I am looking for a good background job processor with following ability,
Works well with MySql
Can have priorities
Can easily schedule anything in background( not just emails)
Ability to reinitialize the job after completion (callback would be good. I have few task/jobs that keeps on running after every minutes), even a repetitive scheduler would work
Should not eat up lot of memory, (have this experience with DJ)
Few options that I am looking into Resque, DJ, Beanstalkd (haven't explored completely)
I have my production env in Amazon EC2 (if this helps for better solution)
Please suggest me which is a good option, is there something else apart from these that people use nowadays ?
I'd heartily recommend sidekiq - it's extremely flexible and it uses far less resources than Resque or DelayedJob.
It does require redis (like Resque), but redis is valuable addition to any Rails project since it can be reused as a session store and cache. Our primary db is MySQL and we deploy to EC2 :-) We've used delayed job and rescue in the past, but found them problematic and heavy on the resources they use. Sidekiq uses threads and a single sidekiq worker is as efficient as several DJ/Resque workers. Here's an interesting part of the project's README that I can corroborate:
You'll find that you might need 50 200MB resque processes to peg your
CPU whereas one 300MB Sidekiq process will peg the same CPU and
perform the same amount of work. Please see my blog post on Resque's
memory efficiency and how I was able to shrink a Carbon Five client's
resque processing farm from 9 machines to 1 machine.
To sum it all up:
It works fine with MySQL - not really, but it doesn't have problems with MySQL either
You can have priorities by setting up different processing queues
You can easily schedule anything (and there is special ala DJ support for e-mails in particular)
Not quite sure about that, we use whenever + cron for repetitive jobs
You're gonna love Sidekiq's small memory footprint
Related
We're building a web-app where users will be uploading potentially large files that will need to be processed in the background. The task involves calling 3rd-party APIs so each job can take several hours to complete. We're using DelayedJob to run the background jobs. With every user kicking off a background job, each of which will take a few hours to finish, that will add up to a lot of background jobs every quickly. I am wondering what would be the best way to setup the deployment for this? We're currently hosted on DigitalOcean. I've kicked off 10 DelayedJob workers. Each one (when ideal) takes up 157MB. When actively running it utilizes around 900 MB. Our user-base right now is pretty small so it's not an issue but will be one soon. So on a 4GB droplet, I can probably run like 2 or 3 workers at a time. How should we approach this issue? Should we be looking at using DigitalOcean's API to auto-spin cheap droplets on demand? Should we subscribe to high-memory droplets on a monthly basis instead? If we go with auto-spinning droplets, should we stick with DigitalOcean or would Heroku make more sense? Or is the entire approach wrong and should we be approaching it from an entire different direction? Any help/advice would be very much appreciated.
Thanks!
It sounds like you are limited by memory on the number of workers that you can run on your DigitalOcean host.
If you are worried about scaling, I would focus on making the workers as efficient as possible. Have you done any benchmarking to understanding where the 900MB of memory is being allocated? I'm not sure what the nature of these jobs are, but you mentioned large files. Are you reading the contents of these files into memory, or are you streaming them? Are you using a database with SQL you can tune? Are you making many small API calls when you could be using a batch endpoint? Are you assigning intermediary variables that must then be garbage collected? Can you compress the files before you send them?
Look at the job structure itself. I've found that background jobs work best with many smaller jobs rather than one larger job. This allows execution to happen in parallel, and be more load balanced across all workers. You could even have a job that generates other jobs. If you need a job to orchestrate callbacks when a group of jobs finishes there is a DelayedJobGroup plugin at https://github.com/salsify/delayed_job_groups_plugin that allows you to invoke a final job only after the sibling jobs complete. I would aim for an execution time of a single job to be under 30 seconds. This is arbitrary but it illustrates what I mean by smaller jobs.
Some hosting providers like Amazon provide spot instances where you can pay a lower price on servers that do not have guaranteed availability. These pair well with the many fewer jobs approach I mentioned earlier.
Finally, Ruby might not be the right tool for the job. There are faster languages, and if you are limited by memory, or CPU, you might consider writing these jobs and their workers in another language like Javascript, Go or Rust. These can pair well with a Ruby stack, but offload computationally expensive subroutines to faster languages.
Finally, like many scaling issues, if you have more money than time, you can always throw more hardware at it. At least for a while.
I thing memory and time is more problem for you. you have to use sidekiq gem for this process because it will consume less time and memory consumption for doing the same job,because it uses redis as database which is key value pair db.if the problem continues go with java script.
Is there anything in its architecture that makes it hard to do?
I want to run an existing rails+sidekiq application in a VM with very little memory, and loading the entire rails stack in two different process is using a lot of RAM.
Puma is built to spin up homogenous web worker threads, and divide incoming requests among them. If you wanted to modify it to spawn off separate Sidekiq threads, it should technically be possible with a crazy puma.rb file, but there's no precedent I can find for doing so (edit: Mike’s answer below points out that the sucker_punch gem can essentially do this, for the same purpose of memory efficiency). Practically-speaking, if your VM cannot support running two Rails processes at a time, it probably won't be able to handle the increased memory load as your application does the work of both Sidekiq and Puma… but that depends on your workload.
If this is just for development purposes, you might be able to accomplish what you're looking for by turning on Sidekiq's inline mode (normally meant just for testing):
require 'sidekiq/testing'
Sidekiq::Testing.inline!
This will cause all perform_async calls to actually execute inline, instead of going into Redis and being picked up by the Sidekiq process.
Nothing official.
This is what sucker_punch is designed for.
I have 16 resque queues and when I try to see the memory allocaton for these queues it is showing like 4% of the memory for each fo these queues. But at that time all these queues are empty. SO, out of 100% of my memory nearly 64% is utilized by the environment load itself. Thats what I feel.
My doubt are
1. Will each of these resque queues loads the complete application into memory separately.
If Yes, can I make any change to the resque configuation in such a way that all resque queues use the same environment loaded in a single place in memory.
Thanks in advance
I think you are out of luck if you're using Resque. I believe this is why Sidekiq was developed as a nearly drop-in replacement for Resque. The author of Sidekiq wrote a blog post describing how he improved Resque's memory usage. Here's a little bit from the Sidekiq FAQs:
Why Sidekiq over Multi-threaded Resque?
Back at Carbon Five I worked on improving Resque to use threads
instead of forking. That project was the basis for Sidekiq. I would
suggest using Sidekiq over that fork of Resque for a few reasons:
MT Resque was a one-off for a Carbon Five client and is not supported.
There are a number of bugs that were not solved, e.g. the web UI's
display of worker threads, because they were not important to the
client.
Sidekiq was built from the ground up to use threads via
Celluloid.
Sidekiq has middleware, which lets you do cool things in
the job lifespan. Resque doesn't support middleware like this
natively.
In short, MT Resque: a quick hack to save one client a lot of money, Sidekiq: the well designed solution for the same problem.
I just got the last month heroku bill, and the scheduled rake tasks were a relatively heavy burden. We are pretty early in our development process, so we just developed some rake tasks to get the job done recently, and didn't had much concern in theirs optimization.
Now we want to improve theirs performance and theirs heroku processing hours usage. We use New Relic to monitor the webapp performance, but apparently this type of rake tasks are ignored by default, and it's unclear how to override that.
Anyone had a similiar problem? How can I track the scheduled tasks in close to real time to monitor performance, optimize, and don't get suprise bills?
Whilst you can't really monitor rake tasks that well, there are a few little things you can do. One is the use of logging. Output start and end times of tasks to logs, and you can then see what's been happening duration wise. If you couple this with something like the Papertrail add-on then you can do additional interrogation later on.
As for running the jobs themselves, there's a couple of ways that you can run background processes which are dependant on how they need to run:
If you're needing to run jobs on a schedule, there's a few options available. Firstly there's the Heroku scheduler, which is pretty good, but doesn't guarantee executions will happen. Normally you would use this to kick off a rake task which will bring up a one-off dyno for the duration of the task - therefore you need to ensure in development that these tasks are as efficient as possible.
Alternatively, if you're looking at jobs that need a little more control or using a clock process. Essentially this is a dyno running 24/7 that does nothing but kick off other jobs at preset intervals and times. This would normally be done using the clockwork gem. The downside of this approach is that you need to pay for a clock process all the time.
A third approach, and one that might work is delayed job, with it's runat option, allowing you to queue a job to be run in the future (and jobs can re-queue themselves). There are a few issues with this in that a failure can kill the whole chain, and you need a full time worker running to process them all.
Therefore, in order to minimize your bills, ensure that your rake tasks are as performant and reliable, and then choose the scheduling option that suits you. If you're looking at schedules plus user created events, delayed_job might be the best option. If you're looking at a few tasks running periodically, then go scheduler. If you're looking at running lots of time critical jobs on a regular basis, go with clockwork.
Either way, you should be able to constrain a fair amount of processing into just one or two processes depending on your approach.
I know this question is almost 10 years old, but there is a new way!
You can now monitor your Heroku Scheduler jobs using One-off Dyno Metrics. This Heroku add-on gathers metrics for all detached one-off dynos running in your Heroku app. It was created to be an extension of Heroku's Application Metrics and works out of the box.
when you are running on heroku cedar there is a way to get a free setup for your workers. this is no answer to your monitoring question, but it might be interesting anyways: http://blog.nofail.de/2011/07/heroku-cedar-background-jobs-for-free/
You can force the New Relic agent to start in your rake tasks and report their performance data.
Not the answer to the specific question,but...
One method of reducing overhead is using Unicorn server to get multiple workers working on one dyno. It depends on your set up, but most people who've taken the time to test it can comfortably get 3 - 4 worker processes running concurrently. It's a huge boost in clearing cues or tasks. Just be careful not to max out the allocated memory for the dyno.
I'm coming from a PHP environment (at least in terms of web dev) and into the beautiful world of Ruby, so I may have some dumb questions. I imagine there are some fundamentally different options available when not using PHP.
In PHP, we use memcache to store alerts we want to display in a bar along the top of the page. When something happens that generates an alert (such as a new blog post being made), a cron script that runs once every 5 minutes or so puts that information into memcache.
Now when a user visits the site, we look in memcache to find any alerts that they haven't already dismissed and we display them.
What I'm guessing I can do differently in Rails, is to by-pass the need for a cron script, and also the need to look in memcache on every request, by using a Singleton and a polling process running in a separate thread to copy from memcache to this singleton. This would, in theory, be more optimized than checking memcache once-per-request and also encapsulate the polling logic into one place, rather than being split between a cron task and the lookup logic.
My question is: are there any caveats to having some sort of runloop in the background while a Rails app is running? I understand the implications of multithreading, from Objective-C/Java, but I'm asking specifically about the Rails (3) environment.
Basically something like:
class SiteAlertsMap < Hash
include Singleton
def initialize
super
begin_polling
end
# ... SNIP, any specific methods etc ...
private
def begin_polling
# Create some other Thread here, which polls at set intervals
end
end
This leads me into a similar question. We push (encrypted) tasks onto an SQS queue, for things related to e-commerce and for long-running background tasks. We don't use cron for this, but rather we have a worker daemon written in PHP, which runs in the background. Right now when we deploy, we have to shut down this worker and start it again from the new code-base. In Rails, could I somehow have this process start and stop with the rails server (unicorn) itself? I don't think that's something I'd running on the main process in a separate thread, since we often want to control it as a process by itself, but it would be nice if it just conveniently ran when the web application was running.
Threading for background processes in ruby would be a terrible mistake, especially since you're using a multi-process server. Using unicorn with say 4 worker processes would mean that you'd be polling from each of them, which is not what you want. Ruby doesn't really have real threads, it has green threads in 1.8 and a global interpreter lock in 1.9 IIRC. Many gems and libraries are also obnoxiously unthreadsafe.
Using memcache is still your best option and, if you have it set up correctly, you should only see it adding a millisecond or two to the request time. Another option which would give you the benefit of persisting these alerts while incurring minimal additional overhead would be to store these alerts in redis. This would better protect you against things like memcache crashing or server reboots.
For the background jobs you should use a similar approach to what you have now, but there are several off the shelf handlers for this like resque, delayed_job, and a few others. If you absolutely have to use SQS as the backend queue, you might be able to find some code to help you, but otherwise you could write it yourself. This still requires the other daemon to be rebooted whenever there is a code change. In practice this isn't a huge concern as best practices dictate using a deployment system like capistrano where a rule can easily be added to bounce the daemon on deploy. I use monit to watch the daemon process, so restarting it is as easy as telling monit to restart it.
In general, Ruby is not like Java/Objective-C when it comes to threads. It follows the more Unix-like model of process based isolation, but the community has come up with best practices and ways to make this less painful than in other languages. Ruby does require a bit more attention to setting up its stack as it is not as simple as enabling mod_php and copying some files around, but once the choices and architecture is understood, it is easier to reason about how your application works. The process model, in my opinion, is much better for web apps as it isolates code and state from the effects of other running operations. The isolation also makes the app easier to work with in a distributed system.