I'm running several batch updates (with about 200 entities each one) and I have a Quantum Leap subscribed to the CB to capture the historical data. It is supposed that each batch update should generate 200 different notifications, but, if I have set a throttle of "1", does this mean I will only receive the first notification and loose the other 199? Is this right? (just watching the QL, it seems to me that I'm loosing many notifications)
Entities are processed one by one during a batch update request. Thus, if you have 200 entities the update in each one triggers a subscription, then you will have 200 notifications being sent.
The throttling effect depends on the case. For instance:
If each entity triggers a different subscription, then they have any effect (as the trottling is evaluated by subscription)
If each entity triggers the same subscription and assuming that all the 200 notifications are send very fast (let's say, less than 1 second) then only the first one will be sent, and the 199 remaining ones will be lost.
In general, we don't recommend to use throttling due to this (and some other :) problems. It uses to be better to implement traffic flow control in the receiver.
Related
Short description about the setup:
I'm trying to implement a "basic" event store/ event-sourcing application using a RDBMS (in my case Postgres). The events are general purpose events with only some basic fields like eventtime, location, action, formatted as XML. Due to this general structure, there is now way of partitioning them in a useful way. The events are captured via a Java Application, that validate the events and then store them in an events table. Each event will get an uuid and recordtime when it is captured.
In addition, there can be subscriptions to external applications, which should get all events matching a custom criteria. When a new matching event is captured, the event should be PUSHED to the subscriber. To ensure, that the subscriber does not miss any event, I'm currently forcing the capture process to be single threaded. When a new event comes in, a lock is set, the event gets a recordtime assigned to the current time and the event is finally inserted into the DB table (explicitly waiting for the commit). Then the lock is released. For a subscription which runs scheduled for example every 5 seconds, I track the recordtime of the last sent event, and execute a query for new events like where recordtime > subscription_recordtime. When the matching events are successfully pushed to the subscriber, the subscription_recordtime is set to the events max recordtime.
Everything is actually working but as you can imagine, a single threaded capture process, does not scale very well. Thus the main question is: How can I optimise this and allow for example multiple capture processes running in parallel?
I already thought about setting the recordtime in the DB itself on insert, but since the order of commits cannot be guaranteed (JVM pauses), I think I might loose events when two capture transactions are running nearly at the same time. When I understand the DB generated timestamp currectly, it will be set before the actual commit. Thus a transaction with a recordtime t2 can already be visible to the subscription query, although another transaction with a recordtime t1 (t1 < t2), is still ongoing and so has not been committed. The recordtime for the subscription will be set to t2 and so the event from transaction 1 will be lost...
Is there a way to guarantee the order on a DB level, so that events are visible in the order they are captured/ committed? Every newly visible event must have a later timestamp then the event before (strictly monotonically increasing). I know about a full table lock, but I think, then I will have the same performance penalties as before.
Is it possible to set the DB to use a single threaded writer? Then each capture process would also be waiting for another write TX to finished, but on a DB level, which would be much better than a single instance/threaded capture application. Or can I use a different field/id for tracking the current state? Normal sequence ids will suffer from the same reasons.
Is there a way to guarantee the order on a DB level, so that events are visible in the order they are captured/ committed?
You should not be concerned with global ordering of events. Your events should contain a Version property. When writing events, you should always be inserting monotonically increasing Version numbers for a given Aggregate/Stream ID. That really is the only ordering that should matter when you are inserting. For Customer ABC, with events 1, 2, 3, and 4, you should only write event 5.
A database transaction can ensure the correct order within a stream using the rules above.
For a subscription which runs scheduled for example every 5 seconds, I track the recordtime of the last sent event, and execute a query for new events like where recordtime > subscription_recordtime.
Reading events is a slightly different story. Firstly, you will likely have a serial column to uniquely identify events. That will give you ordering and allow you to determine if you have read all events. When you read events from the store, if you detect a gap in the sequence. This will happen if an insert was in flight when you read the latest events. In this case, simply re-read the data and see if the gap is gone. This requires your subscription to maintain it's position in the index. Alternatively or additionally, you can read events that are at least N milliseconds old where N is a threshold high enough to compensate for delays in transactions (e.g 500 or 1000).
Also, bear in mind that there are open source RDBMS event stores that you can either use or leverage in your process.
Marten: http://jasperfx.github.io/marten/documentation/events/
SqlStreamStore: https://github.com/SQLStreamStore/SQLStreamStore
We have are developing an application that will receive events from various systems via a message queue (Azure) but it is just possible that some events (messages) will not arrive in the order they were sent. These events will be received and processed by a central CQRS/ES based system but my worry is that if the events are placed in the event store in the wrong order we will get garbage out (for example "order create" after "add order item").
Are typical ES systems meant to resolve this issue or are we meant to ensure that such messages are put in the right order before being pushed into the event store? If you have links to articles that back up either view it would help.
Edit: I think my description is clearly far too vague so the responses, while helpful in understanding CQRS/ES, do not quite answer my problem so I'll add a little more detail and hopefully someone will recognise the problem.
Firstly the players.
the front end web site (not actually relevant to this problem) delivers orders to the management system.
our management system which takes orders from the web site and passes them to the warehouse and is hosted on site.
the warehouse which accepts orders, fulfils them if possible and notifies us when an order is fulfilled or cannot be partially or completely fulfilled.
Linking the warehouse to the management system is a fairly thin Azure cloud based coupling. Messages from the warehouse are sent to a WCF/Soap layer in the cloud, parsed, and sent over the messages bus. Message to the warehouse are sent over the message bus and then, again in the cloud, converted into Soap calls to a server at the warehouse.
The warehouse is very careful to ensure that messages it sends have identifiers that increment without a gap so we can know when a message is missed. However when we take those messages and forward them to the management system they are transported over the message bus and could, in theory, arrive in the wrong order.
Now given that we have a sequence number in the messages we could ensure the messages are put back in the right order before they are sent to the CQRS/ES system but my questions is, is that necessary, can the ES actually be used to reorder the events into the logical order they were intended?
Each message that arrives in Service Bus is tagged with a SequenceNumber. The SequenceNumber is a monotonically increasing, gapless 64-bit integer sequence, scoped to the Queue (or Topic) that provides an absolute order criterion by arrival in the Queue. That order may different from the delivery order due to errors/aborts and exists so you can reconstitute order of arrival.
Two features in Service Bus specific to management of order inside a Queue are:
Sessions. A sessionful queue puts locks on all messages with the same SessionId property, meaning that FIFO is guaranteed for that sequence, since no messages later in the sequence are delivered until the "current" message is either processed or abandoned.
Deferral. The Defer method puts a message aside if the message cannot be processed at this time. The message can later be retrieved by its SequenceNumber, which pulls from the hidden deferral queue. If you need a place to keep track of which messages have been deferred for a session, you can put a data structure holding that information right into the message session, if you use a sessionful queue. You can then pick up that state again elsewhere on an accepted session if you, for instance, fail over processing onto a different machine.
These features have been built specifically for document workflows in Office 365 where order obviously matters quite a bit.
I would have commented on KarlM's answer but stackoverflow won't allow it, so here goes...
It sounds like you want the transport mechanism to provide transactional locking on your aggregate. To me this sounds inherently wrong.
It sounds as though the design being proposed is flawed. Having had this exact problem in the past, I would look at your constraints. Either you want to provide transactional guarantees to the website, or you want to provide them to the warehouse. You can't do both, one always wins.
To be fully distributed: If you want to provide them to the website, then the warehouse must ask if it can begin to fulfil the order. If you want to provide them to the warehouse, then the website must ask if it can cancel the order.
Hope that is useful.
For events generated from a single command handler/aggregate in an "optimistic locking" scenario, I would assume you would include the aggregate version in the event, and thus those events are implicitly ordered.
Events from multiple aggregates should not care about order, because of the transactional guarantees of an aggregate.
Check out http://cqrs.nu/Faq/aggregates , http://cqrs.nu/Faq/command-handlers and related FAQs
For an intro to ES and optimistic locking, look at http://www.jayway.com/2013/03/08/aggregates-event-sourcing-distilled/
You say:
"These events will be received and processed by a central CQRS/ES based system but my worry is that if the events are placed in the event store in the wrong order we will get garbage out (for example "order create" after "add order item")."
There seems to be a misunderstanding about what CQRS pattern with Event Sourcing is.
Simply put Event Sourcing means that you change Aggregates (as per DDD terminology) via internally generated events, the Aggregate persistence is represented by events and the Aggregate can be restored by replaying events. This means that the scope is quite small, the Aggregate itself.
Now, CQRS with Event Sourcing means that these events from the Aggregates are published and used to create Read projections, or other domain models that have different purposes.
So I don't really get your question given the explanations above.
Related to Ordering:
there is already an answer mentioning optimistic locking, so events generated inside a single Aggregate must be ordered and optimistic locking is a solution
Read projections processing events in order. A solution I used in the past was to to publish events on RabbitMQ and process them with Storm.
RabbitMQ has some guarantees about ordering and Storm has some processing affinity features. For Storm, (as far as I remember) allows you to specify that for a given ID (for example an Aggregate ID) the same handler would be used, hence the events are processed in the same order as received from RabbitMQ.
The article on MSDN https://msdn.microsoft.com/en-us/library/jj591559.aspx states "Stored events should be immutable and are always read in the order in which they were saved" under "Performance, Scalability, and consistency". This clearly means that appending events out of order is not tolerated. The same article also states multiple times that while events cannot be altered, corrective events can be made. This would imply again that events are processed in the order they are received to determine the current truth (state of of the aggregate). My conclusion is that we should fixed the messaging order problem before posting events to the event store.
Goal:
I use Bloomberg Java API's subscription service to monitor bond prices in real time (subscribing to ASK/BID real time fields). However in the RESPONSE messages, bloomberg does not provide the associated yield for the given price. I need a way to calculate the yields.
Attempt:
Here's what I've tried:
Within in the code that processes Events coming backing from a real time subscription, when I get a BID or ASK response, I extract the price from the message element, and then initiates a new synchronous reference data request, using overrides to get the YAS_BOND_YLD by providing YAS_BOND_PX and setting the overriding flag.
Problem:
This seems very slow and cumbersome. Is there a better way other than having to calculate yields myself?
In my code, I seem to be able to process real time prices if they are being sent to me slowly. If a few bonds' prices were updated at the same time (say, in MSG1 pricing), I seem to only capture one out of these updates, it feels like I'm missing the other events.. Is this because I cannot use a synchronous reference data request while the subscription is still alive?
Thanks.
bloomberg does not provide the associated yield for the given price
Have you tried retrieving the ASK_YIELD and BID_YIELD fields? They may be what you are looking for.
Problem: This seems very slow and cumbersome.
Synchronous one-off requests are slower than real time subscription. Unless you need real time data on the yield, you could queue the requests and send them all at once every x seconds for example. The time to get 100 or 1 yield is probably not that different, and certainly not 100 times slower.
In my code, I seem to be able to process real time prices if they are being sent to me slowly. If a few bonds' prices were updated at the same time (say, in MSG1 pricing), I seem to only capture one out of these updates, it feels like I'm missing the other events.. Is this because I cannot use a synchronous reference data request while the subscription is still alive?
You should not miss items just because you are sending a synchronous request. You may get a "Slow consumer warning" but that's about it. It's difficult to say more without seeing your code. However, if you want to make sure your real time data is not delayed by your synchronous requests, you should use two separate Sessions.
I have just downloaded joliver eventstore and looking to wire up a service bus with Windows Service Bus 1.0 for an application separated across more than one Bounded Context process.
If a bounded context has been offline whilst events in other bounded contexts have been created (or may even be a new context that has been deployed), I can see the following sequence of events.
For an example ContextA, ContextB and ContextC, all connected using Service Bus 1.0 and each context with their own event store, they all share the same bus messaging backplane.
ContextC goes offline.
When ContextC comes back-up, other bounded contexts need to be notified of the events that need to be resent to the context that has just come back online. These events are replayed from each of the event stores.
My questions are:
The above scenario would apply to any event sourcing libraries, so is there any infrastructure code on top of this I can use, or do I have to roll my own?
With Windows Service Bus 1.0, how do I marry sequence numbers in my event store to sequence numbers on the Service Bus?
What is the best practice to detect and handle events that have already been received in a safe manner (protecting against message handlers failing)?
The above scenario would apply to any event sourcing libraries, so is there any infrastructure code on top of this I can use, or do I have to roll my own?
The notion of a Projection mechanism tied to the events is certainly common. Unfortunately, there are many many ways of handling how that might be done, depending on your stack, performance requirements and scale and many other factors.
As a result I'm not aware of a commoditized facility of this nature.
The GetEventStore store has an integrated Projection facility which looks extremely powerful and takes the need to build all this off the table. Before its existence, I'd have argued that one shouldnt even consider looking past the the SRPness of the JOES.
You havent said much about your actual stack other than mentioning Azure.
With Windows Service Bus, how do I marry sequence numbers in my event store to sequence numbers on the Service Bus?
You can use stream id + the commit sequence number the MessageId (and use that to ensure duplicates are removed by the bus). You will probably also include properties in the Message metadata.
What is the best practice to detect and handle events that have already been received in a safe manner (protecting against message handlers failing)?
If you're on Azure and considering ServiceBus then the Topics can be used to ensure at least once delivery (and you'll use the sessioning facility). Go watch the two hour deep dive ClemensV Subscribe video plus a few other episodes or you'll spent the same amount of time making mistakes)
To keep broadcast traffic down, if ContextC requests replays from ContextA and ContextB, is there any way for these replay messages to be sent only to ContextC? Or should I not worry about this?
Mu. You started off asking whether this stuff was a good idea but now seem to have baked in an assumption that it's the way to go.
Firstly, this infrastructure is a massive wheel to reinvent. Have you considered simply setting up a topic per BC and having anyone that needs to listen listen?
A key thing here is that you need to bear in mind the fact that just because you can think of cases where BCs need to consume each others events, that this central magic bus that's everywhere will deliver everything everywhere.
EDIT: Answers to your edited versions of questions 2+
With Windows Service Bus 1.0, how do I marry sequence numbers in my event store to sequence numbers on the Service Bus?
Your event store doesnt have a sequence number. It has a commit sequence number per aggregate. You'd typically use a sessioned topic and subscription. Then you need to choose whether you want a global ordering (use a single session id) or per aggregate ordering (use the stream id as the session id).
Once events are on a topic, they have a MessageSequenceNumber and the subscription (when sessioned) delivers (actually the subscriber recieves them) them in sequence.
What is the best practice to detect and handle events that have already been received in a safe manner (protecting against message handlers failing)?
This is built into the Service Bus (or any queueing mechanism). You don't mark the Message completed until it has been successfully processed. Any failure leads to Abandonment (which puts it back on the queue for reprocessing).
The subscriber taking a break, becoming disconnected or work backing up is naturally dealt with by the Topic.
Let's say I have deployed an NSB endpoint that subscribes to events A,B, and C.
6 months later, version 1.1 of the endpoint adds a handler for event D, but the handler for event B is removed. What is a sensible process for removing the persisted subscription record for event B? I presume there is no automagic way for this to happen, and my choices would be:
Delete the entire contents of the subscription table and restart all endpoints.
Delete selectively based on what I know about the delta
Have some shutdown mode where my subscriber would call Unsubscribe on all its message types on the way down (and therefore would start with a clean slate on the way up)
Has anyone implemented any of these strategies, or am I missing some alternative?
The best solution would probably be option 1. The operational overhead involved in this would be fairly small:
Shut down publisher host
Clear down subscriptions db
Bounce all subscribers
Start up publisher host
Option 3 would also be possible but would involve making an unsubscribe call from every subscriber which is IMO much higher overhead (plus would require a redeployment if unscubscribe call not already implemented and then a shutdown to trigger the call).
Option 2 seems a bit hacky but would be lowest cost as you can just run a sql statement against the publisher db and bob's your mother's brother.
I would recommend option 1.