I agree with you, with a caveat. I think that the model is better for some specific use cases.
_ry and I had this debate at reasonable length back before node, when he was writing flow and I prepped the first thin async patch/rack hack.
The fundamental problem here is a competition of use cases and ideals. It would be ideal for server authors if Ruby had lightweight coroutines that could be scheduled across threads and relinquish control on IO. You can emulate some of this with Fibers, and Neverblock went really far down this path, as did Goliath. There's really no substitute for real user schedulable goroutines and a decent IO subsystem though - we can build the latter, but the prior is squarely in MRI's control - and they're now headed further down the path of thread isolation.
Skipping a very large background and diatribe of these choices in MRI, I will say that the chosen path is really not suitable for very high scale processes. To be clear, I'm not saying "ruby doesn't scale" in the sense that we can't use it for services that handle Mqps and up. You can - it's not cheap, but it's entirely doable, and the engineering cost is on par with other choices, assuming reasonable problem solving. What I am saying is that Ruby, as designed and where it is headed, will not be ideal for tens of thousands of open sockets, or more. It does not have enough lightweight datastructures. It doesn't have the right IO primitives, and it doesn't have the right concurrency primitives. The newer concurrency primitives that are being discussed also make solving the general case of this problem harder. The general case assumes that task latencies are unpredictable, and in that space, you need a scheduler that can perform memory and cpu offloading. MRI will not deliver either of those capabilities.
The reason I describe the above, is that if we accept that Ruby is only good for limited scale and cost per process, then we can view the problem a little differently. Instead of trying to force it, or constantly work around those limitations in library level systems, we can work around the problem in flow control and traffic management systems. Indeed this is what we do today, though as you note, often by accident/side effect. The kinds of catastrophic load balancing challenges such as the rap genius saga will remain, and slow client challenges will also. We can deal with them. At scale you never really get to escape these anyway, except by engineering systems to specifically combat those challenges. Either you're so fast and efficient that attacks are impractical, or you start needing to put appropriate limitations in place in upstream defenses. Ultimately the prior is brittle and as such the latter eventually gets deployed by SRE/sysadmins/ops folks.
I also don't mean to say that it would be bad to explore some more of these ideas. I think it would, particularly if it could lead to more examples of what servers need in order to be efficient, as strong cases for MRI/Ruby designers to consider. I also think there are good cases to be made for alternative servers for specific use cases - I know you specifically Eric have done great work in this area. I would encourage you, absolutely, to freely depart from Rack for those use cases. I'd also be really happy to eat my words if you find some way of taking on elixir style scalability with MRI, though on a personal level I don't know if it's worth the time. As always, thank you for everything you've done, and for the discussion.
I've been poking around in Plack/PSGI for Perl5 some months,
and am liking it in some ways more than Rack.
This only covers server-agnostic web applications; IMHO exposing
applications to server-specific stuff defeats the purpose of
these common specs.
In Rack, one major problem I have is streaming large responses
requires calling body.each synchronously.
For handling writing large responses to slow clients, this means
a Rack web server has 2 choices:
1) Block the calling Thread, Fiber, or process until the
slow client can consume the input. This hurts if you have
many slow clients blocking all your threads.
body.each { |buf| client.write(buf) }
body.close
Simple, but your app is at the mercy of how fast the client
chooses to read the response.
2) Detect :wait_writable/:wait_readable (EAGAIN) when writing to
the slow client and start buffering the response to memory or
filesystem.
This may lead to out-of-memory or out-of-storage conditions.
nginx does this by default when proxying, so Rubyists are
often unaware of this as it's common to use nginx in front
of Rack servers for this purpose.
Something like the following should handle slow clients
without relying on nginx for buffering:
tmp = nil
body.each do |buf|
if tmp
tmp.write(buf)
else
# the optimistic case:
case ret = client.write_nonblock(buf, exception: false)
when :wait_writable, :wait_writable # EAGAIN :<
tmp = Tempfile.new(ret.to_s)
tmp.write(buf)
when Integer
exp = buf.bytesize
if exp > ret # partial write :<
tmp = Tempfile.new('partial')
tmp.write(buf.byteslice(ret, exp - ret))
end
end
end
end
if tmp
server_specific_finish(client, tmp, body)
else
body.close if body.respond_to?(:close)
end
Gross; but smaller responses never get buffered this way.
Any server-specific logic is still contained within the
server itself, the Rack app may remain completely unaware
of how a server handles slow clients.
PSGI allows at least two methods for streaming large responses.
I will only cover the "pull" method of getline+close below.
Naively, getline+close is usable like the Rack method 1) for
body.each:
# Note: "getline" in Plack/PSGI is not required to return
# a "line", so it can behave like "readpartial" in Ruby.
while (defined(my $buf = $body->getline)) {
$client->write($buf);
}
$body->close;
...With all the problems of blocking on the $client->write call.
On the surface, the difference between Rack and PSGI here is
minor.
However, "getline" yielding control to the server entirely has a
significant advantage over the Rack app calling a Proc provided
by the server: The server can stop calling $body->getline once
it detects a client is slow.
# For the non-Perl-literate, it's pretty similar to Ruby.
# Scalar variables are prefixed with $, and method.
# calls are "$foo->METHOD" instead of "foo.METHOD" in Ruby
# if/else/elsif/while all work the same as in Ruby
# I will over-comment here assuming readers here are not
# familiar with Perl.
# Make client socking non-blocking, equivalent to
# "IO#nonblock = true" in Ruby; normal servers would only
# call this once after accept()-ing a connection.
$client->blocking(0);
my $blocked; # "my" declares a locally-scoped variable
# "undef" in Perl are the equivalent of "nil" in Ruby,
# so "defined" checks here are equivalent to Ruby nil checks
while (defined(my $buf = $body->getline)) {
# length($buf) is roughly buf.bytesize in Ruby;
# I'll assume all data is binary since Perl's Unicode
# handling confuses me no matter how many times I RTFM.
my $exp = length($buf);
# Behaves like Ruby IO#write_nonblock after the
# $client->blocking(0) call above:
my $ret = $client->syswrite($buf);
# $ret is the number of bytes written on success:
if (defined $ret) {
if ($exp > $ret) { # partial write :<
# similar to String#byteslice in Ruby:
$blocked = substr($buf, $ret, $exp - $ret);
last; # break out of the while loop
} # else { continue looping on while }
# $! is the system errno from syswrite (see perlvar manpage
# for details), $!{E****} just checks for $! matching the
# particular error number.
} elsif ($!{EAGAIN} || $!{EWOULDBLOCK}) {
# A minor detail in this example:
# this assignment is a copy, so equivalent to
# "blocked = buf.dup" in Ruby, NOT merely
# "blocked = buf".
$blocked = $buf;
last; # break out of the while loop
} else {
# Perl does not raise exceptions by default on
# syscall errors, "die" is the standard exception
# throwing mechanism:
die "syswrite failed: $!\n";
}
}
if (defined $blocked) {
server_specific_finish($client, $blocked, $body);
} else {
$body->close;
}
In both my Rack and PSGI examples, I have a reference to a
server_specific_finish call. In the Rack example, this method
will stream the entire contents of tmp (a Tempfile) to the
client.
The problem is tmp in the Rack example may be as large as
the entire response. This sucks for big responses.
In the PSGI example, the server_specific_finish call will only
have the contents of one buffer from $body->getline in memory at
a time. The server will make further calls to $body->getline
when (and only when) the previous buffer is fully-written to the
client socket. There is only one (app-provided) buffer in
server memory at once, not entire response.
Both server_specific_finish calls will call the "close" method
on the body when the entire response is written to the client
socket. Delaying the "close" call may make sense for logging
purposes in Rack, even if body.each is long done running, and is
obviously required in the PSGI case since further "getline"
calls need to be made before "close".
The key difference is that in Rack, the data is "pushed" to the
server by the Rack app. In PSGI, the app may instead ask the
server to "pull" that data.
Anyways, thanks for reading this far. I just felt like writing
something down for future Rack/Ruby-related projects. I'm not
sure if Rack can change without breaking all existing apps
and middlewares.
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