We have a requirement for all our messages to be processed in the order of arrival to MSMQ.
We will be exposing a WCF service to the clients, and this WCF service will post the messages using NServiceBus (Sendonly Bus) to MSMQ.
We are going to develop a windows service(MessageHandler), which will use Nservicebus to read the message from MSMQ and save it to the database. Our database will not be available for few hours everyday.
During the db downtime we expect that the process to retry the first message in MSMQ and halt processing other messages until the database is up. Once the database is up we want NServicebus to process in the order the message is sent.
Will setting up MaximumConcurrencyLevel="1" MaximumMessageThroughputPerSecond="1" helps in this scenario?
What is the best way using NServiceBus to handle this scenario?
We have a requirement for all our messages to be processed in the
order of arrival to MSMQ.
See the answer to this question How to handle message order in nservicebus?, and also this post here.
I am in agreement that while in-order delivery is possible, it is much better to design your system such that order does not matter. The linked article outlines the following soltuion:
Add a sequence number to all messages
in the receiver check the sequence number is the last seen number + 1 if not throw an out of sequence exception
Enable second level retries (so if they are out of order they will try again later hopefully after the correct message was received)
However, in the interest of anwering your specific question:
Will setting up MaximumConcurrencyLevel="1"
MaximumMessageThroughputPerSecond="1" helps in this scenario?
Not really.
Whenever you have a requirement for ordered delivery, the fundamental laws of logic dictate that somewhere along your message processing pipeline you must have a single-threaded process in order to guarantee in-order delivery.
Where this happens is up to you (check out the resequencer pattern), but you could certainly throttle the NserviceBus handler to a single thread (I don't think you need to set the MaximumMessageThroughputPerSecond to make it single threaded though).
However, even if you did this, and even if you used transactional queues, you could still not guarantee that each message would be dequeued and processed to the database in order, because if there are any permanent failures on any of the messages they will be removed from the queue and the next message processed.
During the db downtime we expect that the process to retry the first
message in MSMQ and halt processing other messages until the database
is up. Once the database is up we want NServicebus to process in the
order the message is sent.
This is not recommended. The second level retry functionality in NServiceBus is designed to handle unexpected and short-term outages, not planned and long-term outages.
For starters, when your NServiceBus message handler endpoint tries to process a message in it's input queue and finds the database unavailable, it will implement it's 2nd level retry policy, which by default will attempt the dequeue 5 times with increasing infrequency, and then fail permanently, sticking the failed message in it's error queue. It will then move onto the next message in the input queue.
While this doesn't violate your in-order delivery requirement on its own, it will make life very difficult for two reasons:
The permanently failed messages will need to be re-processed with priority once the database becomes available again, and
there will be a ton of unwanted failure logging, which will obfuscate any genuine handling errors.
If you have a regular planned outages which you know about in advance, then the simplest way to deal with them is to implement a service window, which another term for a schedule.
However, Windows services manager does not support the concept of service windows, so you would have to use a scheduled task to stop then start your service, or look at other options such as hangfire, quartz.net or some other cron-type library.
It kinds of depends why you need the messages to arrive in order. If it's like you first receive an Order message and then various OrderLine messages that all belong to a certain order, there are multiple possibilities.
One is to just accept that there can be OrderLine messages without an Order. The Order will come in later anyway. Eventual Consistency.
Another one is to collect messages (and possible state) in an NServiceBus Saga. When normally MessageA needs to arrive first, only to receive MessageB and MessageC later, give all three messages the ability to start the saga. All three messages need to have something that ties them together, like a unique GUID. Then the saga will make sure it collects them properly and when all messages have arrived, perhaps store its final state and mark the saga as completed.
Another option is to just persist all messages directly into the database and have something else figure out what belongs to what. This is a scenario useful for a data warehouse where the data just needs to be collected, no matter what. Some data might not be 100% accurate (or consistent) but that's okay.
Asynchronous messaging makes it hard to process them 100% in order, especially when the client calling the WCF is making mistakes and/or sending them out of order. It wouldn't be the first time I had such a requirement and out-of-order messages.
Related
I have a Java application which publishes events to RabbitMQ. It has one very important characteristic: message order must be preserved at all times. The consumer can handle duplicates, but it cannot handle when message 2 is enqueued before message 1, so to say.
I have been reading a lot about RabbitMQ lately, and I feel there is only solution to do this: set the channel in confirm mode (https://www.rabbitmq.com/confirms.html - basically, it forces the broker to acknowledge the publication) and publish one by one. With one by one I mean that the message 2 is only published after RabbitMQ confirmed (via an asynchronous ACK response) that message 1 is actually well received and persisted.
I tried this in a conceptual implementation, and while this works fine, it's uber slow, without exaggerating. Which makes sense: after all, we are now limiting our message rate to 1 message at a time.
So this leads me to my question: are there other, more performant, ways to ensure that message ordering is always preserved (either in RabbitMQ or via different approaches)?
Although my concern is RabbitMQ, I believe this question might be applied to any kind of asynchronous message queue service.
RabbitMQ's clients enqueue in the same order that you sent. It's when subscribers go down, you get network splits or the subscriber NACKs messages that they can get re-ordered; and even then RMQ tries to keep them in the same approximate order by re-queueing at the same position, or as close to the same position.
You can do it like you suggest; take one message at a time, because if you take a message, but crash before you've ACKed it from the broker, it will pop up when your service comes back up, at the same position.
This assumes you only have a single service instance at any given time, consuming from the queue. Which in turn is a distributed systems problem on its own, if you have a scheduler like Kubernetes or Mesos, spawning your service instances.
Another solution would be to ensure ordering of processing in the receiving service, by "resequencing" the messages based on their logical timestamps/sequence numbers.
I've written a much more thorough guide as annotated code here https://github.com/haf/rmq-publisher-confirms-hopac/blob/master/src/Server/Shared/RabbitMQ.fs — with batching you can resequence. Furthermore, if your idempotence builds the consecutive sequence numbers into its logic, you can start taking batches and each event will be idempotent, despite being re-consumed.
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 have a question about multi consumer concurrency.
I want to send works to rabbitmq that comes from web request to distributed queues.
I just want to be sure about order of works in multiple queues (FIFO).
Because this request comes from different users eech user requests/works must be ordered.
I have found this feature with different names on Azure ServiceBus and ActiveMQ message grouping.
Is there any way to do this in pretty RabbitMQ ?
I want to quaranty that customer's requests must be ordered each other.
Each customer may have multiple requests but those requests for that customer must be processed in order.
I desire to process quickly incoming requests with using multiple consumer on different nodes.
For example different customers 1 to 1000 send requests over 1 millions.
If I put this huge request in only one queue it takes a lot of time to consume. So I want to share this process load between n (5) node. For customer X 's requests must be in same sequence for processing
When working with event-based systems, and especially when using multiple producers and/or consumers, it is important to come to terms with the fact that there usually is no such thing as a guaranteed order of events. And to get a robust system, it is also wise to design the system so the message handlers are idempotent; they should tolerate to get the same message twice (or more).
There are way to many things that may (and actually should be allowed to) interfere with the order;
The producers may deliver the messages in a slightly different pace
One producer might miss an ack (due to a missed package) and will resend the message
One consumer may get and process a message, but the ack is lost on the way back, so the message is delivered twice (to another consumer).
Some other service that your handlers depend on might be down, so that you have to reject the message.
That being said, there is one pattern that servicebus-systems like NServicebus use to enforce the order messages are consumed. There are some requirements:
You will need a centralized storage (like a sql-server or document store) that allows for conditional updates; for instance you want to be able to store the sequence number of the last processed message (or how far you have come in the process), but only if the already stored sequence/progress is the right/expected one. Storing the user-id and the progress even for millions of customers should be a very easy operation for most databases.
You make sure the queue is configured with a dead-letter-queue/exchange for retries, and then set your original queue as a dead-letter-queue for that one again.
You set a TTL (for instance 30 seconds) on the retry/dead-letter-queue. This way the messages that appear on the dead-letter-queue will automatically be pushed back to your original queue after some timeout.
When processing your messages you check your storage/database if you are in the right state to handle the message (i.e. the needed previous steps are already done).
If you are ok to handle it you do and update the storage (conditionally!).
If not - you nack the message, so that it is thrown on the dead-letter queue. Basically you are saying "nah - I can't handle this message, there are probably some other message in the queue that should be handled first".
This way the happy-path is to process a great number of messages in the right order.
But if something happens and a you get a message out of band, you will throw it on the retry-queue (the dead-letter-queue) and Rabbit will make sure it will get back in the queue to be retried at a later stage. But only after a delay.
The beauty of this is that you are able to handle most of the situations that may interfere with processing the message (out of order messages, dependent services being down, your handler being shut down in the middle of handling the message) in exact the same way; by rejecting the message and letting your infrastructure (Rabbit) take care of it being retried after a while.
(Assuming the OP is asking about things like ActiveMQs "message grouping:)
This isn't currently built in to RabbitMQ AFAIK (it wasn't as of 2013 as per this answer) and I'm not aware of it now (though I haven't kept up lately).
However, RabbitMQ's model of exchanges and queues is very flexible - exchanges and queues can be easily created dynamically (this can be done in other messaging systems but, for example, if you read ActiveMQ documentation or Red Hat AMQ documentation you'll find all of the examples in the user guides are using pre-declared queues in configuration files loaded at system startup - except for RPC-like request/response communication).
Also it is very easy in RabbitMQ for a consumer (i.e., message consuming thread) to consume from multiple queues.
So you could build, on top of RabbitMQ, a system where you got your desired grouping semantics.
One way would be to create dynamic queues: The first time a customer order was seen or a new group of customer orders a queue would be created with a unique name for all messages for that group - that queue name would be communicated (via another queue) to a consumer who's sole purpose was to load-balance among other consumers that were responsible for handling customer order groups. I.e., the load-balancer would pull off of its queue a message saying "new group with queue name XYZ" and it would find in a pool of order group consumer a consumer which could take this load and pass it a message saying "start listening to XYZ".
Another way to do it is with pub/sub and topic routing - each customer order group would get a unique topic - and proceed as above.
RabbitMQ Consistent Hash Exchange Type
We are using RabbitMQ and we have found a plugin. It use Consistent Hashing algorithm to distribute messages in order to consistent keys.
For more information about Consistent Hashing ;
https://en.wikipedia.org/wiki/Consistent_hashing
https://www.youtube.com/watch?v=viaNG1zyx1g
You can find this plugin from rabbitmq web page
plugin : rabbitmq_consistent_hash_exchange
https://www.rabbitmq.com/plugins.html
Setup:
I have a couple of subscribers subscribing to an event produced by a publisher on the same machine via MSMQ. The subscribers use two different endpoint names, and are run in its respective process. (This is NSB 4.6.3)
Scenario:
Now, if I do something "bad" to one of the subscribers (say remove proper permission in MSMQ to receive messages, or delete the queue in MSMQ outright...), and call Bus.Publish(), I will still have one event successfully published to the "good" subscriber (if the good one precedes the bad one on the subscriber list in subscription storage), or none successful (if the bad one precedes the good one).
Conclusion:
The upshot here is that Bus.Publish() does not seem to be transactional, as to making publishing to subscribers all succeed or all fail. Depending on the order of the subscribers on the list, the end result might be different.
Questions:
Is this behavior by design?
What is the thought behind this?
If I want to make this call transactional, what is the recommended way? (One option seems to enclose Bus.Publish() in a TransactionScope in my code...)
Publish is transactional, or at least, it is if there is an ambient transaction. Assuming you have not taken steps to disable transactions, all message handlers have an ambient transaction running when you enter the Handle method. (Inspect Transaction.Current.TransactionInformation to see first-hand.) If you are operating out of an IWantToRunWhenBusStartsAndStops, however, there will be no ambient transaction, so then yes you would need to wrap with your own TransactionScope.
How delivery is handled (specific for the MSMQ transport) is different depending upon whether the destination is a local or remote queue.
Remote Queues
For a remote queue, delivery is not directly handled by the publisher at all. It simply drops the two messages in the "Outbox", so to speak. MSMQ uses store-and-forward to ensure that these messages are eventually delivered to their intended destinations, whether that be on the same machine or a remote machine. In these cases, you may look at your outgoing queues and see that there are messages stuck there that are unable to be delivered because of whatever you have done to their destinations.
The safety afforded by store-and-forward mean that one errant subscriber cannot take down a publisher, and so overall coupling is reduced. This is a good thing! But it also means that monitoring outgoing queues is a very important part of your DevOps story when deploying an NServiceBus system.
Local Queues
For local queues, MSMQ may still technically use a concept of an outoging queue in its own plumbing - I'm not sure and it doesn't really matter. But an additional step that MSMQ is capable of doing (and does) is to check the existence of a local queue before you try to send to it, and will throw an exception if it doesn't exist or something is wrong with it. This would indeed affect the publisher.
So yes, if you publish a message from a non-transactional state like the inside of an IWantToRunWhenBusStartsAndStops, and the downed queue happens to be #2 on the list in subscription storage, you could observe a message arriving at SubscriberA but not at Subscriber B. If it were within a message handler with transactions disabled, you could see the multiple copies arriving at SubscriberA because of the message retry logic!
Upshot
IWantToRunWhenBusStartsAndStops is great for quick demos and proving things out, but try to put as little real logic in them as possible, opting instead for the safety of message handlers where the ambient transaction applies. Also remember than an exception inside there could potentially take down your host process. Certainly don't publish inside of one without wrapping it with your own transaction.
Does NServicebus make sure messages are drawn down from a queue in a particular order like FIFO or LIFO?
Thx
NServiceBus doesn't guarantee that messages will be processed in order (as far as im aware). Even if you ran a single thread, you can't guarantee that message 2 doesn't arrive before message 1.
I did a quick google search and also found:
http://mikaelkoskinen.net/post/NServiceBus-In-order-message-processing.aspx
Which seems to test the scenario, but came to the conclusion:
Conclusion
NServiceBus doesn’t handle messages
in-order. It’s up to the developer to
make sure that the relevant messages
are handler in the right order. The
easiest way to do this is to send
messages as batches from the client.
Also if a message fails for some reason, it will be thrown to the back of the queue, and processed out of order from the previous related messages.