In my web app I use two recurring events that "clean up" one of the tables in the database, both executed every 15 minutes or so.
My question is, could this lead to problems in performance in the future? Because I've read somewhere -I don't recall where exactly- that MySQL events are supposed to be scheduled to run once a month or so. Thing is, this same events keep the table in a pretty reduced size (as they delete records older than 15~ minutes), maybe this compensates the frequency of their execution, right?
Also, is it better to have one big MySQL event or many small ones if they are be called in the same frequency?
I don't think there's a performance indication in the monthly base just more of a suggestion of what to do with it. So i think you're ok with doing your cleanup using the events.
In the end the documentation suggets that the events are
Conceptually, this is similar to the idea of the Unix crontab (also known as a “cron job”) or the Windows Task Scheduler.
And the concept for those is that you can run a task every minute if you wish to do so.
On the second part of that question:
Serialize or spread it up. If you split them up into many events that will run at the same time you will create spikes of possibly very high cpu usage that might slow down the application while processing the events.
So either pack everything into one event so it runs in succession or spread the single events up so they execute on different times during the 15 minutes timeframe. Personally i think the first one is to be preferred, pack them up into a single event as then they are guaranteed to run in succession, even if a single one of them keeps running longer than usual.
The same goes for cronjobs. If you shedule 30 long-running exports at a single time your application is going to fail miserably during that timeslot (learned that the hard way).
Related
I run a game statistics site. Its MySQL database is small potatoes compared to most of the things people work on around here, but shared hosting does necessitate an eye on query optimization, particularly when performing lots of joins and sub-queries.
Earlier this week I moved a rather slow (~0.5s) query that grouped, counted, averaged, and sorted the ratings of members to a nightly cron job. Results are stored in a table.
Because we average about one new rating per day, the change does not cause any perceptible data inaccuracy to my users, AND the new query which just grabs rows from the table runs in the ~0.000X range, so all pages pulling that data are noticeably faster.
Clearly this is a good thing!
And as I sat there basking in the glow of my cron job, my mind started running through other aspects of the site and mentally tagging those that could be cron'd... (many)
Which leads me to wonder - is it possible to use cron too much?
Because my site's database changes about once a day, I could conceivably run ALL complex queries (there are many) through nightly cron jobs and store the results in tables.
Is there ever a downside? (apart from data occasionally not being up-to-the-second accurate?)
Cron is great; it's usually a good thing to refrain from reinventing wheels. Some applications have more precise needs than cron can accommodate, so that's one reason not to use it. Also, distributing and managing cronjobs that are to form an integral part of your app can be difficult and error-prone, especially absent a competent package manager from the OS. Troubleshooting can be a little bit of a pain, particularly when there's one server missing one of its 100 cronjobs or something, but that can be managed with an OS package manager or with something like puppet.
But my opinion is to use cron whenever you can and makes sense, rather than rolling your own.
You're not beginning to approach the limits of what amount of jobs can (or should) be scheduled with cron. You'll be just fine. :)
You might want to consider a worker-message queue like gearman to trigger jobs that should be run 'after the fact', but not necessarily on a fixed schedule.
how about one cron job that runs all your procedures?
I once worked on a unix system that failed pretty miserably after the cron job queue exceeded 20 entries. The queue did not execute on any predictable cycle - i.e. FILO, FIFO LIFO etc. it simply was randomized
You might consider using triggers to keep your summary statistics up to date. There's also an event scheduler in MySQL 5.1+ if you like running queries periodically.
http://dev.mysql.com/doc/refman/5.0/en/triggers.html
http://dev.mysql.com/doc/refman/5.1/en/events.html
I'd like to use MySQL as a job queue. Multiple machines will be producing and consuming jobs. Jobs need to be scheduled; some may run every hour, some every day, etc.
It seems fairly straightforward: for each job, have a "nextFireTime" column, and have worker machines search for the job with the nextFireTime, change the status of the record to "inProcess", and then update the nextFireTime when the job ends.
The problem comes in when a worker dies silently. It won't be able to update the nextFireTime or set the status back to "idle".
Unfortunately, jobs can be long-running, so a reaper thread that looks for jobs that have been inProcess too long isn't an option. There's no timeout value that would work.
Can anyone suggest a design pattern that would properly handle unreliable worker machines?
Maybe like this
When a worker fetches a job it can add it's process-id or another unique id to a field in the job
Then in another table every worker keeps updating a value that they are alive. When updating the "i'm alive" field you check all other "last time worker showed sign of life". If one worker is over a limit, find all the jobs it is working on and reset them.
So in other words the watchdog works on the worker-processes and not the jobs themselves.
Using MySQL as a job queue generally ends in pain, as it's a very poor fit for the usual goals of an RDBMS. User 'toong' already linked to https://www.engineyard.com/blog/5-subtle-ways-youre-using-mysql-as-a-queue-and-why-itll-bite-you, which has a lot of interesting stuff to say about it. Unreliable workers are only one of the complications.
There are many, many systems for handling job distribution, mostly distinguished by the sophistication of their queueing and scheduling capabilities. On the simple FIFO end are things like Resque, Celery, Beanstalkd, and Gearman; on the sophisticated end are things like GridEngine, Torque/Maui, and PBS Pro. I highly recommend the new Amazon Simple Workflow system, if you can tolerate reliance on an Amazon service (I believe it does not require that you be in EC2).
To your original question: right now we're implementing a per-node supervisor that can tell if the node's jobs are still active, and sending a heartbeat back to a job monitor if so. It's a pain, but as you are discovering and will continue to discover, there are a lot of details and error cases to manage. Mostly, though, I have to encourage you to do yourself a favor by learning about this domain and build the system properly from the start.
One option is to make sure that jobs are idempotent, and allow more than one worker to start a given job. It doesn't matter which worker completes the job, or if more than one worker completes the job; since the jobs are designed in such a way that multiple completions are handled gracefully. perhaps workers race to supply the result, and the losers find that the slot that will hold the result is already full, so they just drop them.
Another option is to not have big jobs. Break long running jobs into intermediate steps, if the job takes longer than (say) 1 minute, store the intermediate results as a new job (with a link to the old job in some way), so that the new job can be queued again to do another minute of work.
Is there another way to prevent nightly cron jobs that do batch processing against mysql from impacting online webserver->mysql queries other than setting query priority? I'm thinking there may be a way to segment these, but I'm not sure if this is possible?
Try and break the queries down, perhaps rather than processing lots of data in one go try and process smaller batches but more often. This way you will lock tables for less time and allow gaps for queries from the frontend to be executed.
Another solution would be to process more often but even during the day. My last project used an event system, so that a user would comment something and this event would go into a queue. A background process (executed from The Fat Controller) would then take this event and insert data so that all the user's friends news feeds were updated about the comment. That way feeds are updated by simple insert statements and not rebuilt from scratch every x hours.
is there any software that does "lazy" deletion of the rows from the table. I would like to do maintenance of my tables when my server is idle, and ideally i should be able to define what "idle" is (num of database connections/system load/ requests per second). Is there anything remotely similar to this?
If you are on a linux server, you can make your table cleanup scripts only run based on the output of the command "w" which will show you a system load. If your system load is under say .25 you can run your script. Do this with shell scripting.
To some degree, from an internal perspective InnoDB already does this. Rows are initially marked as deleted, but only made free as part of a background operation.
My advice: You can get in to needlessly complicated problems if you try and first check if the server is idle. i.e.
What if it was idle, but the cleanup takes 2 minutes. During that 2 minutes the server load peaks?
What if the server never becomes idle enough? Now you just have an unlimited backlog.
If you just background the task you might improve performance enough, since now at least no users will be sitting in front of web pages waiting for it to complete. Look at activity graphs as to what is the best time to schedule it (3am, 5am etc).
How many tasks can task scheduler run at the same time?
I have set up three backup tasks from within SQLyog, all to start running at 12:00 am and run at subsequent 4 hours until midnight. Each task will backup all tables from three different databases to a network attached storage.
Will there be any impact on the MySQL Server performance or is there any chance for a task to be missed?
Thank you for any input.
It's usually considered proper to space out the scheduled tasks, even if only by 1 minute.
Since I don't know whether your tasks can be consolidated or optimized, and I don't know how long they'll take to run, I'll recommend you space them out by an hour or so.
There is some performance impact from a backup, which is part of the reason they're usually done at night (and, of course, there are fewer transactions being run on the database since people usually aren't working), and three running at the same time ... Well, it's not something I would wish on my database or my users.
To answer the original question: the scheduler can run a lot of things at the same time :)