tornado.web ioloop add_timeout eats CPU


L

Laszlo Nagy

JavaScript clients (browsers) do long poll requests. Each request can
take up to 10 seconds before the server responds. On the server side,
every client has a queue of messages that needs to be sent to the
client. When the long poll request comes in, the server checks if there
are messages to be sent out. If there are no outgoing messages, then it
does not finish the response, but calls ioloop's add_timeout method for
doing further checks. After 10 seconds (if there are no new messages)
the server returns 304/not modified. If there is a message, then it is
sent back to the client as fast as possible, and the client comes back
with another long poll immediately.

These message queues are used for UI updates and also for instant
messaging. UI must be responsive. For this reason, any message in the
outgoing queue should be sent out to the client within 0.1 seconds.
Sometimes (rarely) lots of messages arrive quickly, and in those cases
it would be good to send them out even faster. What I did is that in the
first 0.1 seconds, I call add_timeout with 0.01 seconds. So if the
outgoing queue is full of messages, then they are delivered quickly.
After 0.1 seconds lapsed, add_timeout is called with 0.1 sec parameter.
So the server load is reduced because most clients are inactive, and
they are going to get callbacks in every 0.1 sec.

Here are the two most important methods of my request handler:

@tornado.web.asynchronous
def post(self):
"""Handle POST requests."""
# Disable caching
self.set_header("Cache-Control","no-cache, must-revalidate")
self.set_header("Expires","Mon, 26 Jul 1997 05:00:00 GMT")
self.poll_start = time.time()
action = self.get_argument("action")
if action=="poll":
self.poll()
elif action=="message":
self.process_incoming(self.get_argument("message"))
else:
self.set_status(400)
self.finish()

def poll(self):
"""Handle POLL request for the browser's message loop.

This method monitors the outgoing message queue, and sends
new messages to the browser when they come in (or until
self.poll_interval seconds elapsed)."""
poll_elapsed = time.time() - self.poll_start
if poll_elapsed<0.1:
poll_step = 0.01
else:
poll_step = 0.1
if poll_elapsed<self.poll_interval:
if self.session.outgoing:
msg = self.session.outgoing.pop()
self.write(msg)
self.finish()
else:
tornado.ioloop.IOLoop.instance().add_timeout(
time.time()+poll_step,self.poll)
else:
self.set_status(304)
self.finish()

And here is my problem. If I point 5 browsers to the server, then I get
2% CPU load (Intel i5 2.8GHz on amd64 Linux). But why? Most of the time,
the server should be sleeping. cProfile tells this:

ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 845.146 845.146 <string>:1(<module>)
1135775 832.283 0.001 832.283 0.001 {method 'poll' of
'select.epoll' objects}

I have copied out the two relevant rows only. As you can see, total
runtime was 845 seconds, and 832 seconds were spent in "epoll".
Apparently, CPU load goes up linearly as I connect more clients. It
means that 50 connected clients would do 20% CPU load. Which is
ridiculous, because they don't do anything but wait for messages to be
processed. Something terribly wrong, but I cannot figure out what?

Actually I could not try this with 50 clients. If I open 15 clients,
then the server starts dropping connections. (Tried from Firefox and
Chrome too.) If I change the poll() method this way:

else:
print "No messages after %.2f seconds"%poll_elapsed
self.set_status(304)
self.finish()

then I see this in the log:

No messages after 10.01 seconds
ERROR:root:Uncaught exception POST /client (127.0.0.1)
HTTPRequest(protocol='http', host='127.0.0.1:8888', method='POST',
uri='/client', version='HTTP/1.1', remote_ip='127.0.0.1',
body='_xsrf=df157469a62142d7b28c5a4880dd8478&action=poll',
headers={'Referer': 'http://127.0.0.1:8888/', 'Content-Length': '50',
'Accept-Language': 'en-us;q=0.8,en;q=0.5', 'Accept-Encoding': 'gzip,
deflate', 'Host': '127.0.0.1:8888', 'Accept': '*/*', 'User-Agent':
'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:15.0) Gecko/20100101
Firefox/15.0', 'Connection': 'keep-alive', 'X-Requested-With':
'XMLHttpRequest', 'Pragma': 'no-cache', 'Cache-Control': 'no-cache',
'Cookie':
'sid="MS1acHd5b3V1WHFOQU1BbTVmSXJEeVhkLys=|1346652787|e045d786fdb89b73220a2c77ef89572d0c16901e";
_xsrf=df157469a62142d7b28c5a4880dd8478;
xsfr=df157469a62142d7b28c5a4880dd8478', 'Content-Type':
'application/x-www-form-urlencoded; charset=UTF-8'})
Traceback (most recent call last):
File "/usr/lib/python2.7/dist-packages/tornado/stack_context.py",
line 183, in wrapped
callback(*args, **kwargs)
File "/home/gandalf/Python/Projects/test/client.py", line 67, in poll
self.finish()
File "/usr/lib/python2.7/dist-packages/tornado/web.py", line 641, in
finish
self.request.finish()
File "/usr/lib/python2.7/dist-packages/tornado/httpserver.py", line
411, in finish
self.connection.finish()
File "/usr/lib/python2.7/dist-packages/tornado/httpserver.py", line
186, in finish
self._finish_request()
File "/usr/lib/python2.7/dist-packages/tornado/httpserver.py", line
213, in _finish_request
self.stream.read_until(b("\r\n\r\n"), self._header_callback)
File "/usr/lib/python2.7/dist-packages/tornado/iostream.py", line
151, in read_until
self._check_closed()
File "/usr/lib/python2.7/dist-packages/tornado/iostream.py", line
493, in _check_closed
raise IOError("Stream is closed")
IOError: Stream is closed

What is even more interesting is that on the client side, Firebug tells
me that the connection was dropped after 15 seconds. The JavaScript
message loop is operated by a jQuery AJAX call, that has timeout=15000
parameter given:

<snip>
that.messageLoop = function () {
var xsfr = that.readCookie("xsfr");
$.ajax({
url: '/client',
type: "POST",
data: {"_xsrf":xsfr,"action":"poll"},
async: true,
cache: false,
timeout: 15000,
error: function (data) {
setTimeout( that.messageLoop , 1000);
console.log(data);
},
success: function (data) {
if (data) {
try {
eval(data);
}
catch(err) {
$().toastmessage('showErrorToast', err.message);
}
}
setTimeout( that.messageLoop , 10);
}
});
};
</snip>

But on the server side, I see that the connection was dropped after
10.01 seconds. If I start 20 clients, then about every second poll
request gets dropped.

Thanks,

Laszlo
 
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B

Bryan

Laszlo Nagy wrote:
[...]
And here is my problem. If I point 5 browsers to the server, then I get
2% CPU load (Intel i5 2.8GHz on amd64 Linux). But why? Most of the time,
the server should be sleeping. cProfile tells this:

ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 845.146 845.146 <string>:1(<module>)
1135775 832.283 0.001 832.283 0.001 {method 'poll' of
'select.epoll' objects}

I have copied out the two relevant rows only. As you can see, total
runtime was 845 seconds, and 832 seconds were spent in "epoll".
Apparently, CPU load goes up linearly as I connect more clients. It
means that 50 connected clients would do 20% CPU load. Which is
ridiculous, because they don't do anything but wait for messages to be
processed. Something terribly wrong, but I cannot figure out what?

What's wrong is the 1,135,775 calls to "method 'poll' of
'select.epoll' objects".
With five browsers waiting for messages over 845 seconds, that works
out to each waiting browser inducing 269 epolls per second.

Almost equally important is what the problem is *not*. The problem is
*not* spending the vast majority of time in epoll; that's *good* news.
The problem is *not* that CPU load goes up linearly as we connect more
clients. This is an efficiency problem, not a scaling problem.

So what's the fix? I'm not a Tornado user; I don't have a patch.
Obviously Laszlo's polling strategy is not performing, and the
solution is to adopt the event-driven approach that epoll and Tornado
do well.

-Bryan
 
L

Laszlo Nagy

What's wrong is the 1,135,775 calls to "method 'poll' of
'select.epoll' objects".
I was affraid you are going to say that. :)
With five browsers waiting for messages over 845 seconds, that works
out to each waiting browser inducing 269 epolls per second.

Almost equally important is what the problem is *not*. The problem is
*not* spending the vast majority of time in epoll; that's *good* news.
The problem is *not* that CPU load goes up linearly as we connect more
clients. This is an efficiency problem, not a scaling problem.

So what's the fix? I'm not a Tornado user; I don't have a patch.
Obviously Laszlo's polling strategy is not performing, and the
solution is to adopt the event-driven approach that epoll and Tornado
do well.
Actually, I have found a way to overcome this problem, and it seems to
be working. Instead of calling add_timeout from every request, I save
the request objects in a list, and operate a "message distributor"
service in the background that routes messages to clients, and finish
their long poll requests when needed. The main point is that the
"message distributor" has a single entry point, and it is called back at
given intervals. So the number of callbacks per second does not increase
with the number of clients. Now the CPU load is about 1% with one
client, and it is the same with 15 clients. While the response time is
the same (50-100msec). It is efficient enough for me.

I understand that most people do a different approach: they do a fast
poll request from the browser in every 2 seconds or so. But this is not
good for me, because then it can take 2 seconds to send a message from
one browser into another that is not acceptable in my case. Implementing
long polls with a threaded server would be trivial, but a threaded
server cannot handle 100+ simultaneous (long running) requests, because
that would require 100+ threads to be running.

This central "message distributor" concept seems to be working. About
1-2% CPU overhead I have to pay for being able to send messages from one
browser into another within 100msec, which is fine.

I could have not done this without your help.

Thank you!

Laszlo
 
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P

Paul Rubin

Laszlo Nagy said:
but a threaded server cannot handle 100+ simultaneous (long running)
requests, because that would require 100+ threads to be running.

On a reasonable server these days, 100 threads seems to be no big deal.
I've run several times that many. I think things get ragged at a few
thousand threads.
 

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