I'm trying to learn DIS for a small project that I've in mind.
Basically I've a process that run a scenario, and it can receive external commands for creating and removing entities.
I've another process, a map, that can send commands to the scenario process, and I've two cases:
The map process send a command for creating a new entity, the scenario process receives it, and creates the new entity.
The map process can create a new entity without external commands (i.e. triggered by internal scenario logic). This new entity should be notified in DIS.
DIS CreateEntity PDU has following fields:
OriginatingEntityID
ReceivingEntityID
Which data should be inserted here by the map process in order to send the CreteEntity command? How can I specify which kind of player I want to create (F15, Soldier)?
In the second case, how can I notify that a new player was created without external commands?
In second case
It all depends on the design of your simulation.
A SM (simulation manager - that you have to create) would create EntityIDs and you would use these ID in your CreateEntity PDU. You can also hard-coded them or create your own custom algorithm to generate them. DIS, by itself, doesn't define an EntityIDs generation mechanism but it does require that each EntityID to be unique.
That being said, DIS requires all entities to be updated at least once per 5 secs (not that much true for DIS v7 since that delay can now be managed per entity).
Most of the DIS compatible software I know monitor the EntityState PDU to detect new objects. If an object hasn't been seen for more than 5 sec, you can assume it has been destroyed.
Hope this helps.
Related
I am using Anylogic for a simulation-modeling class, and I am not anylogic or coding smart. My last and only coding class was MatLab based about 16 yrs ago. I have a few questions about how to implement modeling concepts in a discrete model with anylogic.
How can I add/inject agents directly into a queue downstream from a source? I have tried adding an additional source to use the “Calls of inject() function,” but I am not sure how to implement it after selecting it ( example: what do I do after selecting the Calls of inject() function). I have the new source feeding directly into the queue where I want the inject.
How can I set the release of an agent to a defined schedule instead of a rate? Currently, I have my working model set to interarrival time. But I would like to set the agent release to a defined schedule. (example: agent-1 released at 120 seconds, agent-2 released at 150 seconds, agent-3 released at 270 seconds)
Any help would be greatly appreciated, especially if it can be written in a “explain to me like I am 5yrs old” format.
Question 1:
If you have a source connected directly to a queue, then when you call source.inject() an agent will be created at the source block and go to the queue. If you have 1 source with multiple possible destinations, then you will have to use select output blocks and some criteria to go from the source to the desired queue.
Since you mentioned not being a strong programmer, this probably wouldn't be for you, but I often find myself creating agents via add_population and then just adding them to an ArrayList until I am ready to pull them into the DES flow. Really, there are near infinite ways to control agent flow within AnyLogic.
Question 2:
Option a: Arrivals by "Arrival Table in Database" You can link an AnyLogic database table to Excel, and then the source block will just have an agent arrive based on that table.
Option b: Arrival Schedule - you could set this up manually within the development environment or load your schedule from a database. I prefer option a over option b given your brief description.
Option c: Read in data to variable and then write code to release based on next arrival time. 1,000s of ways to do this, but one example could be a list of doubles (your arrival times), set an event to delay until next arrival, call inject function, remove that arrival from the list. I think option a would be best for you, but given that AnyLogic allows you to add java code, there are no limits to how sophisticated you could make your arrival logic.
For 2) You could also use an event or a dynamic event. The action could be source.inject(1); and you can schedule them to your preferences with variables. Just be vigilant that you re-start the events if necessary.
There is a demo-model from AnyLogic for dynamic events.
I'm new to DDD and cutting my teeth on the following exercise. The use case is real, but my attempt to solve it with DDD is purely for learning.
We have multiple Git repos, each containing a file that we call
product spec. The system needs to respond to a HTTP POST by cloning all
the repos, and then update the product spec in those that match some
information in the POST body. System also needs to log the POST request as the cause for updating the product spec.
I'd like to use Aggregates and event sourcing for solving this problem because they seem like a good fit. Event sourcing comes with automatic persistence of the commands, so if I convert the POST body to a command, I get auditing for free.
Problem is, the POST may match multiple product spec. I'm not sure how to deal with that. Should I create a domain service, let it find all the matching product spec and then issue an update command to each? Or should I have the aggregate root do so? If using aggregate root to update multiple entities, it itself needs to be an entity, so what would it be in my problem domain?
The first comment to your question is right (the one of #VoiceOfUnreason): this 'is mostly side effect coordination'.
But I will try to answer your question: How to solve this using DDD / Event Sourcing:
The first aggregate root could just be named: 'MultipleRepoOperations'. This aggregate root has only one stream of events.
The command that fires the whole process could be: 'CloneAndUpdateProdSpecRepos' which carries a list of all the repos to be cloned and updated.
When the aggregate root processes the command it will simply spit a bunch of events of type 'UserRequestedToCloneAndUpdateProdSpec'
The second bounded context manages all the repos, and it its subscribed to all the events from 'MultipleRepoOperations' and will receive each event emitted by it. This bounded context aggregate root can be called: 'GitRepoManagement', and has a stream per repo. Eg: GitRepoManagement-Repo1, GitRepoManagement-Repo215, GitRepoManagement-20158, etc.
'GitRepoManagement' receives each event of type 'UserRequestedToCloneAndUpdateProdSpec', replays its corresponding repo stream in order to rehydrate the current state, and then tries to clone and update the product spec for the repo. When fails emits a failed event or a suceed if appropiate.
for learning purposes try to choose problem domain that has more complex rules and logic, where many actions is needed. for example small game (card game,multiplayer quiz game or whatever). or simulate some real world process like school management or some business process.
Suppose I have an aggregate containing some data and when it reaches a certain state, I'd like to take all that state and pass it to some outside service. For argument and simplicity's sake, lets just say it is an aggregate that has a list and when all items in that list are checked off, I'd like to send the entire state to some outside service. Now when I'm handling the command for checking off the last item in the list, I'll know that I'm at the end but it doesn't seem correct to send it to the outside system from the processing of the command. So given this scenario what is the recommended approach if the outside system requires all of the state of the aggregate. Should the outside system build its own copy of the data based on the aggregate events or is there some better approach?
Should the outside system build its own copy of the data based on the aggregate events.
Probably not -- it's almost never a good idea to share the responsibility of rehydrating an aggregate from its history. The service that owns the object should be responsible for rehydration.
First key idea to understand is when in the flow the call to the outside service should happen.
First, the domain model processes the command arguments, computing the update to the event history, including the ChecklistCompleted event.
The application takes that history, and saves it to the book of record
The transaction completes successfully.
At this point, the application knows that the operation was successful, but the caller doesn't. So the usual answer is to be thinking of an asynchronous operation that will do the rest of the work.
Possibility one: the application takes the history that it just saved, and uses that history to create schedule a task to rehydrate a read-only copy of the aggregate state, and then send that state to the external service.
Possibility two: you ditch the copy of the history that you have now, and fire off an asynchronous task that has enough information to load its own copy of the history from the book of record.
There are at least three ways that you might do this. First, you could have the command schedule the task as before.
Second, you could have a event handler listening for ChecklistCompleted events in the book of record, and have that handler schedule the task.
Third, you could read the ChecklistCompleted event from the book of record, and publish a representation of that event to a shared bus, and let the handler in the external service call you back for a copy of the state.
I was under the impression that one bounded context should not reach out to get state from another bounded context but rather keep local copies of the data it needed.
From my experience, the key idea is that the services shouldn't block each other -- or more specifically, a call to service B should not block when service A is unavailable. Responding to events is fundamentally non blocking; does it really matter that we respond to an asynchronously delivered event by making an asynchronous blocking call?
What this buys you, however, is independent evolution of the two services - A broadcasts an event, B reacts to the event by calling A and asking for a representation of the aggregate that B understands, A -- being backwards compatible -- delivers the requested representation.
Compare this with requiring a new release of B every time the rehydration logic in A changes.
Udi Dahan raised a challenging idea - the notion that each piece of data belongs to a singe technical authority. "Raw business data" should not be replicated between services.
A service is the technical authority for a specific business capability.
Any piece of data or rule must be owned by only one service.
So in Udi's approach, you'd start to investigate why B has any responsibility for data owned by A, and from there determine how to align that responsibility and the data into a single service. (Part of the trick: the physical view of a service can span process boundaries; in other words, a process may be composed from components that belong to more than one service).
Jeppe Cramon series on microservices is nicely sourced, and touches on many of the points above.
You should never externalise your state. Reporting on that state is a function of the read side, as it produces reports and you'll need that data to call the service. The structure of your state is plastic, and you shouldn't have an external service that relies up that structure otherwise you'll have to update both in lockstep which is a bad thing.
There is a blog that puts forward a strong argument that the process manager is the correct place to put this type of feature (calling an external service), because that's the appropriate place for orchestrating events.
I'm working on an event processing pipeline based on Akka actors. I have 3 actors for each step of the pipeline: FilterWorker, EnrichWorker and ProcessWorker; plus a supervisor actor that makes sure the events are sent from one step of the pipeline to the next.
The enrich step might need to query some external database for extra data or even create new data that I'll want to persist. For example, the enrich step of a web analytics system might want to enrich a click event with the user that made the click and store that user information in a database.
Keeping in mind that example, I see the following options:
1.Use a singleton; e.g. UserStore that keeps in memory all the users gathered so far and saves them to the database once in a while; has all the logic to fetch users that are not yet in memory. Doesn't seem like a good idea to use a singleton in an actor system however (?).
Use a store actor. Use tell to add a new user and ask to fetch it.
Is there a better pattern for this?
Thanks!
In order to not leave this unanswered, I went with my second option and johanandren's suggestion of having an Actor fill the data store role. Works pretty well!
I'm trying to play around with DDD and CQRS.
And I got this two solutions :
add AggregateId to my command / event. It's nice beauce I can use my command as my web service's parameter, and I can as well return some instance of my command to my forms for saying "you can do this command,t his one and this one"
add my full Aggregate to my command / event. It's nice because I'm sure that I won't load my aggregate 100 times if there is a lot of event going on, I'll just pass my reference around (for instance I won't load it in my command's validator and in my command handler). But i'd add to create a parameter class for each command wih only the id.
For now I have the id in the commands and the full model in the events (I trust my unit of work for caching the Load(aggregateId) so i won't execute the same request 100 for 1 command).
Is there a right / better way ?
Yes your current approach is correct - reference the aggregate with an identity value on the command. A command is meant to be serialized and sent across process boundaries. Also, a command is normally constructed by a client who may not have enough information to create an entire aggregate instance. This is also why an identity should be used. And yes, your unit of work should take care of caching an aggregate for the duration of a unit of work, if need be.