I have a program where I start several process instances using a cron. For each process instance I have a maximum time, and if the execution time exceeds it, I have to consider it as failure and use some specific methods.
For now what I did was simply to check, once my process instance has finished, if the elapsed time exceeds or not the given maximum time.
But what if my process instance gets blocked for some reason (e.g. server not responding)? I need to catch this event and perform failure operations as soon as the process gets blocked and timeout is exceeded.
How can I catch these two conditions?
I had a look at the FlowableEngineEventType, but there isn’t a PROCESS_BLOCKED/SUSPENDED type of event. But, even if it were, how do I fire it only if a certain amount of time has passed?
I assume that this is the same question as this from the Flowable Forum.
If you are using the Flowable HTTP Task then have a look at the documentation to see how you can set the timeouts on it and how you can react on errors there. If you are firing GET requests from your own code you would need to write your own business logic that would throw some kind of BpmnError and you would then handle that in your process.
The Flowable Process instance does not have the concept of being blocked, and you have to manually to that in your modelling.
Related
I have a task that can be started by the user, that could take hours to run, and where there's a reasonable chance that the user will start the task multiple times during a run.
I've broken the processing of the task up into smaller batches, but the way the data looks it's very difficult to tell what's still to be processed. I batch it using messages that each process a bite sized chunk of the data.
I have thought of using a Saga to control access to starting this process, with a Saga property called Processing that I set at the start of the handler and then unset at the end of the handler. The handler does some work and sends the messages to process the data. I check the value at the start of the handler, and if it's set, then just return.
I'm using Azure storage for Saga storage, if it makes a difference for the next bit. I'm also using NSB 6
I have a few questions though:
Is this the correct approach to re-entrancy with NSB?
When is a change to Saga data persisted? (and is it different depending on the transport?)
Following on from the above, if I set a Saga value in a handler, wait a while and then reset it to its original value will it change the persistent storage at all?
Seem to be cross posted in the Particular Software google group:
https://groups.google.com/forum/#!topic/particularsoftware/p-qD5merxZQ
Sagas are very often used for such patterns. The saga instance would track progress and guard that the (sub)tasks aren't invoked multiple times but could also take actions if the expected task(s) didn't complete or is/are over time.
The saga instance data is stored after processing the message and not when updating any of the saga data properties. The logic you described would not work.
The correct way would be having a saga that orchestrates your process and having regular handlers that do the actual work.
In the saga handle method that creates the saga check if the saga was already created or already the 'busy' status and if it does not have this status send a message to do some work. This will guard that the task is only initiated once and after that the saga is stored.
The handler can now do the actual task, when it completes it can do a 'Reply' back to the saga
When the saga receives the reply it can now start any other follow up task or raise an event and it can also 'complete'.
Optimistic concurrency control and batched sends
If two message are received that create/update the same saga instance only the first writer wins. The other will fail because of optimistic concurrency control.
However, if these messages are not processed in parallel but sequential both fail unless the saga checks if the saga instance is already initialized.
The following sample demonstrates this: https://github.com/ramonsmits/docs.particular.net/tree/azure-storage-saga-optimistic-concurrency-control/samples/azure/storage-persistence/ASP_1
The client sends two identical message bodies. The saga is launched and only 1 message succeeds due to optimistic concurrency control.
Due to retries eventually the second copy will be processed to but the saga checks the saga data for a field that it knows would normally be initialized by by a message that 'starts' the saga. If that field is already initialized it assumes the message is already processed and just returns:
It also demonstrates batches sends. Messages are not immediately send until the all handlers/sagas are completed.
Saga design
The following video might help you with designing your sagas and understand the various patterns:
Integration Patterns with NServiceBus: https://www.youtube.com/watch?v=BK8JPp8prXc
Keep in mind that Azure Storage isn't transactional and does not provide locking, it is only atomic. Any work you do within a handler or saga can potentially be invoked more than once and if you use non-transactional resources then make sure that logic is idempotent.
So after a lot of testing
I don't believe that this is the right approach.
As Archer says, you can manipulate the saga data properties as much as you like, they are only saved at the end of the handler.
So if the saga receives two simultaneous messages the check for Processing will pass both times and I'll have two processes running (and in my case processing the same data twice).
The saga within a saga faces a similar problem too.
What I believe will work (and has done during my PoC testing) is using a database unique index to help out. I'm using entity framework and azure sql, so database access is not contained within the handler's transaction (this is the important difference between the database and the saga data). The database will also operate across all instances of the endpoint and generally seems like a good solution.
The table that I'm using has each of the columns that make up the saga 'id', and there is a unique index on them.
At the beginning of the handler I retrieve a row from the database. If there is a row, the handler returns (in my case this is okay, in others you could throw an exception to get the handler to run again). The first thing that the handler does (before any work, although I'm not 100% sure that it matters) is to write a row to the table. If the write fails (probably because of the unique constraint being violated) the exception puts the message back on the queue. It doesn't really matter why the database write fails, as NSB will handle it.
Then the handler does the work.
Then remove the row.
Of course there is a chance that something happens during processing of the work, so I'm also using a timestamp and another process to reset it if it's busy for too long. (still need to define 'too long' though :) )
Maybe this can help someone with a similar problem.
I have a requirement where I need to make sure only one message is being processed at a time by a mule flow.Flow is triggered by a quartz scheduler which reads one file from FTP server every time
My proposed solution is to keep a global variable "FLOW_STATUS" which will be set to "RUNNING" when a message is received and would be reset to "STOPPED" once the processing of message is done.
Any messages fed to the flow will check for this variable and abort if "FLOW_STATUS" is "RUNNING".
This setup seems to be working , but I was wondering if there is a better way to do it.
Is there any best practices around this or any inbuilt mule helper functions to achieve the same instead of relying on global variables
It seems like a more simple solution would be to set the maxActiveThreads for the flow to 1. In Mule, each message processed gets it's own thread. So setting the maxActiveThreads to 1 would effectively make your flow singled threaded. Other pending requests will wait in the receiver threads. You will need to make sure your receiver thread pool is large enough to accommodate all of the potential waiting threads. That may mean throttling back your quartz scheduler to allow time process the files so the receiver thread pool doesn't fill up. For more information on the thread pools and how to tune performance, here is a good link: http://www.mulesoft.org/documentation/display/current/Tuning+Performance
I'm fairly new to Gigaspaces. I am using a polling container to fetch events from a space and then dispatch these over a HTTPS connection. If the server endpoint for the connection becomes unavailable, I need to update the state of the event objects to 'blocked' and re-queue them in the space for later retries (for which I have a separate polling container that specifically looks for the blocked events).
What I'm struggling with is finding a good way to ensure the blocked event polling container does not over-rotate on the blocked events (that is, read the events, discover that the endpoint is still blocked, write them back to the space and then immediately re-read them).
Is there a way I could build in a delay in re-reading the events from the space. Options might include:
Setting/updating a timestamp on the object before writing it back, and then comparing this with the current time within the polling process (for this, I expect I would have to use a SQLQuery which includes SYSDATE as the EventTemplate, but would I have to query SYSDATE out of the space every time I want to update the object rather than using System.currentTimeMillias or equivalent, in order to ensure I am comparing apples to apples?)
Applying a configuration setting of some kind on the blocked event polling container or listener that causes it to only poll periodically.
You can use both approach:
docs.gigaspaces.com/xap97/polling-container.html#dynamic-template-definition
docs.gigaspaces.com/sbp/dynamic-polling-container-templates-using-triggeroperationhandler.html
In the future, for GigaSpaces related questions, please use:
ask.gigaspaces.org/questions/
Thanks,
Ester.
I have a saga which represents a long-running work assignment process of a "Person" to a "Case". Several events may kick it off, and at the end of the process we have an assignment confirmation, at which point the saga completes and the Person is assigned to the Case. I would like to have a timeout for this saga so that we don't wait indefinitely for confirmation - definitely a valid business use case. No difficulties there - fairly vanilla.
The twist is that this assignment process can be blocked if someone puts the Case on hold. I have an event I can subscribe to so my assignment saga knows the Case is on hold, but unless I adjust the timeout or suspend it in some way, the assignment saga will likely time out before the Case hold is released. It doesn't make business sense to do this, so I basically want to stop the timeout clock until some other event comes in.
This same issue was mentioned here a couple years ago. Is this still not possible or are there new features in v3.x that would allow it? If not, is it a planned feature?
Thanks!
Why not remove the timeout altogether for the instance when your case is put on hold? Your saga maintains the state of the case and the calculated time when the case would have been due. This could have been set when you created the first timeout. When the case is reactivated, simply calculate the difference in time from the reactivation and the saved "deadline", and create a new timeout for that instance with the difference. You may also want to take into account the time the case was on hold and set a new deadline which you would save back to the instance state.
I don't think there is a way to tab directly to the timer and put the timeout message "on-hold"
I would have that logic inside the timeout handler on the saga. Check if the case is on hold and request another timeout without ending the saga.
I'm making an API and have a function which takes a task and runs it. When the task is finished successfully, it's status is set to 'Completed'. Now, lets say the user of the API accidentally (or for whatever reason) sends that same task (or any other already completed task) back into the same function. What should the API do?
Throw an exception
Pretend as if I've rerun the task and tell the user (through events or whatever) that it is done/completed (again).
Do nothing and just ignore it.
Is there a standard or best practice for something like this?
Pretending to rerun hides what's probably a user error - this can lead to deadlocks or other logic bugs (i.e. - I create an event, wait on it and run a task that should reset it at some point - it never happens, deadlock). Also done handlers may fail if invoked twice per one successful task run.
Doing nothing is more or less the same - done handlers can't fail now :), but they are not invoked at all - a bug is more probable if done handler performed necessary communication with the spawning thread.
The worst thing is - these may happen or not happen, depending on the timing. I.e. the task may still be running by the time the user calls the function the second time (what do you do then, by the way?)
So, do throw an exception unless task status is "not started". The user can always check the status and perform the necessary processing in the unlikely case she needs it.