概述
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", "192.20.150.110", "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"] 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。
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