How do I get a list of worker threads of nservicebus. I need to register workerThread ids in to db and then bind some type of messages to the exact workerthread. Real idea is handling poison messages. Want to block all the threads not to handle poison messages except specified ones. There will be a seperate service that will manage threads through database.
I would not try to do that. It is almost sure to run into problems.
Of course, in order to get some sort of "identity" for each thread, you could place something like this in your message handler:
[ThreadStatic]
private static readonly Guid ThreadId = Guid.NewGuid();
But again, I wouldn't do that! The guids would change every time the endpoint was restarted, for one.
You could also query the list of threads direct from .NET and try to determine which ones were the message handling threads, but that sounds so scary I don't even want to go into it.
The real issue: Poison Message Handling
As your comment states, the real problem is that a poison message is REALLY poison. Not only is it failing, but it's taking so long to do so that it's really screwing up all the other threads!
Since you are able to identify these messages based on certain properties of the message, I would detect and throw an exception before the operation that times out. All the time.
If you want to be able to test periodically to see if the issue has been fixed, you have a few options:
Test via other means, and return the messages to the source queue when it has been fixed.
Add an appSetting so that the quick-throw behavior is skipped when the config setting is enabled. Then periodically you can edit the config, restart the endpoint, see if it's fixed, and then switch it back if it isn't.
Create another message handler that maintains a thread-locked increment value of zero. Send it a control message to say "Hey, try one now." Then your quick-throw behavior can decrement that value and allow one through to see what happens. This is also dangerous of course. Make sure your locking is tight since you are now sharing this state between different message processing threads.
Related
Let's say I have one ActiveMQ Broker and an undefined numbers of consumers.
Problem:
To process a message, consumers need an external service which is either "DATA1" or "DATA2" (specified in the message)
Each server, "DATA1" and "DATA2", can only handle 20 connections
So at most 20 "DATA1" and 20 "DATA2" messages must be dispatched at any time
Because of priorization, the messages must be enqueued in the same queue
Even if message A has a higher prio than message B, if A can't be processed because the external service has no free slots, message B needs to be processed instead
How can this be solved? As long as I was using message pulling (prefetch of 0), I was able to do this by using a BrokerPlugin that, on messagePull, achieved this by using semaphores and selectors. If the limits were reached, the pull returned null.
However, due to performance issues I had to set prefetch to 1 and use push instead. Therefore, my messagePull hack no longer works (it's never called).
So far I'm considering implementing a custom Cursor but I was wondering if someone knows a better solution.
Update the custom cursor worked but broke features like message removal. I tried with a custom Queue and QueueDispatchSelector (which is a pain to configure since there isn't a proper API to do so) and it mostly works but I still have synchronisation issues.
Also, a very suitable API seems to be DispatchPolicy, however, while it is referenced by Queue, it's never used.
Queues give you buffering for system processing time for free. Messages are delivered on demand. With prefetch=0 or prefetch=1, should effectively get you there. Messages will only be delivered to a consumer when the consumer is ready (ie.. during the consumer.receive() method).
consumer.receive() is a blocking call, so you should not need any custom plugin or other to delay delivery until the consumer process (and its required downstream services) are ready to handle it.
The behavior should work out-of-the-box, or there are some details to your use case that are not provided to shed more light on the scenario.
In my app(multiple instances), we occasionally see the case where connection is lost between my app and rabbitmq due to network issues(my app and rabbitmq are both alive), then after connection is recovered(re-established) we will receive messages that are unacked.
This creates an issue for us, because my app wasn't dead, and it is still processing the same message it received before, but now the message is redeivered, and it causes the app to process the message again (which can be fatal to us).
Since the app has multiple instances, it is not easy for an instance to check if another instance is processing the same message at the same time. We can't simply filter out redelivered message, because we need this feature to handle instance/app crashes/re-deployments.
It doesn't seem that there is an api to tell rabbitmq when to not redeliver unacked messages.
So what is the recommended practice to handle this situation ?
Thanks,
The general solution for such scenario is to make the consumers handle the messages in an idempotent manner . Generally what I do is from the producer side ( in case there is no unique identifier in the message body ) I add an attribute idempotencyId to the message body which is a guid and on the consumer side for each message this id is validated against the stored value in database , any duplicates are rejected.
This approach also works for messages which might be shoveled from another cluster or if in a same cluster multiple instances of consumers are listening then too this approach guarantee one time processing.
Would suggest to go over the RabbitMQ Reliability Guide here
Yeah, exactly-once delivery is not something RabbitMQ is good at. In fact, I'd say you should probably not be using it for these kinds of problems. Honestly, the only way to truly fix this is to use distributed transactions or locking.
Anyway, you could turn the problem on its head by ack'ing the message as soon as the consumer gets it, before it starts working on it. That would avoid the RabbitMQ-related duplication issue at least. This is at-most-once delivery.
Of course, it means that if the consumer crashes, the message is lost forever. So you need to persist the message right before you ack it so you can recover it later and also the consumer should remove it once it's complete.
Considering that crashes are rare, you can then have a single dedicated process that just works on those persisted messages. Or for that matter, handle them manually.
Just be aware that you are pushing the duplication problem in front of you, because the consumer might fail to remove the persisted message after it's done working with it anyway, but at least you have the option to implement it however you want.
Storage in this case could be anything from files, a RDBMS or something like ZooKeeper or Redis to lock/unlock in-flight messages.
In some exceptional situations I need somehow to tell consumer on receiving point that some messages shouldn’t be processed. Otherwise two systems will become out-of-sync (we deal with some outdates external systems, and if, for example, connection is dropped we have to discard all queued operations in scope of that connection).
Take a risk and resolve problem messages manually? Compensation actions (that could be tough to support in my case)? Anything else?
There are a few ways:
You can set a time-to-live when sending a message: await endpoint.Send(myMessage, c => c.TimeToLive = TimeSpan.FromHours(1));, but this will apply to all messages that are sent (or published) like this. I would consider this, after looking at your requirements. This is technical, but it is a proper messaging pattern.
Make TTL and generation timestamp properties of your message itself and let the consumer decide if the message is still worth processing. This is more business and, probably, the most correct way.
Combine tech and business - keep the timestamp and TTL in message headers so they don't pollute your message contracts, and filter them out using a custom middleware. In this case, you need to be careful to log such drops so you won't be left wonder why messages disappear now and then.
Almost any unreliable integration can be monitored using sagas, with timeouts. For example, we use a saga to integrate with Twilio. Since we have no ability to open a webhook for them, we poll after some interval to check the message status. You can start a saga when you get a message and schedule a message to check if the processing is still waiting. As discussed in comments, you can either use the "human intervention required" way to fix the issue or let the saga decide to drop the message.
A similar way could be to use a lookup table, where you put the list of messages that aren't relevant for processing. Such a table would be similar to the list of sagas. It seems that this way would also require scheduling. Both here, and for the saga, I'd recommend using a separate receive endpoint (a queue) for the DropIt message, with only one consumer. It would prevent DropIt messages from getting stuck behind the integration messages that are waiting to be processed (and some should be already dropped)
Use RMQ management API to remove messages from the queue. This is the worst method, I won't recommend it.
From what I understand, you're building a system that sends messages to 3rd party systems. In other words, systems you don't control. It has an API but compensating actions aren't always possible, because the API doesn't provide it or because actions are performed inside the 3rd party system that can't be compensated or rolled back?
If possible try to solve this via sagas. Make sure the saga executes the different steps (the sending of messages) in the right order. So that messages that cannot be compensated are sent last. This way message that can be compensated if they fail, will be compensated by the saga. The ones that cannot be compensated should be sent last, when you're as sure as possible that they don't have to be compensated. Because that last message is the last step in synchronizing all systems.
All in all this is one of the problems with distributed systems, keeping everything in sync. Compensating actions is the way to deal with this. If compensating actions aren't possible, you're in a very difficult situation. Try to see if the business can help by becoming more flexible and accepting that you need to compensate things, where they'll tell you it's not possible.
In some exceptional situations I need somehow to tell consumer on receiving point that some messages shouldn’t be processed.
Can't you revert this into:
Tell the consumer that an earlier message can be processed.
This way you can easily turn this in a state machine (like a saga) that acts on two messages. If the 2nd message never arrives then you can discard the 1st after a while or do something else.
The strategy here is to halt/wait until certain that no actions need to be reverted.
I'm working with RabbitMQ and I'd like to have multiple consumers doing different things for the same message, with this message being exactly in one queue.Each consumer would work on his own, and in the moment the consumer ends with his part, it marks the message as having completed phase "x" , when all the phases are completed for one message, then use the method a basicAck() to remove our message from the queue.
I suspect this to be impossible, if so, I would face this in other way. Having multiple queues with the same message ( using an exchange), each queue with a different consumer , which would communicate with with a Server. This server would then work with a database and checking/updating the completed phases. When all the phases are completed, log it in some way.
But this workaround seems exceedingly unefficient, I'd like to skip it if posssible.
Could it be posssible to set "states" or "phases" to a message in rabbitMQ?
So, first of all, in the context you're talking about, a "message" is an order to do some unit of work.
The first part of your question, by referring to "marking the message" treats the message as a stateful object. This is incorrect. Once a message is produced, it is immutable, meaning no changes are permitted to it. If you violate, or attempt to violate this principle, you have made an excursion beyond the realm of sound design.
So, let's reframe. In a properly-archtiected message-oriented system, a message can represent either a command ("do something") or an event ("something happened"). Note that sometimes we can call a reply message (something sent in response to a command) a third category, but it's really a sub-category of event.
Thus, we are led to the possibility of having (a) one message going to one queue, to be picked up by one consumer, or (b) one message going to many queues, to be picked up by many consumers. You take (a) and (b) to compose complex system behaviors that evolve over time with the execution of each of these small behaviors, and suddenly you have a complex system.
Messages do, in fact, have state. Their state is "processed" or "unprocessed", as appropriate. That is the limit to their statefulness.
Bottom Line
Your situation describes a series of activities (what each consumer does) being acted upon some sort of shared state among the activities. The role of messages and the message broker is to assist in the orchestration of these activities, by providing instruction on what to do (via commands) and what took place (via events). Messages themselves cannot be the shared state. So, you still need some sort of a database or other means to persist the state of your system. There is no way to avoid this.
I have part of my application that receives string messages from remote clients and decodes these into a _Message class. I then want to pass these messages into a queue for immediate processing. The FIFO method is exactly what I require as I would particularly prefer to process these messages in order of receiving.
These messages come in fairly constant (24 hours a day, maybe 1 every couple of seconds or so...) so I need to ensure that I capture them all and no messages get lost or rejected.
Each _Message will then run through a Routine which will decode and action various parts of the message content.
Therefore, what would be the best way of handling a constant message pool? I started to go down the path of Queues with Queue.Enqueue and Queue.Dequeue but I'm not sure how to constantly poll for items within the Queue without affecting performance or resources.
I then came across ThreadPooling (something very new to me) which sounds like it could be down the right path, but I'm not 100% sure on how it works or how to set it up correctly.
Or....can I use ThreadPooling in conjunction with a Queue? And simply add items into my Queue and have the ThreadPool automatically detect new items?
Any help or guidance would be appreciated. Thanks