We use node camunda-external-task-client-js to handle camunda external tasks.
Following is the client configuration
"topic_name": "app-ext-task",
"maxTasks": 5,
"maxParallelExecutions": 5,
"interval": 500,
"usePriority": true,
"lockDuration":2100000,
"workerId": "app-ext-task-worker"
We are getting external task details and able to processing them,But some times we see some tasks are getting deprioritised.
We are not setting any priority to any external task, by default all tasks are assigned priority 0.
We expect all tasks will execute in sequential manner, we agree some tasks may take more time than the subsequent task so that the taks-1 may take more time than task-2.
Ex: If a queue contains 10 taks [task1,taks-2,task-3,task-4,task-5,...task-10]
All the tasks executed sequentially as all the tasks have same priority.
1st:task-1,
2nd:task-2
3rd: task-3
Problem:
We see some tasks are getting deprioritised it means early messages are taking priority over existing messages.
1st:task-1,
2nd:task-2
3rd: task-4
4th: task-5
5th: task-6
6th: task-7
7th: task-8
8th: task-3
I am seeing problem at 2 places
While producing the message, camunda could have not posted the message in QUEUE.
While reading the Queue camunda external tasks are not processed properly.
I didn't find much docs on this, I don't know how do I debug this.
For me this is an intermitent issue, as I am not able to find the root cause of the problem.
I am not sure how to debug this as well.
Is my expectation wrong in camunda queues?
The external tasks do not form a "queue". They are instances in a pool of possible tasks, your worker fetches "some" tasks, which might be in order or not. You could prioritise the tasks, but still, if you have 10 "highest" prio tasks in the pool and the worker fetches 5, you won't be able to determine which are chosen.
But you have a process engine at hand, if keeping the sequence is essential for your process, why do you start all tasks at once and rely on the external worker to keep the order? Why not just creating one task at a time and continue when it is finished?
Related
There is a task which creates database record {R) when it runs for the first time. When task is started second time it should read database record, perform some calculations and call external API. First and second start happens in a loop
In case of single start of the task there are no problems, but in the case of loops (at each loop's iteration the new task is created and starts at certain time) there is a problem. In the task queue (for it we use a flower) we have crashed task on every second iteration.
If we add, at the and of the loop time.sleep(1) sometimes the tasks work properly, but sometimes - not. How to avoid this problem? We afraid that task for different combination of two users started at the same time also will be crashed.
Is there some problem with running tasks in Celery simultaneously? Or something we should consider, tasks are for scheduled payments so they have to work rock solid
Since my project has so many moving parts.. probably best to explain the symptom
I have 1 scheduler running on 1 queue. I add scheduled jobs ( to be executed within seconds of the scheduling).
I keep repeating scheduling of jobs with NO rq worker doing anything (in fact, the process is completely off). In another words, the queue should just be piling up.
But ALL of a sudden.. the queue gets chopped off (randomly) and first 70-80% of jobs just disappear.
Does this have anything to do with:
the "max length" of queue? (but i dont recall seeing any limits)
does the scheduler automatically "discard" jobs where the start time
is BEFORE the current time?
ran my own experiment. RQ scheduler does indeed remove jobs whose start date < now.
We are using azure web job for batch processing, the job will trigger when there is a message in the storage queue.
We have configured the job to execute the messages one by one.
JobHostConfiguration config = new JobHostConfiguration();
config.Queues.BatchSize = 1;
config.Queues.MaxDequeueCount = 1;
even though the job is taking multiple messages from the storage queue and executing parallelly.
Please help.
taking multiple messages from the storage queue and executing
parallelly
How did you judge take multiple messages and executing in parallel? Did you have multiple instances?
I test the code in different situations.
1)The normal situation ,not set the batchsize, it will drag all messages in the queue.However i think it still run one by one.But from the result i think it won't wait last running completely over.Here is result.
2)Set the batchsize to 1, if you debug the code or refresh the queue frequently, you will find it did drag one message one time run. And here is result.
3) Set the batchsize to three and debug , it just change the message number dragged, each time it will drag 3 messages, then it will run like normal without setting batchsize.Here is the result.And i found if you just run not debug , the order console showing is very orgnized.
So if you don't have other instance running, i think this is working in sequential mode.
If this doesn't match your requirements or you still have questions, please let me know.
I have below code in supervisor which keep polling the jobs table
program:laravel-queue-listener]
command=php /var/www/laravel/artisan queue:work --sleep=120 --tries=2 --daemon
Question: Right now, it goes to database to check pending jobs after each 2 minutes...Is there any way to process queues on demand? I meant when the below code executes...it may process the queue and before that check if the queue is already processing or not...
Is there any such function in the Framework to process queues manually and check if the queue is currently polling or processing any job or not?
$User->notify(new RegisterNotification($token, $User));
I understand your question as how to process queues on demand in Laravel. There is already a detailed answer here but the command you are looking for is.
php artisan queue:work --once
However if what you are trying to do is to run the queue worker when an event happens, you can still do that by invoking the queue worker from code. Example:
public static function boot(){
static creating($user){
Artisan::call('queue:work --once');
}
}
I've read about graceful shutdowns here using the WEBJOBS_SHUTDOWN_FILE and here using Cancellation Tokens, so I understand the premise of graceful shutdowns, however I'm not sure how they will affect WebJobs that are in the middle of processing a queue message.
So here's the scenario:
I have a WebJob with functions listening to queues.
Message is added to Queue and job begins processing.
While processing, someone pushes to develop, triggering a redeploy.
Assuming I have my WebJobs hooked up to deploy on git pushes, this deploy will also trigger the WebJobs to be updated, which (as far as I understand) will kick off some sort of shutdown workflow in the jobs. So I have a few questions stemming from that.
Will jobs in the middle of processing a queue message finish processing the message before the job quits? Or is any shutdown notification essentially treated as "this bitch is about to shutdown. If you don't have anything to handle it, you're SOL."
If we are SOL, is our best option for handling shutdowns essentially to wrap anything you're doing in the equivalent of DB transactions and implement your shutdown handler in such a way that all changes are rolled back on shutdown?
If a queue message is in the middle of being processed and the WebJob shuts down, will that message be requeued? If not, does that mean that my shutdown handler needs to handle requeuing that message?
Is it possible for functions listening to queues to grab any more queue messages after the Job has been notified that it needs to shutdown?
Any guidance here is greatly appreciated! Also, if anyone has any other useful links on how to handle job shutdowns besides the ones I mentioned, it would be great if you could share those.
After no small amount of testing, I think I've found the answers to my questions and I hope someone else can gain some insight from my experience.
NOTE: All of these scenarios were tested using .NET Console Apps and Azure queues, so I'm not sure how blobs or table storage, or different types of Job file types, would handle these different scenarios.
After a Job has been marked to exit, the triggered functions that are running will have the configured amount of time (grace period) (5 seconds by default, but I think that is configurable by using a settings.job file) to finish before they are exited. If they do not finish in the grace period, the function quits. Main() (or whichever file you declared host.RunAndBlock() in), however, will finish running any code after host.RunAndBlock() for up to the amount of time remaining in the grace period (I'm not sure how that would work if you used an infinite loop instead of RunAndBlock). As far as handling the quit in your functions, you can essentially "listen" to the CancellationToken that you can pass in to your triggered functions for IsCancellationRequired and then handle it accordingly. Also, you are not SOL if you don't handle the quits yourself. Huzzah! See point #3.
While you are not SOL if you don't handle the quit (see point #3), I do think it is a good idea to wrap all of your jobs in transactions that you won't commit until you're absolutely sure the job has ran its course. This way if your function exits mid-process, you'll be less likely to have to worry about corrupted data. I can think of a couple scenarios where you might want to commit transactions as they pass (batch jobs, for instance), however you would need to structure your data or logic so that previously processed entities aren't reprocessed after the job restarts.
You are not in trouble if you don't handle job quits yourself. My understanding of what's going on under the covers is virtually non-existent, however I am quite sure of the results. If a function is in the middle of processing a queue message and is forced to quit before it can finish, HAVE NO FEAR! When the job grabs the message to process, it will essentially hide it on the queue for a certain amount of time. If your function quits while processing the message, that message will "become visible" again after x amount of time, and it will be re-grabbed and ran against the potentially updated code that was just deployed.
So I have about 90% confidence in my findings for #4. And I say that because to attempt to test it involved quick-switching between windows while not actually being totally sure what was going on with certain pieces. But here's what I found: on the off chance that a queue has a new message added to it in the grace period b4 a job quits, I THINK one of two things can happen: If the function doesn't poll that queue before the job quits, then the message will stay on the queue and it will be grabbed when the job restarts. However if the function DOES grab the message, it will be treated the same as any other message that was interrupted: it will "become visible" on the queue again and be reran upon the restart of the job.
That pretty much sums it up. I hope other people will find this useful. Let me know if you want any of this expounded on and I'll be happy to try. Or if I'm full of it and you have lots of corrections, those are probably more welcome!