Unclog the tubes; blocking detection in Eventlet 28 Aug 2010
software development python

Colleagues of mine are all very familiar with my admiration of Eventlet, a Python concurrency library, built on top of greenlet, that provides lightweight “greenthreads” that naturally yield around I/O points. For me, the biggest draw of Eventlet besides its maturity, is how well it integrates with standard Python code. Any code that uses the built-in socket module can be “monkey-patched” (i.e. modified at runtime) to use the “green” version of the socket module which allows Eventlet to turn regular ol’ Python into code with asynchronous I/O.

The problem with using libraries like Eventlet, is that some Python code just blocks, meaning that code will hit an I/O point and not yield but instead block the entire process until that network operation completes.

In practical terms, imagine you have a web crawler that uses 10 “green threads”, each crawling a different site. The first greenthread (GT1) will send an HTTP request to the first site, then it will yield to GT2 and so on. If each HTTP request blocks for 100ms, that means when crawling the 10 sites, you’re going to block the whole process, preventing anything from running, for a whole second. Doesn’t sound too terrible, but imagine you’ve got 1000 greenthreads, instead of everything smoothly yielding from one thread to another the process will lock up very often resulting in painful slowdowns.

Starting with Eventlet 0.9.10 “blocking detection” code has been incorporated into Eventlet to make it far easier for developers to find these portions of code that can block the entire process. import eventlet.debug eventlet.debug.hub_blocking_detection(True)

While using the blocking detection is fairly simple, its implementation is a bit “magical” in that it’s not entirely obvious how it works. The detector is built around signals, inside of Eventlet a signal handler is set up prior to firing some code and then after said code has executed, if a certain time-threshhold has passed, an alarm is raised dumping a stack trace to the console. I’m not entirely convinced I’m explaining this appropriately so here’s some pseudo-code:

def runloop(): while True: signal.alarm(handler, 1) execute_next_block() if (time.time() - start) < resolution: clear_signal() # Clear the signal if we're less than a second, otherwise it will alarm

The blocking detection is a bit crude and can raise false positives if you have bits of code that churn the CPU for longer than a second but it has been instrumental in incorporating non-blocking DNS support into Eventlet, which was also introduced in 0.9.10 (ported over from Slide’s gogreen package).

If you are using Eventlet, I highly recommend running your code periodically with blocking detection enabled, it is an invaluable tool for determining whether you’re running as fast and as asynchronous as possible. In my case, it has been the difference between web services that are fast in development but slow under heavy stress, and web services that are fast always regardless of load.