实现混杂模式下HTTP包网址计数监控工具

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资源摘要信息:"count_web_v1.00.rar_包 网址" 在IT领域,"count_web_v1.00.rar_包 网址"这一资源描述涉及到了网络抓包分析和数据计数的应用。首先,"rar"是WinRAR压缩文件的扩展名,表明这是一个压缩文件包,而标题中"包 网址"则指出了文件包的用途可能与分析网络包以及网址相关。接着,根据描述"混杂模式下抓包,滤取HTTP包,相同网址计数+1,实现网关监视",可以提炼出以下几个关键知识点: 1. 网络抓包(Packet Sniffing):这是一种网络安全工具,用于捕获网络上流经的数据包。通过抓包,我们可以查看详细的网络流量信息,包括数据包的来源、目的地、传输协议以及内容等。抓包工具有Wireshark、tcpdump等,它们可以在网络的任何节点上运行,以管理员权限抓取经过该节点的数据包。 2. 混杂模式(Promiscuous Mode):当网络接口卡(NIC)设置为混杂模式时,它将接收所有经过网络媒介的数据包,而不考虑目标地址是否为该卡本身。这在网络安全和故障排查中非常有用,因为它允许抓包工具捕获所有网络流量,而不仅仅是发往或来自本机的数据。 3. 过滤HTTP包(Filtering HTTP Packets):网络抓包工具允许用户设置过滤条件来筛选特定类型的数据包。在本例中,过滤条件是针对HTTP协议的数据包。HTTP包是应用层协议,通常用于网页浏览、数据传输等。过滤HTTP包的目的是为了专注于分析与网址相关的网络活动。 4. 网址计数(Website Traffic Counting):通过对捕获的HTTP包中的网址进行分析,并对出现的相同网址进行计数,可以得出特定网站或页面的访问次数。这可以用于监控网站的访问量,分析用户行为,或用于计费等商业用途。 5. 网关监视(Gateway Monitoring):网关是网络的入口点,所有的网络请求都会经过它。监视网关可以帮助管理员了解和控制进出网络的数据流,包括访问的网址、流量大小、可能的网络滥用等。这样的监视可以增强网络安全,防止未授权访问和数据泄露。 根据文件名称列表中的"count_web_v1.00.c",可以推断出该压缩包可能包含一个用C语言编写的程序,版本号为1.00,用于实现上述提到的网址计数功能。C语言是一种广泛用于系统编程和底层软件开发的语言,具备直接与操作系统交互的能力,适合用来编写网络抓包和数据处理的程序。 总结以上知识点,我们可以得出"count_web_v1.00.rar_包 网址"这一资源的核心用途是实现一个网络抓包程序,用于在混杂模式下捕获所有经过网关的HTTP数据包,并对其中出现的网址进行计数,从而提供对网关访问活动的监视。该程序可能会在网络安全、网络管理和网站流量分析等多个方面发挥作用。

select lot_hs.lot_id as lot_id,lot_type,lot_hs.mainpd_id, created_time,COMPLETE_TIME, value(bank.banktime,0) as banktime , round ( ( 1.00*(days(COMPLETE_TIME)-days(created_time)) + (hour(COMPLETE_TIME)-hour(created_time))*1.00/24 + (minute(COMPLETE_TIME)-minute(created_time))*1.00/24/60 + (second(COMPLETE_TIME)-second(created_time))1.00/24/60/60) - value(bank.banktime,0),3) as use_days, customer_id, coalesce(cc.cust_id_define,lot_hs.customer_id) as cust_id2, cc.cycletime_target as ct_target, date,layer, round(count() over(partition by coalesce(cc.cust_id_define,lot_hs.customer_id),cc.cycletime_target)*0.9,0) cnt, row_number() over(partition by coalesce(cc.cust_id_define,lot_hs.customer_id),cc.cycletime_target order by ( ( days(COMPLETE_TIME)-days(created_time) + (hour(COMPLETE_TIME)-hour(created_time))*1.00/24 + (minute(COMPLETE_TIME)-minute(created_time))*1.00/24/60 + (second(COMPLETE_TIME)-second(created_time))*1.00/24/60/60) - value(bank.banktime,0))/layer) id From (select date(a.claim_time) as date, a.lot_id, a.lot_type,a.mainpd_id,a.prodspec_id,a.custprod_id, case when(date(b.created_time) <= '2009-01-05') then b.created_time + 21 days else b.created_time end as created_time, CASE WHEN A.CUST_id in ('MCA','NPA','SET') THEN a.COMPLETE_TIME ELSE a.COMPLETE_TIME END COMPLETE_TIME, a.cust_id as customer_id, a.ope_category, c.layer From f3rpt.F3_TB_DAILY_FABOUT a, f3rpt.fvlot b, (select mainpd_id, sum(masks)layer from f3rpt.ASMCRPT_VW_MAINPD_MASKS_ALL group by mainpd_id) as c, (select * from (select lot_id, max(claim_time)claim_time, count(case when(ope_category='Ship')then lot_id else null end) as LS, count(case when(ope_category='Unship') then lot_id else null end) as LUS from f3rpt.F3_TB_DAILY_FABOUT where substr(lot_id,1,2) not in('CA','CW','ES','E0','EM') and lot_type = 'Production' AND LOT_ID NOT LIKE 'H%' and substr(lot_id,7,4)='.00F' and ope_category in ('Ship','Unship') and year(claim_time) = year(current date - 1 days) and month(claim_time) = month(current date - 1 days) group by lot_id) as a where LS - LUS > 0 ) as lot Where a.lot_id = b.lot_id and b.mainpd_id = c.mainpd_id and a.lot_id = lot.LOT_ID and a.claim_time = lot.claim_time and a.ope_category = 'Ship' and a.cust_id in ('SM','BOE','GSC','NPA','GTA') ) as lot_hs left outer join (select lot_id,max(bankin_time) banktime from f3rpt.asmc_dpm where bankin_time>0 group by lot_id) bank on (lot_hs.lot_id = bank.lot_id) left join f3cim.f3cim_cfg_cust_rule cc on case when lot_hs.customer_id='WXM' THEN 'WII'||SUBSTR(lot_hs.mainpd_id,6,1) else lot_hs.customer_id end = cc.cust_id and locate(cc.mainpd_id,lot_hs.mainpd_id)>0 and locate(cc.prodspec_id,lot_hs.prodspec_id)>0 and locate(cc.custprod_id_45,substr(lot_hs.custprod_id,3,3))>0 where lot_hs.ope_category = 'Ship' ;以上sql如何优化

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