I have the following code in a controller
user = RegUser.create_reg_user(:some_parameters)
UserStuff.pass_user(some_parameters)
#hex = user.hex
The #hex is passed to the view and returned. The UserStuff call is taking a decent amount of time and is not actually important to the #hex which is needed for the view. Is there a way to go ahead and return the #hex and load the view and let the UserStuff process afterwards?
Offload these kinds of long running "jobs" to a background queue. Probably the easiest for you to get setup and running is Delayed Job.
We use Beanstalkd (a queue) and many worker processes to handle all long-running tasks (or any tasks that takes longer than 1-2 seconds).
The beauty of having a background system to process these kinds of jobs is that you can scale quickly, you can spin-up any number of worker processes which all pull jobs from a master queue (or DB in the case of Delayed Job).
Delayed Job is good, and easy to use. I recommend it.
Related
I am using Delayed jobs for my Ruby app hosted in Heroku to perform a very long task that can take up to 5 minutes.
I've noticed that, in development mode at least, when this task is running the ones that come afterwards are not started until that one finishes. I would like other tasks to be able to start running without having to wait for the other to finish (to have at least 3 concurrent tasks, for example).
I don't wish to increase the number of workers in Heroku ($$$).
I noticed the 'pool' param in delayed jobs but I don't fully understand if this is what I need or how to use it.
https://github.com/collectiveidea/delayed_job/blob/master/README.md
I achieved it using threads in the task code, but maybe this is not the best way to do it.
If you could tell me exactly how I could achieve concurrency in delayed jobs I would really appreciate it.
A DJ worker only runs a single job at a time. If you want concurrent processing of your background jobs, you'll need multiple background workers.
You are way better off implementing sidekiq.
I have the following tasks to do in a rails application:
Download a video
Trim the video with FFMPEG between a given duration (Eg.: 00:02 - 00:09)
Convert the video to a given format
Move the converted video to a folder
Since I wanted to make this happen in background jobs, I used 1 resque worker that processes a queue.
For the first job, I have created a queue like this
#queue = :download_video that does it's task, and at the end of the task I am going forward to the next task by calling Resque.enqueue(ConvertVideo, name, itemId). In this way, I have created a chain of queues that are enqueued when one task is finished.
This is very wrong, since if the first job starts to enqueue the other jobs (one from another), then everything get's blocked with 1 worker until the first list of queued jobs is finished.
How should this be optimised? I tried adding more workers to this way of enqueueing jobs, but the results are wrong and unpredictable.
Another aspect is that each job is saving a status in the database and I need the jobs to be processed in the right order.
Should each worker do a single job from above and have at least 4 workers? If I double the amount to 8 workers, would it be an improvement?
Have you considered using sidekiq ?
As said in Sidekiq documentation :
resque uses redis for storage and processes messages in a single-threaded process. The redis requirement makes it a little more difficult to set up, compared to delayed_job, but redis is far better as a queue than a SQL database. Being single-threaded means that processing 20 jobs in parallel requires 20 processes, which can take a lot of memory.
sidekiq uses redis for storage and processes jobs in a multi-threaded process. It's just as easy to set up as resque but more efficient in terms of raw processing speed. Your worker code does need to be thread-safe.
So you should have two kind of jobs : download videos and convert videos and any download video job should be done in parallel (you can limit that if you want) and then each stored in one queue (the "in-between queue") before being converted by multiple convert jobs in parallel.
I hope that helps, this link explains quite well the best practices in Sidekiq : https://github.com/mperham/sidekiq/wiki/Best-Practices
As #Ghislaindj noted Sidekiq might be an alternative - largely because it offers plugins that control execution ordering.
See this list:
https://github.com/mperham/sidekiq/wiki/Related-Projects#execution-ordering
Nonetheless, yes, you should be using different queues and more workers which are specific to the queue. So you have a set of workers all working on the :download_video queue and then you other workers attached to the :convert_video queue, etc.
If you want to continue using Resque another approach would be to use delayed execution, so when you enqueue your subsequent jobs you specify a delay parameter.
Resque.enqueue_in(10.seconds, ConvertVideo, name, itemId)
The down-side to using delayed execution in Resque is that it requires the resque-scheduler package, so you're introducing a new dependency:
https://github.com/resque/resque-scheduler
For comparison Sidekiq has delayed execution natively available.
Have you considered merging all four tasks into just one? In this case you can have any number of workers, one will do the job. It will work very predictable, you can even know how much time will take to finish the task. You also don't have problems when one of the subtasks takes longer than all others and it piles up in the queue.
I have a rake task which is going to call 4 more rake tasks, in order:
rake:one
rake:two
rake:three
rake:four
Rake tasks one, two, and three are getting data and adding it to my database. Then rake:four is going to do something with that data. But I need to make sure that one, two, and three are complete first. Each rake task is actually spinning up Sidekiq workers to run in the background. In this scenario, would all of the workers created by rake:one finish first, then rake:two, etc?
If not, how can I ensure that the workers are executed in order?
Sidekiq processes jobs in the order which they are created, but by default it processes multiple jobs simultaneously, and there is no guarantee that a given job will finish before another job is started.
Quoting from https://github.com/mperham/sidekiq/wiki/FAQ:
How can I process a certain queue in serial?
You can't, by design. Sidekiq is designed for asynchronous processing
of jobs that can be completed in isolation and independent of each
other. Jobs will be popped off of Redis in the order in which they
were pushed but there's no guarantee that Job #1 will execute fully
before Job #2 is started.
If you need serial execution, you should look into other systems which
give those types of guarantees.
Note you can create a Sidekiq process dedicated to processing a queue
with a single worker. This will give you serial execution but it's a
hack.
Also note you can use third-party extensions for sidekiq to achieve
that goal.
You can simply create one meta rake task, which will include all those tasks in right order.
Or as a less hacky solution: reduce number of workers per queue to 1:
https://github.com/brainopia/sidekiq-limit_fetch#limits
And add all your jobs to this queue
In the Sidekiq wiki it is stated:
Make your jobs small and simple
I get simple, I get idempotent and transactional, but what is small? Maybe required Memory and Computing Time is a good measure? My Sidekiq jobs take between 10sec and 30min.
I think that 10sec is okay, but what about the long-running task of 30min? I am loading all the data of a certain type from the database into memory, run lengthy computations on them and then write back the results. All three things in one worker job.
Is that fine? Or should I instead invoke from a worker job, multiple worker jobs that run the small computations? The problem is, these small computations may need some complex hash tables to do the computations and it was suggested not to persist this in Redis, only small simple values.
That depends on how often you want/have to invoke the job and whether it is acceptable to you that it takes so long.
If you run the job in shorter intervals than it takes to finish it certainly is too long.
Splitting it up into multiple workers would only help here if you could improve the total run time (e.g. if some of it can be run at the same time)
So rule of thumb as always: as long as it suits your needs it is ok.
However:
on long jobs you should consider that the job might fail mid-execution for whatever reason (server crashes etc).
Can you still continue this lengthy job there or will it be rolled back properly?
Also: What happens if data is changed while you are executing the job?
I need to process files which get uploaded and it can take as little as 1 second or as much as 10 minutes. Currently my solution is to make a quartz job with a timer of 30 seconds and then process and arbitrary job whenever it hits. There are several problems with this.
One: if the job will take less than a few seconds it is wasteful to make things wait 30 seconds for the job queue.
Two: if there is only one long job in the queue it could feasibly try to do it twice.
What I want is a timeless queue. When things are added the are started immediately if there is a free worker. Is there a solution for this? I was looking at jesque, but I couldn't tell if it can do this.
What you are looking for is a basic message queue. There are lots of options out there, but my favorite for Grails is RabbitMQ. The Grails plugin for it is quite good and it performs well in my experience.
In general, message queues allow you to have N producers (things creating jobs") adding work messages to a queue and then M consumers pulling jobs off of the queue and processing them. When a worker completes it's job, it simply asks the queue for the next job to process and if there is none, it just waits for the queue to give it something to do. The queue also keeps track of success / failure of message processing (you can control this) so that you don't give the same message to more than one worker.
This has the advantage of not relying on polling (so you can start processing as soon as things come in) and it's also much more scaleable. You can scale both your producers and consumers up or down as needed, decoupling the inputs from the outputs so that you can take a traffic spike and then work your way through it as you have the resources (workers) available.
To solve problem one just make the job check for new uploaded files every 5 seconds (or 3 seconds, or 1 second). If the check for uploaded files is quick then there is no reason you can't run it often.
For problem two you just need to record when you start processing a file to ensure it doesn't get picked-up twice. You could create a table in the database, or store the information in memory somewhere.