epoll's Introduction

epoll

Epoll examples and benchmarks

Description:

Simple epoll based HTTP servers with constant JSON response to any request.
It's possible to make and run examples on your system as well as in Docker.

To run C version in the Docker container use the next commands:

# cd c/
# docker build -f Dockerfile_C -t epoll .
# docker run --net=host -p 8000:8000 -t epoll

After that you'll see the next output:

Successfully tagged epoll:latest
Server listening on 0.0.0.0:8000

For benchmarks wrk tool was used.

NB: Even with --net=host key in docker run command the performance of examples on a host system is better than in the Docker.

Results:

To test I've used the next wrk confuguration: 2 threads, 100 clients and 10 seconds.
Tested epoll servers were run in Docker, whereas wrk was on the host system (Ubuntu 16.04).

C (threaded_loop (2 threads)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  77176.69

=============================================

CPython3 (multiprocessed_loop (2 processes)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  48215.67

CPython3 (threaded_loop (2 threads)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  29849.85

=============================================

PyPy3 (multiprocessed_loop (2 processes)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  76399.70

PyPy3 (threaded_loop (2 threads)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  74526.86

=============================================

Go (ConcurrentLoop (2 threads)):
$ wrk -t2 -c100 -d10s http://0.0.0.0:8000/
Requests/sec:  76362.73

It's interesting that PyPy3 performance is close to C.