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From: hukl <hukl@berlin.ccc.de>
To: unicorn-public@bogomips.org
Subject: Re: WTF is up with memory usage nowadays?
Date: Mon, 12 Dec 2016 10:49:47 +0100	[thread overview]
Message-ID: <584E72BB.70303@berlin.ccc.de> (raw)
In-Reply-To: <20161212021000.GA15226@untitled>

I agree with most of what you've written. I drew my conclusions a while 
ago and switched to using Erlang (not Elixir!) for all my backend jobs 
in the past couple of years. In a way it is a more constraint / 
restricted environment. There are less libraries and frameworks 
available and the language itself is smaller in terms of available 
constructs, ways of doing things and how dynamic it feels. But I like 
the constraints. A small language is easier to reason about especially 
if there are not 23 different ways of assigning a value to a variable etc.

Looking back at my Ruby times I often feel like that Ruby was not 
created with the intention to become a universal, high performance 
backend programming language and its amazing that still it got that far. 
Unicorn was one of the big steps enabling us to build somewhat large 
scale backend and that was a big help.

However it feels like people keep putting lipstick on a pig, hoping that 
eventually it will become a shiny, metallic, high performance backend 
programming environment. But it will always remain a pig … or Ruby - no 
matter how many layers of lipstick or abstractions you put on it - and 
in Rubyland people love adding more layers :)

I'm happy with Erlang now because it feels much more designed for the 
task and it has a very interesting and practical mix of design decisions.

What you've described is not an isolated Ruby problem of course as the 
general trend is always towards more abstractions than less, but I guess 
its a little amplified in this particular eco system.

Coming back to what I initially wrote:

I agree with most of what you've written, I just came to a different 
conclusion which is basically giving up the constraint or desire to keep 
programming in Ruby. (But I'm still reading this mailing list ;) )

~ John

Eric Wong wrote:
> <rant>  Came across this in my feeds today:
> https://about.gitlab.com/2016/12/11/proposed-server-purchase-for-gitlab-com/
> ... Yeah, they cite 0.5 GB of memory usage per unicorn worker.
> I guess this is typical nowadays, but damn, it sucks :<
> This is not the future I had in mind or ever wanted unicorn to
> be associated with back in 2009 when I started.
> I don't think it's the fault of unicorn itself; unicorn recycles
> request buffers, uses pre-frozen hash keys, and even
> uses String#clear nowadays to discard heap memory, and never
> buffers more than it has to.
> Since day one, unicorn was built to handle multi-gigabyte
> uploads and responses; even from a crappy 256MB laptop.
> "curl -T-" is my co-pilot :)
> So... I guess the problem is up the stack in the app or
> framework.  Maybe Rails?  *shrug*  I don't use that anymore...
> I remember using Rails over a decade ago and being shocked at
> 50MB (yes, fifty megabytes) of RSS usage.  This was on 32-bit,
> but even in the worst case on 64-bit, it would be 100MB.
> Of course, nowadays Rails has grown to the point where I'm
> afraid to go near it; instead I work directly off Rack.
> And yes, I still freak out nowadays when my Rack processes
> exceed 100MB...
> So, what can and should we do about it?
> * First step: Limit ourselves.
>    Use slower, older hardware, slower Internet connection so you
>    force yourself to eke out every bit of performance out of
>    what you have.
>    It's utterly hilarious for me to hear about people complain
>    about laptops which can "only" have 16GB RAM.
>    I've definitely made transgressions in the past, and the worst
>    code I've written was on powerful hardware.
> Disclaimer: Some of the following may not be very Ruby-ish :P
> And everything else is optional and the result of the first step
> above.
> * Recycle.  Don't waste object slots: {Array,Hash,String}#clear
>    can allow you to recycle heap memory for large objects
>    and minimize GC pressure.  Using thread-local variables
>    in your app helps maintain compatibility with multi-threaded
>    Rack servers; or perhaps go Rack env-local for compatibility
>    with single-threaded non-blocking servers.
> * Can't recycle?  Discard objects you don't need, ASAP,
>    and continue #clear-ing what you can. Take advantage
>    of streaming built into Rack.
>    The Rack response body only needs to respond to #each.
>    There should be no reason to build giant response
>    documents in memory before sending them to a client.
>    unicorn can't do the following for you automatically since
>    we don't know how/if a Rack app will reuse a string;
>    but upstack authors can String#clear after yielding
>    in #each to ensure any malloced heap memory is immediately
>    available for future use (but beware of downstream middlewares
>    which do not expect this, too(**)):
>      def each
>        # .. do something to generate a giant string
>        yield giant_string
>        giant_string.clear # String#clear
>      end
>    A Rack response body may also respond to #close; it can
>    be used to explicitly release any response-local resources.
>    Rack::TempfileReaper + Rack::BodyProxy is an example of
>    this for Tempfiles.
>    Smaller functions and smaller code helps keep this manageable.
> * Avoid slurping.  Large datasets do not need everything up
>    front.  For example, threading 10K messages entirely
>    in memory is no problem: just don't load entire messages
>    into memory up front, only what you need.
>    JWZ's algorithm was doing this in the 90s:
>    https://www.jwz.org/doc/threading.html
> Disclaimer: Some of these things may hurt throughput and
> performance in benchmarks, especially with smaller datasets;
> but I consider predictable and consistent performance more
> far more important than burst throughput.
> ** Know your entire stack; top to bottom.
>     You ought to be able to track every single line of code
>     in a high-level Rack app you maintain down through each
>     and every layer of framework, middleware, Rack server,
>     Ruby VM, C library, down to the OS kernel.
>     Yes, this limits you to using smaller and simpler stacks :P
> *** Why stick with Ruby if you care about memory usage?
> I'm too impatient to wait on compilers, and don't like the extra
> storage of binaries.  Scripting languages forces authors to
> distribute (hopefully non-obfuscated) code; reducing network and
> storage costs, and that also lowers the barrier from user to
> hacker.  Fwiw, I actually prefer Perl5 with the predictability
> (and caveats of) refcounting over a GC like Ruby's.
> </rant>
> --
> unsubscribe: unicorn-public+unsubscribe@bogomips.org
> archive: https://bogomips.org/unicorn-public/

  parent reply	other threads:[~2016-12-12  9:49 UTC|newest]

Thread overview: 5+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2016-12-12  2:10 WTF is up with memory usage nowadays? Eric Wong
2016-12-12  4:05 ` Sam Saffron
2016-12-12  5:48   ` Eric Wong
2016-12-12  9:49 ` hukl [this message]
2017-02-08 20:00 ` Eric Wong

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