesn't know the type of the event, the type of the message, any >> time information, any causal dependency etc. I guess what I am saying is >> that the events need to include as much metadata as possible so that the >> event store can provide the necessary synthetic streams if they are >> requested by the read side. As I mentioned later, some event stores (like >> Kafka may replicate the events into separate topics based on this >> information), others (like Event Store) may use this information later to >> form streams of links to the original events. >> >> >> The event store has the full event available, which is all the >> information there is: gathering or duplicating arbitrary parts of the >> information is likely not going to help, because you will discover later >> that you missed something initially, and if the mechanism is baked into the >> Akka Persistence Journal SPI then fixing it will take a very long time >> (until plugins are migrated and your OPS guys allow you to use it etc.). My >> recommendation is to use a serialization mechanism that fits the Journal, >> allowing it to understand the events and provide semantic features on top. >> Both (Journal and serialization) are configured in the same file, so I >> submit that coupling them is a valid approach. >> >> On causal consistency: I am still unconvinced that it is worth pursuing, >> and I am certain that you are vastly underestimating the amount of data and >> effort involved. And it cannot be done without collaboration from the user >> since a single inter-Actor message outside of the traced system (i.e. not >> using a PersistenceEnvelope of sorts) would hamper or destroy it. >> >> >> (iii) read from (and replay) streams of events on the read and write side >> according to a range of criteria supported and defined within the store or >> via the store API (e.g. using a DSL), and >> >> This is the unclear point: who defines the query and when? What are the >> consistency guarantees for the generated event stream? >> >> >> I suggest the developers of the read side specify the queries directly to >> the event store but this may be after the events have initially been >> persisted. The event store produces the query stream (if it can) and a >> PersistentView can be setup to read from that named query. With regards to >> consistency guarantees - my understanding is that these streams are used to >> eventually guarantee that the query model will be consistent with the write >> model, i.e. all the events will get across. With regards to ordering I >> think the event store does the best it can to provide consistent ordering, >> e.g. total ordering if there was no distribution and causal ordering, where >> possible, if there was ordering. The developer would need to understand >> the limitations of how the query store is configured and queried. >> >> >> As I answered to Greg already, I think that this should not be a core >> concern of Akka Persistence; as you note it relies on features provided by >> the underlying event store, and those features are not necessary to achieve >> the goal of making actors persistent. >> >> >> >> >> (iv) reliably (at least once) deliver information to other read side >> store(s) and systems above and beyond the store used for persisting the >> events. >> >> This is PersistentView, so “check!” (As argued previously “reliably” >> translates to “persistent”.) >> >> >> As I asked in another thread (I think) I am not sure how PersistentView >> can do this when PersistentActor is the one that can mixin >> AtLeastOnceDelivery? >> >> I think we need a PeristentView that can guarantee AtLeastOnceDelivery to >> an actor representing a query store. This would seem to require a >> PersistentViewActor ;-) that can read from a persistent query and also >> persist its state to provide guaranteed delivery. >> >> My lack of knowledge of Scala and Akka may be showing here. >> >> >> My current impression is that PersistentView needs to be re-thought: >> instead of tying it to a persistenceId like we do now we should just >> provide an API for subscribing to named topics in the Journal—be that >> persistenceIds of some PersistentActors or synthetic ones. One Actor should >> be able to subscribe to any number of them, but the onus will be on it to >> keep track of the positions up to which it has consumed from all of them. >> >> This does not preclude the Journal from providing a synthetic topic with >> proper linearization for all events in it (or whatever you want to >> specifically configure on the storage back-end, outside of the Journal >> SPI). And this also does not invalidate my point that normally the >> consumption of Queries should be done directly from the backing store, >> making full use of its unique feature set. >> >> >> I believe each of these is readily achievable with Akka but: >> >> >> (i) doesn’t mean explicitly persisting the events to specific topics as >> you suggest in your (1) (although this may be how some stores implement the >> required functionality on the read side). Instead it means transparently >> including information like the actorId, event type, actor type, probably >> the time and possibly information to help with causal ordering (see my next >> post). >> >> No, again we need to strictly keep Topics and Queries separate, they are >> very different features. Topics are defined up-front and explicitly written >> to, Queries are constructed later based on the existing event log contents. >> Marking events within the store with timestamps of some kind might help >> achieving a pseudo-deterministic behavior, but it is by no means a >> guarantee. Causal ordering is out of scope, and it also does not help in >> achieving the desired ability to replay Queries from some given point in >> the past. >> >> >> I think we do agree somewhere in there but I don't think as was suggested >> (by you earlier?) that creating topics up-front whether a fixed set or >> arbitrary tags will work. I feel in what way the store supports the >> queries (and how much it can) is up to the store (e.g. creating separate >> topics or synthetic topics), so I would argue against using topics for >> CQRS. As I mention below for Pub/Sub to Persistent topics it would be >> great, but not for CQRS. >> >> >> Yes, indeed, topics are interesting but not strictly related to CQRS. >> >> C. CQRS with Event Sourcing >> >> >> And finally, there is CQRS with Event Sourcing, which I believe is much >> more that (A) and (B) and particularly doesn’t necessarily require (B.) for >> all event stores. So if Akka were to implement (B), which I think would be >> very useful for other reasons, it would not specifically be for CQRS. >> >> >> Please consider this diagram overviewing CQRS with Event Sourcing: >> >> >> <https://www.dropbox.com/s/z2iu0xi4ki42sl7/annotated_cqrs_ >> architecture.jpg >> <https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fz2iu0xi4ki42sl7%2Fannotated_cqrs_architecture.jpg&sa=D&sntz=1&usg=AFQjCNEc6KMEVqIPtBTH05x6rYSiCaxUCw> >> > >> >> >> For example, a saga could be waiting for an event indicating funds had >> been withdrawn from a bank account after it had issued a command requesting >> that be done. The saga could subscribe to events from the bank account >> before issuing the command and watch for a specific event from that time on. >> >> Why would the Sage subscribe to events instead of talking with the domain >> entities directly? >> >> >> I believe it is for loose coupling and to make the process asynchronous >> (and event-driven). >> >> >> Actor messaging already has those qualities, no event store necessary. >> >> When an AR processes a command it cannot know all the other ARs or sagas >> wanting to know when the command has been performed. >> >> >> It will be the Saga that has sent the Command, so yes, it will know whom >> to reply to (unless I misunderstand what a Saga is). Another consideration >> is that modeling the replies by the Saga subscribing to the events produced >> by various aggregates (in the example linked to below) involves a large >> overhead as compared to directly receiving just those events pertaining to >> its own commands—this is best done within the target aggregate by simple >> sending them with the tell operator after having received the confirmation >> from the persistent store. >> >> Also in an actor-based system to be reliable(?) I would assume sagas >> need to read events from a persistent store (or receive messages with >> at-least-once-delivery guarantee). >> >> >> The Saga persist its own progress and retries commands that are not >> confirmed within a timeout (or falls back to different strategies or fails >> the overall request). This makes it reliable in exactly the right way >> without unnecessary overhead. >> >> >> Please check out the short section on Sagas from the CQRS Journey book: >> >> http://msdn.microsoft.com/en-us/library/jj591569.aspx >> >> Particularly Figure 2. >> >> I believe the black filled arrows are events and the white hollow arrows >> are commands. Commands I believe are well suited to actor messages but >> events I believe are best suited to persistent publish/subscribe-like >> communication (i.e. the journal). To be honest though, I note that the >> text talks about event messages, although it also talks about the event >> messages using an event bus, so I am a little unsure. >> >> >> >> My understanding is that the Saga sits logically on the top left side of >> the first diagram, acting on behalf of and just like the user (and like the >> user it should have a memory and be persistent). >> >> >> My understanding is that sagas sit where the Services are in the diagram >> I provided (near [2]), i.e. they issue commands (not labelled as such in >> the diagram unfortunately but what else could they be?) and listen for >> events on the write side (as labelled). >> >> <https://www.dropbox.com/s/z2iu0xi4ki42sl7/annotated_cqrs_ >> architecture.jpg >> <https://www.google.com/url?q=https%3A%2F%2Fwww.dropbox.com%2Fs%2Fz2iu0xi4ki42sl7%2Fannotated_cqrs_architecture.jpg&sa=D&sntz=1&usg=AFQjCNEc6KMEVqIPtBTH05x6rYSiCaxUCw> >> > >> >> Someone please correct me if I am wrong. >> >> >> I don’t know about being wrong, I’m just making up my mind based on what >> I find useful, and if my conclusions are wrong I trust people will tell me >> so eventually ;-) >> >> >> This is the dashed area labelled [3] in the diagram. >> >> >> Akka seems to distribute the event store used for persistence of ARs [1] >> on the write side to the read side, which is an interesting idea. But I >> don’t believe this is enough for CQRS. One event store cannot provide all >> the required read models. >> >> >> This is probably where all (our) misunderstanding originates: >> PersistentView is a very particular thing and it turns out that it does not >> actually match up with the Q in CQRS. Perhaps we should indeed just remove >> it and add a facility which lets Actors query the Journal instead (in case >> you want to roll your own read model adapter). >> >> >> PersistentViews tied to one PersistentActor we know are too limited. >> However, I think PersistentViews tied to named query streams (specified to >> the journal) would be useful (if they could guaranteed at least once >> delivery to an actor representing a query store). >> >> >> If we change the View feature in the way I suggested above then we have >> all the pieces already, AtLeastOnceDelivery or persist() could be used to >> reliably write projections into another store where needed. >> >> >> Thank you for your patience reading through all of this text. >> >> >> Thank you for this discussion, it is very useful and enjoyable! >> >> Regards, >> >> Roland >> >> >> Cheers, >> Ashley. >> >> >> >> -- >> >>>>>>>>>> Read the docs: http://akka.io/docs/ >> >>>>>>>>>> Check the FAQ: http://doc.akka.io/docs/ >> 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