Linux上很多好工具要解决的问题(需求)可能别人多年前就也遇到过了,但别人不告诉我的话我就根本不知道它存在。第一次知道MTR还是在几年前和其他公司的工程师沟通XML接口速度问题的时候学到的,当时对方发来这样一个报表:
Host Loss% Snt Last Avg Best Wrst StDev
1. 60.195.249.1 0.0% 41 0.3 2.2 0.3 71.5 11.1
2. 202.99.57.129 0.0% 41 0.3 0.3 0.2 1.5 0.2
3. 202.99.57.9 0.0% 41 0.7 19.9 0.6 189.6 46.8
4. 221.239.18.133 0.0% 41 3.2 3.4 3.2 3.7 0.1
5. 221.239.7.49 0.0% 41 3.0 2.8 2.7 3.2 0.1
6. 221.238.222.209 0.0% 41 2.7 14.2 2.7 131.5 29.9
7. 202.97.34.225 0.0% 41 22.7 23.0 22.6 29.0 1.0
8. 202.97.37.53 0.0% 41 22.7 34.5 22.6 180.6 37.1
9. 202.97.33.10 0.0% 41 23.1 22.9 22.7 23.6 0.2
10. 202.97.33.54 0.0% 40 24.4 31.6 23.1 44.9 6.0
11. 202.97.4.46 0.0% 40 58.0 58.3 58.0 60.8 0.4
12. 216.239.47.237 12.5% 40 188.2 189.2 188.0 204.6 2.8
13. 72.14.239.13 10.0% 40 191.7 191.8 191.1 193.5 0.5
14. 72.14.233.55 7.7% 40 192.0 191.4 190.7 192.2 0.4
15. 72.14.233.118 12.5% 40 242.8 243.1 242.4 244.8 0.6
16. 72.14.236.183 7.5% 40 243.7 243.5 242.3 250.9 1.6
72.14.232.113
17. 66.249.94.118 22.5% 40 242.7 247.9 242.7 255.7 4.5
72.14.236.13018. eh-in-f99.google 10.0% 40 242.7 243.3 242.6 246.0 0.6
利用报表中的提示搜索了一下,发现了mtr这个工具,以前需要多个ping和traceroute 命令实现的统计,用mtr集成在了一起。
WinMTR就是MTR工具的Windows窗口客户端,非常适合Windows用户做路由跟踪。
下载地址:winmtr.sourceforge.net
2 (very) Australian television commercials that use simple infographic diagrams to convince people to eat more lamb (& be more Australian). in fact, tomorrow is Australia day, the day no lamb is safe.
[links: votelamb.com.au & youtube.com (bar chart) & youtube.com (pie chart)|thnkx Andrea]
an interactive infographic of President Bush's State of the Union address over the years, averaged about 5,000 words, or 34.000 words in total. this means some words appear more frequently than others.
see also presidential speech tagcloud & state of the union visualization & power of words & the updated parsing the state of the union.
[link: nytimes.com]
an online application that blends software art & search tools to visualize participants' interests in prevalent streams of information, encouraging browsing & interaction between users in real time.
participants search for words which expand contextually through the use of a lexical database. English nouns, verbs, adjectives & adverbs are organized into floating synonym "seeds," each representing 1 underlying lexical concept. when participants "plant" their interests, each becomes a tree that "grows" over time. each organism's leaves are linked to related streaming RSS feeds, & by interacting with their own & other participants' trees, participants create a contextual timescape in which interests can be seen growing & changing within an environment that endures.
see also casual search & mnemomap search & hierarchical search & the still very aesthetic ecotonoha.
[link: turbulence.org]