The Paste HTTP Server Thread Pool¶
This document describes how the thread pool in
works, and how it can adapt to problems.
Note all of the configuration parameters listed here are prefixed with
threadpool_ when running through a Paste Deploy configuration.
When a WSGI application is called, it’s possible that it will block indefinitely. There’s two basic ways you can manage threads:
- Start a thread on every request, close it down when the thread stops
- Start a pool of threads, and reuse those threads for subsequent requests
In both cases things go wrong – if you start a thread every request you will have an explosion of threads, and with it memory and a loss of performance. This can culminate in really high loads, swapping, and the whole site grinds to a halt.
If you are using a pool of threads, all the threads can simply be used up. New requests go into a queue to be processed, but since that queue never moves forward everyone will just block. The site basically freezes, though memory usage doesn’t generally get worse.
Paste Thread Pool¶
The thread pool in Paste has some options to walk the razor’s edge between the two techniques, and to try to respond usefully in most cases.
The pool tracks all workers threads. Threads can be in a few states:
- Idle, waiting for a request (“idle”)
- Working on a request
- For a reasonable amount of time (“busy”)
- For an unreasonably long amount of time (“hung”)
- Thread that should die
- An exception has been injected that should kill the thread, but it hasn’t happened yet (“dying”)
- An exception has been injected, but the thread has persisted for an unreasonable amount of time (“zombie”)
When a request comes in, if there are no idle worker threads waiting
then the server looks at the workers; all workers are busy or hung.
If too many are hung, another thread is opened up. The limit is if
there are less than
spawn_if_under busy threads. So if you have
spawn_if_under is 5, and there are 6 hung threads and
4 busy threads, another thread will be opened (bringing the number of
busy threads back to 5). Later those threads may be collected again
if some of the threads become un-hung. A thread is hung if it has
been working for longer than
hung_thread_limit (default 30
Every so often, the server will check all the threads for error
conditions. This happens every
(default 100). At this time if there are more than enough threads
spawn_if_under) some threads may be collected. If any
threads have been working for longer than
(default 1800 seconds, i.e., 30 minutes) then the thread will be
To kill a thread the
ctypes module must be installed. This will
raise an exception (
SystemExit) in the thread, which should cause
the thread to stop. It can take quite a while for this to actually
take effect, sometimes on the order of several minutes. This uses a
non-public API (hence the
ctypes requirement), and so it might not
work in all cases. I’ve tried it in pure Python code and with a hung
socket, and in both cases it worked. As soon as the thread is killed
(before it is actually dead) another worker is added to the pool.
If the killed thread lives longer than
300 seconds, 5 minutes) then it is considered a zombie.
Zombie threads are not handled specially unless you set
max_zombies_before_die. If you set this and there are more than
this many zombie threads, then the entire process will be killed.
This is useful if you are running the server under some process
monitor, such as
paster serve --monitor. To make the process die, it may run
os._exit, which is considered an impolite way to exit a process
kill -9). It will try to run the functions registered
atexit (except for the thread cleanup functions, which are
the ones which will block so long as there are living threads).
If you set
error_email (including setting it globally in a Paste
[DEFAULT] section) then you will be notified of two error
conditions: when hung threads are killed, and when the process is
killed due to too many zombie threads.
If you have a worker pool size of 10, and 11 slow or hung requests
come in, the first 10 will get handed off but the server won’t know
yet that they will hang. The last request will stay stuck in a queue
until another request comes in. When a later request comes later
hung_thread_limit seconds) the server will notice the
problem and add more threads, and the 11th request will come through.
If a trickle of bad requests keeps coming in, the number of hung
threads will keep increasing. At 100 the
not clean them up fast enough.
Killing threads is not something Python really supports. Corruption
of the process, memory leaks, or who knows what might occur. For the
most part the threads seem to be killed in a fairly simple manner –
an exception is raised, and
finally blocks do get executed. But
this hasn’t been tried much in production, so there’s not much
experience with it.
If you want to see what’s going on in your process, you can install
egg:Paste#watch_threads (in the
paste.debug.watchthreads module). This lets you see requests and
how long they have been running. In Python 2.5 you can see tracebacks
of the running requests; before that you can only see request data
(URLs, User-Agent, etc). If you set
allow_kill = true then you
can also kill threads from the application. The thread pool is
intended to run reliably without intervention, but this can help debug
problems or give you some feeling of what causes problems in the site.
This does open up privacy problems, as it gives you access to all the request data in the site, including cookies, IP addresses, etc. It shouldn’t be left on in a public setting.
The HTTP server (not the thread pool) also accepts an argument
socket_timeout. It is turned off by default. You might find it
helpful to turn it on.