We are trying to figure out how best to monitor long-running jobs automatically. Say, over X=3 hours. In Snowflake, users can put a resource governor that terminates these things. In EMR, users can monitor and alert. Is there a best practice or easy knob to turn to do this for Databricks jobs?
In the advanced drop-down for a task, there is an option to set a timeout.
See the docs for more options and information.
Related
As per title, if I am creating workers via helm or kubernetes, is it possible to assign "worker resources" (https://distributed.readthedocs.io/en/latest/resources.html#worker-resources) after workers have been created?
The use case is tasks that hit a database, I would like to limit the amount of processes able to hit the database in a given run, without limiting the total size of the cluster.
As of 2019-04-09 there is no standard way to do this. You've found the Worker.set_resources method, which is reasonable to use. Eventually I would also expect Worker plugins to handle this, but they aren't implemented.
For your application of controlling access to a database, it sounds like what you're really after is a semaphore. You might help build one (it's actually decently straightforward given the current Lock implementation), or you could use a Dask Queue to simulate one.
I'm connecting to Twitter's streaming API to get a stream of updates to my Rails app, adding them to the db, etc, etc.
What's the best way to do this on Heroku? Right now, I'm using the delayed_job gem - problem is that the job (connecting to the Twitter Streaming API) expires after hours.
Is there a way to make the job run forever, or a better way to do this?
Thanks
I wouldn't make a job "run forever" as that would mean loading the CPU forever too.
The way this is usually handled is by using a cron job which starts the specific script at specific intervals (every minute, every hour, every few days, etc.).
Almost every webhost provides an easy interface to setup such cron jobs via their backend (eg: CPanel).
In case you're running your own server, you probably already know how to configure such jobs. If you don't, you'll have to lookup the individual setup guide which fits the operating system you're running on your server… there's always a way to run "jobs" at specific intervals (even on MS Windows servers — via scheduling).
And for a more detailed description and better insight into what "cron" is, you might want to check the "cron" article at Wikipedia , which also provides some pretty good examples.
I'm currently using cron and "rails runner" to execute background jobs. For the most part these jobs are simple polls "Find the records that are due to receive a reminder email. Send that email."
I've been watching my Amazon EC2 Small instance, and noticed that each time one of these cron job kicks in, the CPU spikes to ~99%. The teeny tiny little query inside my current job is definitely not responsible. I'm presuming that the spike is simply due to the effort of loading the full rails environment via "rails runner".
Is there a more CPU efficient way to handle regularly scheduled batch jobs?
P.S. I know that in the particular example of sending a reminder email at time X in the future, I could delayed_jobs, and simply schedule the job in the future. Not every possible task fits into the delayed_jobs framework very well though, so I'm looking for a more traditional "cron job" type solution. Like "rails runner", but without the crazy CPU consequences.
You can use workers witch don't load rails env. Or load it only once(like resque)
I don't think there is a solution for this, since you do need to load a Rails environment to handle whatever that is you are handling. So when on the "cron" model you will be starting up a handler which in turn will create some load on your instance. I don't know how cloud services lend themselves to this, but I think the optimal model in your case would be to have a running daemon for job handling and forking coupled with REE for the job execution (that helps prevent memory leaks by letting as much as possible happen in the child process that will die at the end of the execution loop).
The daemon could be configured to accept signals (also via a job queue) that would spin off jobs doing specific things.
I need to build a background job that goes through a list of RSS feeds and analyze them say every 10 minutes.
I have been using delayed_job for handling background jobs and I liked it a lot. I believe though that it's not built for recurring background jobs. I guess I can auto-schedule background job at the end of everyone (maybe with begin..rescue just to ensure it gets executes). Or preschedule say a month of advance worth of jobs and have another one that reschedule the every month..etc
This raised some concerned to me as I started asking myself: what if the server goes down in the middle of execution and the jobs didn't get scheduled?
I have also looked at Daemons gems which seemed the like it runs simple Ruby scripts with start/stop commands. I like the way delayed_job schedules and handles retries.
What do you recommend using in this case? What do you think the best way to design such a system with recurring background jobs? Also do you know a way I can monitor that background process and get notified if it stops?
I just implemented delayed_job for a similar task (using :run_at => 2.days.from_now) and found it to be a perfect fit. The easiest way to handle your concern about a process failing is to make the first step of the job to create the next job. Also, you can create a has_many relationship to the delayed_job model which would allow you to access the :last_error. Or, look at the "Hooks" section of readme and it has a perfect example for failure.
I think that this was a similar question: A cron job for rails: best practices? - not only are there answers, but also links to railscasts about background jobs in rails.
I used cron + delayed_job, but scheduled tasks were supposed to run few times a day, mostly just once.
Take a look at SimpleWorker. It's an elastic scheduling and background processing worker queue. It's cloud based and has persistence and redundancy so you don't need to worry if your servers go down or are restarted.
Very flexible in terms of scheduling, provides great introspection of jobs in the queue as well as notifications on status and errors.
Full disclosure: I work at SimpleWorker.
Currently, my Nokogiri script iterates through Google's SERPs until it finds the position of the target website. It does this for each keyword for each website that each user specifies (users are capped on amount of websites & keywords they can track).
Right now, it's run in a rake that's hard-scheduled every day and batches all scrapes at once by looping through all the websites in the database. But I'm concerned about scalability and swarming Google with a batch of requests.
I'd like a solution that scales and can run these scrapes over the course of the day. I'm not sure what kind of solution is available or what I'm really looking for.
Note: The amount of websites/keywords change from day to day as users add and delete their websites and keywords. I don't mean to make this question too superfluous, but is this the kind of thing Beanstalkd/Stalker (job queuing) can be used for?
You will have to balance two issues: Scalability for lots of users versus Google shutting you down for scaping in violation of their terms of use.
So your system will need to be able to distribute tasks to various different IPs to conceal your bulk scraping which suggests at least two levels of queuing. One to manage all the jobs and send them to each separate IP for subsequent searching and collecting results and queues on each separate machine to hold the requested searches until they are executed and the results returned.
I have no idea what Google's thresholds are (I am sure they don't advertise it) but exceeding them and getting cut off would obviously be devastating for what you are trying to do so your simple looping rake task is exactly what you shouldn't do after a certain number of users.
So yes, use a queue of some sort but realize that you probably have a different goal from the typical goal of a queue in that you want to deliberately delay jobs rather that offload word to avoid UI delays. So you will be seeking ways to slow down the queue rather than have it just execute job after job as they arrive in the queue.
So based on a cursory inspection of DelayedJob and BackgroundJobs it looks like DelayedJob has what you would need with the run_at attribute. But I am only speculating here and I am sure an expert would have more to say.
If I'm understanding correclty, it sounds like one of these tools might fit the bill:
Delayed_job: https://github.com/tobi/delayed_job
or
BackgroundJobs: http://codeforpeople.rubyforge.org/svn/bj/trunk/README
I've used both of them, and found them easy to work with.
There are definitely some background job libraries that might work.
delayed_job: https://github.com/collectiveidea/delayed_job (beware of the unmaintained branch from tobi!)
resque: https://github.com/defunkt/resque
However, you might think about just scheduling a Cron job that runs more times during the day, and processes less items per run.
SaaS solution: http://momentapp.com/ "Launch delayed jobs with scheduled http requests" - disclaimer a) in beta b) I am not affiliated with this service