we are currently working in a message driven Microservice environment and some of our messages/events are event sourced (using Apache Kafka). Now we are struggling with implementing more complex business requirements, were we have to take multiple events into account to create new events and side effects.
In the current situation we are working with devices that can produce errors and we already process them and have a single topic which contains ERROR_OCCURRED and ERROR_RESOLVED events (so they are in order). We also make sure, that all messages regarding a specific device always go onto the same partition. And both messages share an ID that identifies that specific error incident. We already have a projection that consumes those events and provides an API for our customers, s.t. they can see all occurred errors and their current state.
Now we have to deal with the following requirement:
Reporting Errors
We need a push system that reports errors of devices to our external partners, but only after 15 minutes and if they have not been resolved in that timeframe. Our first approach was to consume all ERROR_RESOLVED events, store the IDs and have another consumer that is handling the ERROR_OCCURRED events in a delayed fashion (e.g. by only consuming the next ERROR_OCCURRED event on the topic if its timestamp is at least 15 minutes old). We would then be able to know if that particular error has already been resolved and does not need to be reported (since they share a common ID with the corresponding ERROR_RESOLVED event). Otherwise we send an HTTP request to our external partner and create an ERROR_REPORTED event on a new topic. Is there any better approach for delayed and conditional message processing?
We also have to take the following special use cases into account:
Service restarts: currently we are planning to keep the list of resolved errors in memory, so if a service restarts, that list has to be created from scratch. We could just replay the ERROR_RESOLVED messages, but that may take some time and in that time no ERROR_OCCURRED events should be processed because that may result in reporting errors that have been resolved in less then 15 minutes, but we are just not aware of it. Are there any good practices regarding replay vs. "normal" processing?
Scaling: we may increase or decrease the number of instances of our service at any time, so the partition assignment may change during runtime. That should not be a problem if we create a consumer group for each service instance when consuming the ERROR_RESOLVED events, s.t. every instance knows all resolved errors while still only handling the ERROR_OCCURRED events of its assigned partitions (in another consumer group which is shared by all instances). Is there a better approach for handling partition reassignment and internal state?
Thanks in advance!
For side effects, I would record all "side" actions in the event store. In your particular example, when it is time to send a notification, I would call SEND_NOTIFICATION command that emit NOTIFICATION_SENT event. These events would be processed by some worker process that does actual HTTP request.
Actually I would elaborate this even furter, since notifications could fail, so I would have, say, two events NOTIFICATION_REQUIRED, and NORIFICATION_SENT, so we can retry failed notifications.
And finally your logic would be "if error was not resolved in 15 minutes and notification was not sent - send a notification (or just discard if it missed its timeframe)"
I was trying to understanding ES+CQRS and tech stack can be used.
As per my understanding flow should be as below.
UI sends a request to Controller(HTTP Adapter)
Controller calls application service by passing Request Object as parameter.
Application Service creates Command from Request Object passed from controller.
Application Service pass this Command to Message Consumer.
Message Consumer publish Command to message broker(RabbitMQ)
Two Subscriber will be listening for above command
a. One subscriber will generate Aggregate from eventStore using command
and will apply command than generated event will be stored in event store.
b. Another subscriber will be at VIEW end,that will populate data in view database/cache.
Kindly suggest my understanding is correct.
Kindly suggest my understanding is correct
I think you've gotten a bit tangled in your middleware.
As a rule, CQRS means that the writes happen to one data model, and reads in another. So the views aren't watching commands, they are watching the book of record.
So in the subscriber that actually processes the command, the command handler will load the current state from the book of record into memory, update the copy in memory according to the domain model, and then replace the state in the book of record with the updated version.
Having update the book of record, we can now trigger a refresh of the data model that backs the view; no business logic is run here, this is purely a transform of the data from the model we use for writes to the model we use for reads.
When we add event sourcing, this pattern is the same -- the distinction is that the data model we use for writes is a history of events.
How atomicity is achieved in writing data in event store and writing data in VIEW Model?
It's not -- we don't try to make those two actions atomic.
how do we handle if event is stored in EventStrore but System got crashed before we send event in Message Queue
The key idea is to realize that we typically build new views by reading events out of the event store; not by reading the events out of the message queue. The events in the queue just tell us that an update is available. In the absence of events appearing in the message queue, we can still poll the event store watching for updates.
Therefore, if the event store is unreachable, you just leave the stale copy of the view in place, and wait for the system to recover.
If the event store is reachable, but the message queue isn't, then you update the view (if necessary) on some predetermined schedule.
This is where the eventual consistency part comes in. Given a successful write into the event store, we are promising that the effects of that write will be visible in a finite amount of time.
I am trying to observe sent messages using SendObserver on an ISendEndpoint. When I use GetSendEndpoint from the consume context and add the observer using ConnectSendObserver I notice that the previous observers added from previous messages still exist, so the observer is called multiple times after the first message is sent.
Please note that I have to set the observer through the consume context.
You should use the ConnectHandle returned when the observer is connected to disconnect the observer once the sent messages have been observed. In your case, once the ConsumeContext is no longer being used - such as at the end of the consumer.
That way, you don't accumulate them over time.
I'm writing a library that can interact with a socket server that transmits data as events to certain actions my library sends it.
I created an Actions module that formats the actions so that the server can read it. It also generates an action_id, because the events parser can identify it with the action that sent it. There are more than one event per action possible.
While I'm sending my action to the server, the event parser is still getting data from the server, so they work independent from each other (but then again they do work together: events response aggregator triggers the action callback).
In my model, I want to get a list of some resource from the server. The server sends its data one line at a time, but that's being handled by the events aggregator, so don't worry about that.
Okay, my problem:
In my model I am requesting the resources, but since the events are being parsed in another thread, I need to do a "infinite" loop that checks if the list is filled, and then break out to return it to the consumer of the model (e.g. my controller).
Is there another (better) way of doing this or am I on the right track? I would love your thoughts :)
Here is my story in code: https://gist.github.com/anonymous/8652934
Check out Ruby EventMachine.
It's designed to simplify this sort of reactor pattern application.
It depends on the implementation. In the code you provide you're not showing how actually the request and responses are processed.
If you know exactly the number of responses you're supposed to receive, in each one you could check if all are completed, then execute an specific action. e.g.
# suppose response_receiver is the method which receives the server response
def response_receiver data
#responses_list << data
if #response_list.size == #expected_size
# Execute some action
end
end
The documentation for the Win32 API PulseEvent() function (kernel32.dll) states that this function is “… unreliable and should not be used by new applications. Instead, use condition variables”. However, condition variables cannot be used across process boundaries like (named) events can.
I have a scenario that is cross-process, cross-runtime (native and managed code) in which a single producer occasionally has something interesting to make known to zero or more consumers. Right now, a well-known named event is used (and set to signaled state) by the producer using this PulseEvent function when it needs to make something known. Zero or more consumers wait on that event (WaitForSingleObject()) and perform an action in response. There is no need for two-way communication in my scenario, and the producer does not need to know if the event has any listeners, nor does it need to know if the event was successfully acted upon. On the other hand, I do not want any consumers to ever miss any events. In other words, the system needs to be perfectly reliable – but the producer does not need to know if that is the case or not. The scenario can be thought of as a “clock ticker” – i.e., the producer provides a semi-regular signal for zero or more consumers to count. And all consumers must have the correct count over any given period of time. No polling by consumers is allowed (performance reasons). The ticker is just a few milliseconds (20 or so, but not perfectly regular).
Raymen Chen (The Old New Thing) has a blog post pointing out the “fundamentally flawed” nature of the PulseEvent() function, but I do not see an alternative for my scenario from Chen or the posted comments.
Can anyone please suggest one?
Please keep in mind that the IPC signal must cross process boundries on the machine, not simply threads. And the solution needs to have high performance in that consumers must be able to act within 10ms of each event.
I think you're going to need something a little more complex to hit your reliability target.
My understanding of your problem is that you have one producer and an unknown number of consumers all of which are different processes. Each consumer can NEVER miss any events.
I'd like more clarification as to what missing an event means.
i) if a consumer started to run and got to just before it waited on your notification method and an event occurred should it process it even though it wasn't quite ready at the point that the notification was sent? (i.e. when is a consumer considered to be active? when it starts or when it processes its first event)
ii) likewise, if the consumer is processing an event and the code that waits on the next notification hasn't yet begun its wait (I'm assuming a Wait -> Process -> Loop to Wait code structure) then should it know that another event occurred whilst it was looping around?
I'd assume that i) is a "not really" as it's a race between process start up and being "ready" and ii) is "yes"; that is notifications are, effectively, queued per consumer once the consumer is present and each consumer gets to consume all events that are produced whilst it's active and doesn't get to skip any.
So, what you're after is the ability to send a stream of notifications to a set of consumers where a consumer is guaranteed to act on all notifications in that stream from the point where it acts on the first to the point where it shuts down. i.e. if the producer produces the following stream of notifications
1 2 3 4 5 6 7 8 9 0
and consumer a) starts up and processes 3, it should also process 4-0
if consumer b) starts up and processes 5 but is shut down after 9 then it should have processed 5,6,7,8,9
if consumer c) was running when the notifications began it should have processed 1-0
etc.
Simply pulsing an event wont work. If a consumer is not actively waiting on the event when the event is pulsed then it will miss the event so we will fail if events are produced faster than we can loop around to wait on the event again.
Using a semaphore also wont work as if one consumer runs faster than another consumer to such an extent that it can loop around to the semaphore call before the other completes processing and if there's another notification within that time then one consumer could process an event more than once and one could miss one. That is you may well release 3 threads (if the producer knows there are 3 consumers) but you cant ensure that each consumer is released just the once.
A ring buffer of events (tick counts) in shared memory with each consumer knowing the value of the event it last processed and with consumers alerted via a pulsed event should work at the expense of some of the consumers being out of sync with the ticks sometimes; that is if they miss one they will catch up next time they get pulsed. As long as the ring buffer is big enough so that all consumers can process the events before the producer loops in the buffer you should be OK.
With the example above, if consumer d misses the pulse for event 4 because it wasn't waiting on its event at the time and it then settles into a wait it will be woken when event 5 is produced and since it's last processed counted is 3 it will process 4 and 5 and then loop back to the event...
If this isn't good enough then I'd suggest something like PGM via sockets to give you a reliable multicast; the advantage of this would be that you could move your consumers off onto different machines...
The reason PulseEvent is "unreliable" is not so much because of anything wrong in the function itself, just that if your consumer doesn't happen to be waiting on the event at the exact moment that PulseEvent is called, it'll miss it.
In your scenario, I think the best solution is to manually keep the counter yourself. So the producer thread keeps a count of the current "clock tick" and when a consumer thread starts up, it reads the current value of that counter. Then, instead of using PulseEvent, increment the "clock ticks" counter and use SetEvent to wake all threads waiting on the tick. When the consumer thread wakes up, it checks it's "clock tick" value against the producer's "clock ticks" and it'll know how many ticks have elapsed. Just before it waits on the event again, it can check to see if another tick has occurred.
I'm not sure if I described the above very well, but hopefully that gives you an idea :)
There are two inherent problems with PulseEvent:
if it's used with auto-reset events, it releases one waiter only.
threads might never be awaken if they happen to be removed from the waiting queue due to APC at the moment of the PulseEvent.
An alternative is to broadcast a window message and have any listener have a top-level message -only window that listens to this particular message.
The main advantage of this approach is that you don't have to block your thread explicitly. The disadvantage of this approach is that your listeners have to be STA (can't have a message queue on an MTA thread).
The biggest problem with that approach would be that the processing of the event by the listener will be delayed with the amount of time it takes the queue to get to that message.
You can also make sure you use manual-reset events (so that all waiting threads are awaken) and do SetEvent/ResetEvent with some small delay (say 150ms) to give a bigger chance for threads temporarily woken by APC to pick up your event.
Of course, whether any of these alternative approaches will work for you depends on how often you need to fire your events and whether you need the listeners to process each event or just the last one they get.
If I understand your question correctly, it seems like you can simply use SetEvent. It will release one thread. Just make sure it is an auto-reset event.
If you need to allow multiple threads, you could use a named semaphore with CreateSemaphore. Each call to ReleaseSemaphore increases the count. If the count is 3, for example, and 3 threads wait on it, they will all run.
Events are more suitable for communications between the treads inside one process (unnamed events). As you have described, you have zero ore more clients that need to read something interested. I understand that the number of clients changes dynamically. In this case, the best chose will be a named pipe.
Named Pipe is King
If you need to just send data to multiple processes, it’s better to use named pipes, not the events. Unlike auto-reset events, you don't need own pipe for each of the client processes. Each named pipe has an associated server process and one or more associated client processes (and even zero). When there are many clients, many instances of the same named pipe are automatically created by the operating system for each of the clients. All instances of a named pipe share the same pipe name, but each instance has its own buffers and handles, and provides a separate conduit for client/server communication. The use of instances enables multiple pipe clients to use the same named pipe simultaneously. Any process can act as both a server for one pipe and a client for another pipe, and vice versa, making peer-to-peer communication possible.
If you will use a named pipe, there would be no need in the events at all in your scenario, and the data will have guaranteed delivery no matter what happens with the processes – each of the processes may get long delays (e.g. by a swap) but the data will be finally delivered ASAP without your special involvement.
On The Events
If you are still interested in the events -- the auto-reset event is king! ☺
The CreateEvent function has the bManualReset argument. If this parameter is TRUE, the function creates a manual-reset event object, which requires the use of the ResetEvent function to set the event state to non-signaled. This is not what you need. If this parameter is FALSE, the function creates an auto-reset event object, and system automatically resets the event state to non-signaled after a single waiting thread has been released.
These auto-reset events are very reliable and easy to use.
If you wait for an auto-reset event object with WaitForMultipleObjects or WaitForSingleObject, it reliably resets the event upon exit from these wait functions.
So create events the following way:
EventHandle := CreateEvent(nil, FALSE, FALSE, nil);
Wait for the event from one thread and do SetEvent from another thread. This is very simple and very reliable.
Don’t' ever call ResetEvent (since it automatically reset) or PulseEvent (since it is not reliable and deprecated). Even Microsoft has admitted that PulseEvent should not be used. See https://msdn.microsoft.com/en-us/library/windows/desktop/ms684914(v=vs.85).aspx
This function is unreliable and should not be used, because only those threads will be notified that are in the "wait" state at the moment PulseEvent is called. If they are in any other state, they will not be notified, and you may never know for sure what the thread state is. A thread waiting on a synchronization object can be momentarily removed from the wait state by a kernel-mode Asynchronous Procedure Call, and then returned to the wait state after the APC is complete. If the call to PulseEvent occurs during the time when the thread has been removed from the wait state, the thread will not be released because PulseEvent releases only those threads that are waiting at the moment it is called.
You can find out more about the kernel-mode Asynchronous Procedure Calls at the following links:
https://msdn.microsoft.com/en-us/library/windows/desktop/ms681951(v=vs.85).aspx
http://www.drdobbs.com/inside-nts-asynchronous-procedure-call/184416590
http://www.osronline.com/article.cfm?id=75
We have never used PulseEvent in our applications. As about auto-reset events, we are using them since Windows NT 3.51 (although they appeared in the first 32-bit version of NT - 3.1) and they work very well.
Your Inter-Process Scenario
Unfortunately, your case is a little bit more complicated. You have multiple threads in multiple processes waiting for an event, and you have to make sure that all the threads did in fact receive the notification. There is no other reliable way other than to create own event for each consumer. So, you will need to have as many events as are the consumers. Besides that, you will need to keep a list of registered consumers, where each consumer has an associated event name. So, to notify all the consumers, you will have to do SetEvent in a loop for all the consumer events. This is a very fast, reliable and cheap way. Since you are using cross-process communication, the consumers will have to register and de-register its events via other means of inter-process communication, like SendMessage. For example, when a consumer process registers itself at your main notifier process, it sends SendMessage to your process to request a unique event name. You just increment the counter and return something like Event1, Event2, etc, and creating events with that name, so the consumers will open existing events. When the consumer de-registers – it closes the event handle that it opened before, and sends another SendMessage, to let you know that you should CloseHandle too on your side to finally release this event object. If the consumer process crashes, you will end up with a dummy event, since you will not know that you should do CloseHandle, but this should not be a problem - the events are very fast and very cheap, and there is virtually no limit on the kernel objects - the per-process limit on kernel handles is 2^24. If you are still concerned, you may to the opposite – the clients create the events but you open them. If they won’t open – then the client has crashed and you just remove it from the list.