Python Flask Gevent 堆栈 - 简单的 "Hello World"应用程序在进行基准测试时显示效率低下

Question

我有以下简单的“Hello World”应用程序:

from gevent import monkey
monkey.patch_all()
from flask import Flask
from gevent import wsgi

app = Flask(__name__)

@app.route('/')
def index():
  return 'Hello World'

server = wsgi.WSGIServer(('127.0.0.1', 5000), app)
server.serve_forever()

如您所见，它非常简单。

问题是，尽管如此简单，但它仍然非常缓慢/效率低下，如下面的基准测试(使用 Apache Benchmark 制作)所示:

ab -k -n 1000 -c 100 http://127.0.0.1:5000/

Benchmarking 127.0.0.1 (be patient)
Completed 100 requests
Completed 200 requests
Completed 300 requests
Completed 400 requests
Completed 500 requests
Completed 600 requests
Completed 700 requests
Completed 800 requests
Completed 900 requests
Completed 1000 requests
Finished 1000 requests


Server Software:        
Server Hostname:        127.0.0.1
Server Port:            5000

Document Path:          /
Document Length:        11 bytes

Concurrency Level:      100
Time taken for tests:   1.515 seconds
Complete requests:      1000
Failed requests:        0
Write errors:           0
Keep-Alive requests:    0
Total transferred:      146000 bytes
HTML transferred:       11000 bytes
Requests per second:    660.22 [#/sec] (mean)
Time per request:       151.465 [ms] (mean)
Time per request:       1.515 [ms] (mean, across all concurrent requests)
Transfer rate:          94.13 [Kbytes/sec] received

Connection Times (ms)
              min  mean[+/-sd] median   max
Connect:        0    0   0.6      0       3
Processing:     1  145  33.5    149     191
Waiting:        1  144  33.5    148     191
Total:          4  145  33.0    149     191

Percentage of the requests served within a certain time (ms)
  50%    149
  66%    157
  75%    165
  80%    173
  90%    183
  95%    185
  98%    187
  99%    188
 100%    191 (longest request)

最终增加连接数和/或并发数并没有带来更好的结果，实际上它变得更糟。

我最担心的是我无法处理超过 700 个每秒请求 和 98 KB/秒的传输速率。

此外，单个每个请求的时间似乎太多了。

我很好奇 Python 和 Gevent 在后台做什么，或者更好的是，操作系统在做什么，所以我使用 strace 来确定最终的系统端问题，结果如下:

% time     seconds  usecs/call     calls    errors syscall
------ ----------- ----------- --------- --------- ----------------
 56.46    0.000284           0      1386           close
 24.25    0.000122           0      1016           write
 10.74    0.000054           0      1000           send
  4.17    0.000021           0      3652      3271 open
  2.19    0.000011           0       641           read
  2.19    0.000011           0      6006           fcntl64
  0.00    0.000000           0         1           waitpid
  0.00    0.000000           0         1           execve
  0.00    0.000000           0         3           time
  0.00    0.000000           0        12        12 access
  0.00    0.000000           0        32           brk
  0.00    0.000000           0         5         1 ioctl
  0.00    0.000000           0      5006           gettimeofday
  0.00    0.000000           0         4         2 readlink
  0.00    0.000000           0       191           munmap
  0.00    0.000000           0         1         1 statfs
  0.00    0.000000           0         1         1 sigreturn
  0.00    0.000000           0         2           clone
  0.00    0.000000           0         2           uname
  0.00    0.000000           0        21           mprotect
  0.00    0.000000           0        69        65 _llseek
  0.00    0.000000           0        71           rt_sigaction
  0.00    0.000000           0         1           rt_sigprocmask
  0.00    0.000000           0         3           getcwd
  0.00    0.000000           0         1           getrlimit
  0.00    0.000000           0       243           mmap2
  0.00    0.000000           0      1838       748 stat64
  0.00    0.000000           0        74           lstat64
  0.00    0.000000           0       630           fstat64
  0.00    0.000000           0         1           getuid32
  0.00    0.000000           0         1           getgid32
  0.00    0.000000           0         1           geteuid32
  0.00    0.000000           0         1           getegid32
  0.00    0.000000           0         4           getdents64
  0.00    0.000000           0         3         1 futex
  0.00    0.000000           0         1           set_thread_area
  0.00    0.000000           0         2           epoll_ctl
  0.00    0.000000           0        12         1 epoll_wait
  0.00    0.000000           0         1           set_tid_address
  0.00    0.000000           0        26           clock_gettime
  0.00    0.000000           0         2           openat
  0.00    0.000000           0         1           set_robust_list
  0.00    0.000000           0         1           eventfd2
  0.00    0.000000           0         1           epoll_create1
  0.00    0.000000           0         1           pipe2
  0.00    0.000000           0         1           socket
  0.00    0.000000           0         1           bind
  0.00    0.000000           0         1           listen
  0.00    0.000000           0      1000           accept
  0.00    0.000000           0         1           getsockname
  0.00    0.000000           0      2000      1000 recv
  0.00    0.000000           0         1           setsockopt
------ ----------- ----------- --------- --------- ----------------
100.00    0.000503                 24977      5103 total

如您所见，有 5103 个错误，最严重的问题是 open syscall，我怀疑这与找不到文件有关 (ENOENT )。令我惊讶的是，epoll 看起来不像是一个麻烦，因为我听说过很多关于它的恐怖故事。

我希望发布完整的 strace，其中包含每个调用的详细信息，但它太大了。

最后一点；我还设置了以下系统参数(这是允许的最大数量)，希望它能改变这种情况，但事实并非如此:

echo “32768 61000″ > /proc/sys/net/ipv4/ip_local_port_range
sysctl -w fs.file-max=128000
sysctl -w net.ipv4.tcp_keepalive_time=300
sysctl -w net.core.somaxconn=61000
sysctl -w net.ipv4.tcp_max_syn_backlog=2500
sysctl -w net.core.netdev_max_backlog=2500
ulimit -n 1024

我的问题是，考虑到我使用的示例无法更改太多来解决这些问题，我应该去哪里纠正它们？

更新我用 Wheezy.web 和 Gevent 制作了以下“Hello World”脚本，每秒收到约 2000 个请求:

from gevent import monkey
monkey.patch_all()
from gevent import pywsgi
from wheezy.http import HTTPResponse
from wheezy.http import WSGIApplication
from wheezy.routing import url
from wheezy.web.handlers import BaseHandler
from wheezy.web.middleware import bootstrap_defaults
from wheezy.web.middleware import path_routing_middleware_factory

def helloworld(request):
    response = HTTPResponse()
    response.write('hello world')
    return response


routes = [
    url('hello', helloworld, name='helloworld')
]


options = {}
main = WSGIApplication(
    middleware=[
        bootstrap_defaults(url_mapping=routes),
        path_routing_middleware_factory
    ],
    options=options
)


server = pywsgi.WSGIServer(('127.0.0.1', 5000), main, backlog=128000)
server.serve_forever()

基准测试结果:

ab -k -n 1000 -c 1000 http://127.0.0.1:5000/hello

Benchmarking 127.0.0.1 (be patient)
Completed 100 requests
Completed 200 requests
Completed 300 requests
Completed 400 requests
Completed 500 requests
Completed 600 requests
Completed 700 requests
Completed 800 requests
Completed 900 requests
Completed 1000 requests
Finished 1000 requests


Server Software:        
Server Hostname:        127.0.0.1
Server Port:            5000

Document Path:          /front
Document Length:        11 bytes

Concurrency Level:      1000
Time taken for tests:   0.484 seconds
Complete requests:      1000
Failed requests:        0
Write errors:           0
Keep-Alive requests:    0
Total transferred:      170000 bytes
HTML transferred:       11000 bytes
Requests per second:    2067.15 [#/sec] (mean)
Time per request:       483.758 [ms] (mean)
Time per request:       0.484 [ms] (mean, across all concurrent requests)
Transfer rate:          343.18 [Kbytes/sec] received

Connection Times (ms)
              min  mean[+/-sd] median   max
Connect:        0    8  10.9      0      28
Processing:     2   78  39.7     56     263
Waiting:        2   78  39.7     56     263
Total:         18   86  42.6     66     263

Percentage of the requests served within a certain time (ms)
  50%     66
  66%     83
  75%    129
  80%    131
  90%    152
  95%    160
  98%    178
  99%    182
 100%    263 (longest request)

我发现 Wheezy.web 的速度很快，但我仍然喜欢使用 Flask，因为它更简单，使用起来更省时。

Answer 1

您使用的是什么 gevent 版本？尝试将您的软件堆栈简化到最低限度，并尝试他们在他们的 github 上的示例。

https://github.com/gevent/gevent/blob/master/examples/wsgiserver.py

您是否将基准测试与非 gevent 版本进行了比较？我已经使用这个库获得了显着的加速，所以我会进一步调查。