Udi Dahan   Udi Dahan – The Software Simplist
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Life without distributed transactions

Monday, December 31st, 2012.

transactionsOccasionally I get questions about the issue of transactional messaging – why is it so important, why does NServiceBus default to this behavior, and if we didn’t use it, what bad things could happen. I’m talking specifically about the ability to enlist a queue in a distributed transaction here.

I think the reason for this interest is the rise in popularity of cloud platforms and queuing systems like RabbitMQ (which don’t support distributed transactions) and the difficulty of setting up distributed transactions even in on-premise.

Of course, there’s also the regular scalability hand-wringing going on even though most people wouldn’t bump up against those limits anyway.

In this post, I’ll talk about the nature of the problem, explain the pitfalls in some of the common solutions, but I’ll put off the description of how to provide consistency without distributed transactions to a future post as this one is already going to be quite long.

I’ll start with the basic fault-tolerance issues and then explain how things spiral out from there.

Starting with the basics

OK, so we have a queuing system in place that dispatches messages to our business logic which does some transactional work against a database.

Let’s say that we completed the transaction against our database but before we could acknowledge to the queue that the message was processed successfully, our machine crashed. What our machine comes up again, the queue will once again dispatch us the same message. Unless we have some logic to detect that we’ve already processed it (called “idempotence” in the REST community), we will end up processing it again.

In short, the problem is duplicates.

Attempted solutions to the duplicate problem

Most queuing systems don’t do anything about duplicates, actually giving it a proper architectural name: At-least-once message delivery, as opposed to the Once-and-only-once model that a queue that supports distributed transaction provides.

The solution often suggested is to have your logic check to see if it has already processed a message with that ID before – in essence storing the ID of each message processed for some period of time. Of course, there is some performance overhead with that, but it might be a small price to pay compared to dealing with it in the logic of every use case.

On the other hand, you’ll often have some messages (like Update commands) for which it looks like you can safely process them multiple times, in which case you might want not to pay the performance overhead there. The thing is, if your logic publishes an event in addition to the regular database work (something that is quite common) and you process the same message twice, you will probably end up publishing the event twice as well.

These duplicates are different in that here we have two distinct messages with different IDs that contain the same business data. This means that recipients of these messages will not be able to filter them out at an infrastructure level anymore.

NOTE: Deduplication abilities in queues

Although the Azure Service Bus doesn’t support distributed transactions meaning you still have the issue mentioned above, Microsoft added the ability to detect and filter out duplicates based on message contents rather than just the ID. This helps quite a bit but it’s important to understand that that doesn’t cover everything for you. Let me explain:

More complex logic

In some of your most important use cases, you may have both entity updates as well as entity creation happening together in your domain model. You might be using some kind of event model (like I wrote about here) to percolate out the information that an entity was created in order to keep your service layer decoupled from the internals of the domain model.

In the callback code from these domain events, you will likely publish out an event on the queuing system containing information like the ID of the entities created as well as other business data. And there’s the rub.

You see, without distributed transactions, you can run into some problematic scenarios:

For example, if you don’t make sure that your event publishing calls to the queuing system include the same transaction object as the one you used when retrieving the original message from the queue, then those calls could “escape” before you know if the database transaction is going to succeed. Deadlocks always happen at the lousiest times. Anyway, if you’re using database generated IDs for your entities, then those IDs will get published out in events despite the database rolling back and your subscribers will now be making decisions on wrong data – not just eventually consistent data.

In this case, processing the message again doesn’t really solve the problem – it just means that you’ll be publishing events with different IDs, so an infrastructure like Azure Service Bus couldn’t really de-duplicate them.

On the other hand, if you do use the same transaction and combine in the infrastructural message ID based de-duplication described above (as identifying duplicate calls for complex business logic is damn hard), you’ll run into another problem.

Consider what would happen if your server crashes right after finishing its database work but before it completes the transaction against the queuing system. When going to retry the message, the infrastructure filtering thing would know not to call your business logic again and that message would be quietly swallowed. Unfortunately, the event publishing calls to the queuing system from the first time the message was processed were rolled back and since your business logic isn’t called again, the event publishing won’t happen again.

Oops.

In closing

I hope I’ve been able to clarify what kind of scenarios distributed transactions solve for you and some of the difficulties in solving them yourself.

Now, to be clear, you could solve these problems by going in-depth on each of your use cases, analyzing the consistency needs and structuring the code differently to address those needs. But give this another thought, if our consistency is dependent on calling otherwise independent APIs in exactly the right order, and that a change in this order would not cause any visible functional effects, what would happen when developers with less expertise maintain this code?

The folks in the event sourcing community have their solution to this which is based on writing their business logic differently. As the adoption of this pattern is still pretty limited (probably still in the Innovator section of the Technology Adoption Curve), it’ll be interesting to see how it holds up with larger teams in the mainstream.

Oh, and in case it wasn’t clear from before, the guys in the REST community haven’t even begun addressing this problem when it comes to server-to-server integration.

We’re working on a solution for this with NServiceBus that won’t require you to change how you write business logic. We’ve got one big release to do before we can roll this in, and that’s coming soon (with all sorts of cool things like support for ActiveMQ and queues in the database). The solution we’ve found is architecturally sound but you’ll have to wait for my next post to hear about it.

Stay tuned.

  
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10 Comments

  1. Sean Kearon Says:

    “Queues in the database” – oh yes!! :) That means one less moving part for me to have to worry about – which is great news!

    Presuming here that you’re going to be supporting (at least) RavenDB here, I’m hoping that I’ll be able to use RavenHQ. Which would mean I could then easily have all my bus data stored on a hosted and backed up server for minimal effort.

    Can’t wait for the next post to hear more…

    Happy New Year to you too!


  2. Michael L Perry Says:

    Durability is a key concern of any distributed system. And like it or not, most systems these days are distributed. It should be front-of-mind.

    I like to consider these promises related to durability:
    1. If I acknowledge the message, it was stored.
    2. If you resend the message, it will not be duplicated.
    3. If I removed the message from the queue, it was processed.

    There are several strategies I’ve used in the past to guarantee these promises. My favorites are:
    1. Client generated IDs.
    2. Capturing the message ID in the side-effect.
    3. Transactions.

    Transactions alone are not enough. You have to cover all aspects of durability.


  3. Phil Sandler Says:

    Great post. We are doing our first major project with NSB and were asking some of these exact questions (actually one on the NSB list).

    “Anyway, if you’re using database generated IDs for your entities, then those IDs will get published out in events despite the database rolling back and your subscribers will now be making decisions on wrong data – not just eventually consistent data.”

    This was indeed one of the major questions we ran up against. In our case, we are using (non-NSB) Domain Events for inter-system messaging in addition to NSB Events for intra-system communication. We were actually seeing data on the screen that had not yet been committed to the database yet, and in some cases would get rolled back.

    Since our Domain Event dispatcher can’t participate in a DTC transaction (or any transaction for that matter), so we implemented post-commit logic for publishing events: we add post-commit Action delegates to our UOW implementation, then execute them only if the commit succeeds.

    It’s a bit of housekeeping to ensure that no one writes code that publishes directly from a domain object instead of adding it to the action collection, plus we always need access to the UOW instance in order to add the post-commit Actions, but it seems to work well.


  4. Stacy Says:

    I think Sql Service Broker may be the solution here. You have durability, queues, transactions all in the same place. Queues guarantee to receive exactly once.


  5. Yogi Says:

    Stacy – NSB is based on the bus architectural style as oppose to Sql Service Broker (i.e. Broker architectural style), the Bus style has a number of advantages over a broker for distributed systems.


  6. Joseph Daigle Says:

    I can think of one implementation which involves a lot of journaling. Assuming you have one “business” database (the primary database that transactions occur against): in the same database transaction as your “business logic” write the messages which were sent/published including the serialized data referenced by a message ID. In the message queue you need a way to journal which messages were sent by message ID. Now in the case of a failure at any point you have enough information to recover. For example, if the business transaction commits but you fail to send the messages to the queue, the retry will read the committed events and try to send them again.

    Of course this is tricky with MSMQ. I can see where table-based queues can be beneficial. I’d like to point out SQL Service Broker as another alternative. The implementation I described coupled with Service Broker is what we use as an alternative to DTC. It works very well. *Note* that we do NOT use Service Broker in the same database our business logic works against as it’ll wreck havoc with your Transaction Log file.


  7. udidahan Says:

    Stacy, as Yogi said, the Bus architectural style has several advantages over the Broker architectural style. See some of my previous posts for more info:

    http://www.udidahan.com/2011/03/24/bus-and-broker-pubsub-differences/

    http://www.udidahan.com/2011/03/20/careful-with-content-based-routing/


  8. udidahan Says:

    Joseph,

    You’re on track with your solution, but there are some other little details that need to be handled.


  9. Evgeniy Shapiro Says:

    Udi,

    I believe the correct answer is suggested by the paper: Life beyond Distributed Transactions:
    an Apostate’s Opinion.

    The entity within a service should maintain activities that manage the interaction with other services. Of course this should be solved by the infrastructure layer, since we don’t want solution developers to be involved in this kind of logic.

    One way this can be implemented is:
    1. A message is received (peeked) from the queue.
    2. Id based deduplication happens to ensure we didn’t process the message.
    3. The attributes of the entity have changed and the intents to send messages or publish events are captured (but not sent).
    4. The id of the message that triggered the state change and all the intents on sending/publish are written to the database as part of a transaction. For relational databases these can reside in a different table, however you should still think of them as part of the reacting entity, since they are processed at the same time.
    5. The message is removed from the queue.
    6. Once the transaction is confirmed the intents are loaded and acted upon (messages sent/events published) and the intents are deleted from the database.

    If the process fails in steps 1-4 the message is still in the queue and can be processed on the next loop iteration.
    If the process fails on step 5, the deduplication logic on step 2 should prevent the message from being processed again.
    Failing on step 6 can be handled on application start and a timer (assuming proper isolation level).

    Note that step 6 can start on another thread (one that doesn’t process the input queue messages) assuming the messages are targeting different entities and the number of entities is considerable (otherwise database contention can be high).

    The deduplication performance can be increased if the ID of the processed message is written to an in-memory database (e.g. Redis or Memcache) after the original transaction is processed.

    Overall the performance of this solution will not be any better than the DTC. In general case, however, queues do not support distributed transactions (think of Amazon and Azure queues) so DTC may not be your answer anyway. If you already use MSMQ and SQL Server (or other database with DTC support) I don’t see a reason to avoid DTC.

    Side note: logically all send/publish intents and the list of processed messages belong to the targeted entity, even if it’s a superfluous one that represents the service itself.

    Thanks for the great article.


  10. udidahan Says:

    Hi Evgeniy,

    You are very close but there are still some issues with your solution. In any case, performance-wise, we are seeing things run 2-3X as fast as with DTC.


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Rhys Campbell Rhys Campbell, Owner at Artemis West
“For many years I have been following the works of Udi. His explanation of often complex design and architectural concepts are so cleanly broken down that even the most junior of architects can begin to understand these concepts. These concepts however tend to typify the "real world" problems we face daily so even the most experienced software expert will find himself in an "Aha!" moment when following Udi teachings.
It was a pleasure to finally meet Udi in Seattle Alt.Net OpenSpaces 2008, where I was pleasantly surprised at how down-to-earth and approachable he was. His depth and breadth of software knowledge also became apparent when discussion with his peers quickly dove deep in to the problems we current face. If given the opportunity to work with or recommend Udi I would quickly take that chance. When I think .Net Architecture, I think Udi.”

Sverre Hundeide Sverre Hundeide, Senior Consultant at Objectware
“Udi had been hired to present the third LEAP master class in Oslo. He is an well known international expert on enterprise software architecture and design, and is the author of the open source messaging framework nServiceBus. The entire class was based on discussion and interaction with the audience, and the only Power Point slide used was the one showing the agenda.
He started out with sketching a naive traditional n-tier application (big ball of mud), and based on suggestions from the audience we explored different solutions which might improve the solution. Whatever suggestions we threw at him, he always had a thoroughly considered answer describing pros and cons with the suggested solution. He obviously has a lot of experience with real world enterprise SOA applications.”

Raphaël Wouters Raphaël Wouters, Owner/Managing Partner at Medinternals
“I attended Udi's excellent course 'Advanced Distributed System Design with SOA and DDD' at Skillsmatter. Few people can truly claim such a high skill and expertise level, present it using a pragmatic, concrete no-nonsense approach and still stay reachable.”

Nimrod Peleg Nimrod Peleg, Lab Engineer at Technion IIT
“One of the best programmers and software engineer I've ever met, creative, knows how to design and implemet, very collaborative and finally - the applications he designed implemeted work for many years without any problems!

Jose Manuel Beas
“When I attended Udi's SOA Workshop, then it suddenly changed my view of what Service Oriented Architectures were all about. Udi explained complex concepts very clearly and created a very productive discussion environment where all the attendees could learn a lot. I strongly recommend hiring Udi.”

Daniel Jin Daniel Jin, Senior Lead Developer at PJM Interconnection
“Udi is one of the top SOA guru in the .NET space. He is always eager to help others by sharing his knowledge and experiences. His blog articles often offer deep insights and is a invaluable resource. I highly recommend him.”

Pasi Taive Pasi Taive, Chief Architect at Tieto
“I attended both of Udi's "UI Composition Key to SOA Success" and "DDD in Enterprise Apps" sessions and they were exceptionally good. I will definitely participate in his sessions again. Udi is a great presenter and has the ability to explain complex issues in a manner that everyone understands.”

Eran Sagi, Software Architect at HP
“So far, I heard about Service Oriented architecture all over. Everyone mentions it – the big buzz word. But, when I actually asked someone for what does it really mean, no one managed to give me a complete satisfied answer. Finally in his excellent course “Advanced Distributed Systems”, I got the answers I was looking for. Udi went over the different motivations (principles) of Services Oriented, explained them well one by one, and showed how each one could be technically addressed using NService bus. In his course, Udi also explain the way of thinking when coming to design a Service Oriented system. What are the questions you need to ask yourself in order to shape your system, place the logic in the right places for best Service Oriented system.

I would recommend this course for any architect or developer who deals with distributed system, but not only. In my work we do not have a real distributed system, but one PC which host both the UI application and the different services inside, all communicating via WCF. I found that many of the architecture principles and motivations of SOA apply for our system as well. Enough that you have SW partitioned into components and most of the principles becomes relevant to you as well. Bottom line – an excellent course recommended to any SW Architect, or any developer dealing with distributed system.”

Consult with Udi

Guest Authored Books
Chapter: Introduction to SOA    Article: The Enterprise Service Bus and Your SOA

97 Things Every Software Architect Should Know



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