queryClient.fetchQuery can be used in place of useQuery hook provided by react-query. Any guidelines, best practices on in which scenario, one should be preferred over other.
One scenario might be where we want to conditionally fetch data. So, queryClient.fetchQuery looks more natural while useQuery hook not.
Is the above logic correct? Please advise on the best practise of using one over the other
fetchQuery is an imperative way to fetch data. You cannot call this during rendering, because it would be a side-effect and you cannot await the result. So you would need to spawn a useEffect.
The other difference is that useQuery creates a subscription to the queryKey, but fetchQuery does not. So if the data updates for some other reason (like a second component mounts and triggers a re-refetch of the query, or you refetch in the background because you focus the window and the query is stale), your component will not re-render and show the new data.
One scenario might be where we want to conditionally fetch data.
This is where you want the enabled option of useQuery, so that you can disable your query for as long as the conditions are not met.
The bottom line is: The two are not interchangeable, I have almost never used fetchQuery. For components, always useQuery
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I have a CQRS/ES application where some of the views are populated by events from multiple aggregate roots.
I have a CashRegisterActivated event on the CashRegister aggregate root and a SaleCompleted event on the Sale aggregate root. Both events are used to populate the CashRegisterView. The CashRegisterActivated event creates the CashRegisterView or sets it active in case it already exists. The SaleCompleted event sets the last sale sequence number and updates the cash in the drawer.
When two of these events arrive within milliseconds, the first update is overwritten by the last one. So that's a lost update.
I already have a few possible solutions in mind, but they all have their drawbacks:
Marshal all event processing for a view or for one record of a view on the same thread. This works fine on a single node, but once you scale out, things start to get complex. You need to ensure all events for a view are delivered to the same node. And you need to migrate to another node when it goes down. This requires some smart load balancer which is aware of the events and the views.
Lock the record before updating to make sure no other threads or nodes modify it in the meantime. This will probably work fine, but it means giving up on a lock-free system. Threads will set there, waiting for a lock to be freed. Locking also means increased latency when I scale out the data store (if I'm not mistaken).
For the record: I'm using Java with Apache Camel, RabbitMQ to deliver the events and MariaDB for the view data store.
I have a CQRS/ES application where some of the views in the read model are populated by events from multiple aggregate roots.
That may be a mistake.
Driving a process off of an isolated event. But composing a view normally requires a history, rather than a single event.
A more likely implementation would be to use the arrival of the events to mark the current view stale, and to use a single writer to update the view from the history of events produced by the aggregate(s) concerned.
And that requires a smart messaging solution. I thought "Smart endpoints and dumb pipes" would be a good practice for CQRS/ES systems.
It is. The endpoints just need to be smart enough to understand when they need histories, or when events are sufficient.
A view, after all, is just a snapshot. You take inputs (X.history, Y.history), produce a snapshot, write the snapshot into your view store (possibly with meta data describing the positions in the histories that were used), and you are done.
The events are just used to indicate to the writer that a previous snapshot is stale. You don't use the event to extend the history, you use the event to tell the writer that a history has changed.
You don't lose updates with multiple events, because the event itself, with all of its state, is captured in the history. It's the history that is used to build the event-sourced view.
Konrad Garus wrote
... handling events coming from a single source is easier, but more importantly because a DB-backed event store trivially guarantees ordering and has no issues with lost or duplicate messages.
A solution could be to detect the when this situation happens, and do a retry.
To do this:
Add to each table the aggregate version number which is kept up to date
On each update statement add the following the the where clause "aggr_version=n-1" (where n is the version of the event being processed)
When the result of the update statement is that no records where modified, it probably means that the event was processed out of order and a retry strategy can be performed
The problem is that this adds complexity and is hard to test. The performance bottleneck is very likely in the database, so a single process with a failover solution will probably be the easiest solution.
Although I see you ask how to handle these things at scale - I've seen people recommend using a single threaded approach - until such times as it actually becomes a problem - and then address it.
I would have a process manager per view model, draw the events you need from the store and write them single threaded.
I combined the answers of VoiceOfUnreason and StefRave into something I think might work. Populating a view from multiple aggregate roots feels wrong indeed. We have out of order detection with a retry queue. So an event on an aggregate root will only be processed when the last completely processed event is version n-1.
So when I create new aggregate roots for the views that would be populated by multiple aggregate roots (say aggregate views), all updates for the view will be synchronised without row locking or thread synchronisation. We have conflict detection with a retry mechanism on the aggregate roots as well, that will take care of concurrency on the command side. So if I just construct these aggregate roots from the events I'm currently using to populate the aggregate views, I will have solved the lost update problem.
Thoughts on this solution?
Consider a function: IsWalletValid(walletID). It returns true if the walletID exists in the database, and updates a 'last_accessed_time' field.
A task runs periodically to remove any wallets that have not been accessed for a set period of time.
Seems like an easy solution for what we want to do, but IsWalletValid() has a side effect because it writes to the database.
Should we add an additional 'UpdateLastAccessedTime(walletID)' function? Everytime we call IsWalletValid() we will also need to remember to call UpdateLastAccessedTime(walletID).
Do verifying that a wallet is valid and updating it's last_accessed_time field need to be transactionally consistent (ACID)? You could use eventual consistency here:
The method IsWalletValid publishes an WalletAccessed event, then an event handler updates last_accessed_time asynchronously.
if last_accessed_time is not accessed by domain logic to make decisions on any write handling this could just be a facet of the read only projection. Seems like this is the same concern as other more verbose read audit concerns. Just because data is being written and maintained doesn't mean that it necessarily needs to be part of the write model of the system. If you did however want to implement this as part of the domain and perhaps stored within the same event store it could be considered a separate auditing context outside of the boundary of the original aggregate being audited.
I'm trying to learn EventStore, I like the concept but when I try to apply in practice I'm getting stuck in same point.
Let's see the code:
foreach (var k in stream.CommittedEvents)
{
//handling events
}
Two question about that:
When an app start ups after some maintenance, how do we bookmark in a
safe way what events start to read? Is there a pattern to use?
as soon the events are all consumed, the cycle ends... what about the message arriving run time? I would expect the call blocking until some new message arrive ( of course need to be handled in a thread ) or having something like BeginRead EndRead.
Do I have to bind an ESB to handle run time event or does the EventSore provides some facility to do this?
I try to better explain with an example
Suppose the aggregate is a financial portfolio, and the application is an application showing that portfolio to a trader. Suppose the trader connect to the web app and he looks at his own portfolio. The current state will be the whole history, so I have to read potentially a lot of records to reproduce the status. I guess this could be done by a so called snapshot, but who's responsible for creating it? When one should choose to create an aggregate? How can one guess a snapshot for an aggregate exists ?
For the runtime part: as soon the user look at the reconstructed portfolio state, the real time part begin to run. The user can place an order and a new position can be created by succesfully execute that order in the market. How is the portfolio updated by the infrastructure? I would expect, but maybe I'm completely wrong, having the same event stream being the source of that new event new long position, otherwise I have two path handling the state of the same aggregate. I would like to know if this is how the strategy is supposed to work, even if I feel a little tricky having the two state agents, that can possibly overlap.
Just to clarify how I fear the overlapping:
I know events has to be idempotent, so I know it must not be a
problem anyway,
But let's consider the following:
I subscribe an event bus before streaming the event to update the state of the portfolio. some "open position event" appears on the bus: I must handle them, but maybe the portfolio is not in the correct state to handle it since is not yet actualized. Even if I'm able to handle such events I will find them again when I read the stream.
More insidious: I open the stream and I read all events and I create a state. Then I subscribe to the bus: some message on the bus happen in the middle between the end of the steram reading and the beggining of the subscription: those events are missing and the aggregate is not in the correct state.
Please be patient all, my English is poor and the argument is tricky, hope I managed to share my doubt :)
The current state will be the whole history, so I have to read
potentially a lot of records to reproduce the status. I guess this
could be done by a so called snapshot, but who's responsible for
creating it?
In CQRS and event sourcing, queries are served by projections which are generated from events emitted by aggregates. You don't use the aggregate instance as reconstituted from the event store to display information.
The term snapshot refers specifically to an optimization of the event store which allows rebuilding the aggregate without replaying all of the events.
Projections are essentially event handlers which maintain a denormalized view of aggregates. Events emitted from aggregates are published, possibly out of band, and the projection subscribes to and handles those events. A projection can combine multiple aggregates if a requirement exists to display summary information, for instance. In case of a trading application, each view will typically contain data from various aggregates. Projections are designed in a consumer-driven way - application requirements determine the different views of the underlying data that are needed.
With this type of workflow you have to embrace eventual consistency throughout your application. For instance, if an end user is viewing their portfolio and initiating new trades, the UI has to subscribe to updates to reflect updated projections in an asynchronous manner.
Take a look at here for an overview of CQRS and event sourcing.
Observe
I was trying to figure it out how cursor.observe runs inside meteor, but found nothing about it.
Docs says
Establishes a live query that notifies callbacks on any change to the query result.
I would like to understand better what live query means.
Where will be my observer function executed? By Meteor or by mongo?
Multiple runs
When we have more than just a user subscribing an observer, one instance runs for each client, leading us to a performance and race condition issue.
How can I implement my observe to it be like a singleton? Just one instance running for all.
Edit: There was a third question here, but now it is a separated question: How to avoid race conditions on cursor.observe?
Server side, as of right now, observe works as follows:
Construct the set of documents that match the query.
Regularly poll the database with query and take a diff of the changes, emitting the relevant events to the callbacks.
When matching data is changed/inserted into mongo by meteor itself, emit the relevant events, short circuiting step #2 above.
There are plans (possibly in the next release) to automatically ensure that calls to subscribe that have the same arguments are shared. So basically taking care of the singleton part for you automatically.
Certainly you could achieve something like this yourself, but I believe it's a high priority for the meteor team, so it's probably not worth the effort at this point.
I have an entity in my domain that represent a city electrical network. Actually my model is an entity with a List that contains breakers, transformers, lines.
The network change every time a breaker is opened/closed, user can change connections etc...
In all examples of CQRS the EventStore is queried with Version and aggregateId.
Do you think I have to implement events only for the "network" aggregate or also for every "Connectable" item?
In this case when I have to replay all events to get the "actual" status (based on a date) I can have near 10000-20000 events to process.
An Event modify one property or I need an Event that modify an object (containing all properties of the object)?
Theres always an exception to the rule but I think you need to have an event for every command handled in your domain. You can get around the problem of processing so many events by making use of Snapshots.
http://thinkbeforecoding.com/post/2010/02/25/Event-Sourcing-and-CQRS-Snapshots
I assume you mean currently your "connectable items" are part of the "network" aggregate and you are asking if they should be their own aggregate? That really depends on the nature of your system and problem and is more of a DDD issue than simple a CQRS one. However if the nature of your changes is typically to operate on the items independently of one another then then should probably be aggregate roots themselves. Regardless in order to answer that question we would need to know much more about the system you are modeling.
As for the challenge of replaying thousands of events, you certainly do not have to replay all your events for each command. Sure snapshotting is an option, but even better is caching the aggregate root objects in memory after they are first loaded to ensure that you do not have to source from events with each command (unless the system crashes, in which case you can rely on snapshots for quicker recovery though you may not need them with caching since you only pay the penalty of loading once).
Now if you are distributing this system across multiple hosts or threads there are some other issues to consider but I think that discussion is best left for another question or the forums.
Finally you asked (I think) can an event modify more than one property of the state of an object? Yes if that is what makes sense based on what that event represents. The idea of an event is simply that it represents a state change in the aggregate, however these events should also represent concepts that make sense to the business.
I hope that helps.