python & snmp
用python获取snmp信息有多个现成的库可以使用,其中比较常用的是netsnmp
和pysnmp
两个库。网上有较多的关于两个库的例子。
本文重点在于如何并发的获取snmp的数据,即同时获取多台机器的snmp信息。
netsnmp
先说netsnmp。python的netsnmp,其实是来自于net-snmp包。
python通过一个c文件调用net-snmp的接口获取数据。
因此,在并发获取多台机器的时候,不能够使用协程获取。因为使用协程,在get数据的时候,协程会一直等待net-snmp接口返回数据,而不会像socket使用时那样在等待数据时把cpu切换给其他协程使用。从这点上来说,使用协程和串行获取没有区别。
那么如何解决并发获取的问题呢?可以使用线程,多线程获取(当然也可以使用多进程)。多个线程同时调用net-snmp的接口获取数据,然后cpu在多个线程之间不停切换。当一个线程获取一个结果后,可以继续调用接口获取下一个snmp数据。
这里我写了一个样例程序。首先把所有的host和oid做成任务放到队列里,然后启动多个线程,去执行获取任务。程序样例如下:
import threading import time import netsnmp import Queue start_time = time.time() hosts = ["192.20.150.109","192.20.150.110","192.20.150.111","192.20.150.112","192.20.150.113","192.20.150.114","192.20.150.115","192.20.150.116","192.20.150.117","192.20.150.118","192.20.150.119","192.20.150.120","192.20.150.121","192.20.80.148","192.20.80.149","192.20.96.59","192.20.82.14","192.20.82.15","192.20.82.17","192.20.82.19","192.20.82.12","192.20.80.139","192.20.80.137","192.20.80.136","192.20.80.134","192.20.80.133","192.20.80.131","192.20.80.130","192.20.81.141","192.20.81.140","192.20.82.26","192.20.82.28","192.20.82.23","192.20.82.21","192.20.80.128","192.20.80.127","192.20.80.122","192.20.81.159","192.20.80.121","192.20.80.124","192.20.81.151","192.20.80.118","192.20.80.119","192.20.80.113","192.20.80.112","192.20.80.116","192.20.80.115","192.20.78.62","192.20.81.124","192.20.81.125","192.20.81.122","192.20.81.121","192.20.82.33","192.20.82.31","192.20.82.32","192.20.82.30","192.20.81.128","192.20.82.39","192.20.82.37","192.20.82.35","192.20.81.130","192.20.80.200","192.20.81.136","192.20.81.137","192.20.81.131","192.20.81.133","192.20.81.134","192.20.82.43","192.20.82.45","192.20.82.41","192.20.79.152","192.20.79.155","192.20.79.154","192.25.76.235","192.25.76.234","192.25.76.233","192.25.76.232","192.25.76.231","192.25.76.228","192.25.20.96","192.25.20.95","192.25.20.94","192.25.20.93","192.24.163.14","192.24.163.21","192.24.163.29","192.24.163.6","192.18.136.22","192.18.136.23","192.24.193.2","192.24.193.19","192.24.193.18","192.24.193.11","192.20.157.132","192.20.157.133","192.24.212.232","192.24.212.231","192.24.212.230"] oids = [".1.3.6.1.4.1.2021.11.9.0",".1.3.6.1.4.1.2021.11.10.0",".1.3.6.1.4.1.2021.11.11.0",".1.3.6.1.4.1.2021.10.1.3.1",".1.3.6.1.4.1.2021.10.1.3.2",".1.3.6.1.4.1.2021.10.1.3.3",".1.3.6.1.4.1.2021.4.6.0",".1.3.6.1.4.1.2021.4.14.0",".1.3.6.1.4.1.2021.4.15.0"] myq = Queue.Queue() rq = Queue.Queue() #把host和oid组成任务 for host in hosts: for oid in oids: myq.put((host,oid)) def poll_one_host(): while True: try: #死循环从队列中获取任务,直到队列任务为空 host,oid = myq.get(block=False) session = netsnmp.Session(Version=2,DestHost=host,Community="cluster",Timeout=3000000,Retries=0) var_list = netsnmp.VarList() var_list.append(netsnmp.Varbind(oid)) ret = session.get(var_list) rq.put((host,oid,ret,(time.time() - start_time))) except Queue.Empty: break thread_arr = [] #开启多线程 num_thread = 50 for i in range(num_thread): t = threading.Thread(target=poll_one_host,kwargs={}) t.setDaemon(True) t.start() thread_arr.append(t) #等待任务执行完毕 for i in range(num_thread): thread_arr[i].join() while True: try: info = rq.get(block=False) print info except Queue.Empty: print time.time() - start_time break
netsnmp除了支持get操作之外,还支持walk操作,即遍历某个oid。
但是walk使用的时候需要谨慎,以免导致高延时等问题,具体可以参见之前的一篇snmpwalk高延时问题分析的博客。
pysnmp
pysnmp是用python实现的一套snmp协议的库。其自身提供了对于异步的支持。
import time import Queue from pysnmp.hlapi.asyncore import * t = time.time() myq = Queue.Queue() #回调函数。在有数据返回时触发 def cbFun(snmpEngine,sendRequestHandle,errorIndication,errorStatus,errorIndex,varBinds,cbCtx): myq.put((time.time()-t,varBinds)) hosts = ["192.20.150.109","192.24.212.230"] oids = [".1.3.6.1.4.1.2021.11.9.0",".1.3.6.1.4.1.2021.4.15.0"] snmpEngine = SnmpEngine() #添加任务 for oid in oids: for h in hosts: getCmd(snmpEngine,CommunityData('cluster'),UdpTransportTarget((h,161),timeout=3,retries=0,),ContextData(),ObjectType(ObjectIdentity(oid)),cbFun=cbFun) time1 = time.time() - t #执行异步获取snmp snmpEngine.transportdispatcher.rundispatcher() #打印结果 while True: try: info = myq.get(block=False) print info except Queue.Empty: print time1 print time.time() - t break
pysnmp本身只支持最基础的get和getnext命令,因此如果想使用walk,需要自己进行实现。
性能测试
在同一个环境下,对两者进行了性能测试。两者对198个host,10个oid进行采集。
测试组 | 耗时(sec) |
---|---|
netsnmp(20线程) | 6.252 |
netsnmp(50线程) | 3.269 |
netsnmp(200线程) | 3.265 |
pysnmp | 4.812 |
可以看到netsnmp的采集速度跟线程数有关。当线程数增大到一定程度,采集时间不再缩短。因为开辟线程同样会消耗时间。而已有的线程已经足够处理。
pysnmp性能较之略差一下。详细分析pysnmp在添加任务(执行getCmd时)消耗了约1.2s,之后的采集约消耗3.3秒。
在增加了oid数,在进行实验。host仍然是198个,oid是42个。
测试组 | 耗时(sec) |
---|---|
netsnmp(20线程) | 30.935 |
netsnmp(50线程) | 12.914 |
netsnmp(200线程) | 4.044 |
pysnmp | 11.043 |
可以看到差距被进一步拉大。在线程足够多的情况下,netsnmp的效率要明显强于pysnmp。
因为二者都支持可以并行采集多个host,从易用性来说,netsnmp更为简单一些,且netsnmp支持walk功能。本文更加推荐netsnmp。
安装netsnmp需要安装net-snmp。如果centos,则使用yum会较为方便。
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持编程小技巧。
版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 dio@foxmail.com 举报,一经查实,本站将立刻删除。