Log for YSITD
ㄍㄍㄍㄍㄢㄍㄢㄍㄢ幹ㄕㄕㄕㄕㄤㄕㄤㄕㄤㄕㄤㄑㄕㄤㄑㄕㄤㄑㄕㄤㄑㄩㄕㄤㄑㄩㄕㄤㄑㄩ上去 ㄓㄓㄓㄓㄨㄓㄨㄓㄨ住ㄧㄧㄧㄧㄣㄧㄣㄧㄣㄧㄣㄓㄧㄣㄓㄧㄣㄓㄧㄣㄓㄤㄧㄣㄓㄤㄧㄣㄓㄤ音障ㄞㄞㄞ礙
ㄨㄨㄨㄨㄤㄨㄤㄨㄤㄨㄤㄅㄨㄤㄅㄨㄤㄅㄨㄤㄅㄚㄨㄤㄅㄚㄨㄤㄅㄚㄨㄤㄅㄚㄉㄨㄤㄅㄚㄉㄨㄤㄅㄚㄉㄨㄤㄅㄚㄉㄢㄨㄤㄅㄚㄉㄢㄨㄤㄅㄚㄉㄢ王八蛋
ㄕㄕㄕㄕㄨㄕㄨㄕㄨㄕㄨㄟㄕㄨㄟㄕㄨㄟㄕㄨㄟㄐㄕㄨㄟㄐㄕㄨㄟㄐㄕㄨㄟㄐㄩㄕㄨㄟㄐㄩㄕㄨㄟㄐㄩㄕㄨㄟㄐㄩㄝㄕㄨㄟㄐㄩㄝㄕㄨㄟㄐㄩㄝ睡覺ㄏㄏㄏㄏㄠㄏㄠㄏㄠㄏㄠㄖㄏㄠㄖㄏㄠㄖㄏㄠㄖㄜㄏㄠㄖㄜㄏㄠㄖㄜ好惹
[情報] iPhone 7重磅功能確定：終於支持快充!
http://www.ptt.cc/bbs/mobilecomm/M.1471092712.A.C6E.html
http://www.ptt.cc/bbs/mobilecomm/M.1471092712.A.C6E.html
Google Drive現在會有小數點惹喔
https://img.chris.taipei/20160814125421.png
https://img.chris.taipei/20160814125421.png
A distributed hash table (DHT) is a class of a decentralized distributed system that provides a lookup service similar to a hash table: (key, value) pairs are stored in a DHT, and any participating node can efficiently retrieve the value associated with a given key.
Ok, they're fundamentally a pretty simple idea. A DHT gives you a dictionary-like interface, but the nodes are distributed across the network. The trick with DHTs is that the node that gets to store a particular key is found by hashing that key, so in effect your hash-table buckets are now independent nodes in a network.
This gives a lot of fault-tolerance and reliability, and possibly some performance benefit, but it also throws up a lot of headaches. For example, what happens when a node leaves the network, by failing or otherwise? And how do you redistribute keys when a node joins so that the load is roughly balanced. Come to think of it, how do you evenly distribute keys anyhow? And when a node joins, how do you avoid rehashing everything? (Remember you'd have to do this in a normal hash table if you increase the number of buckets).
One example DHT that tackles some of these problems is a logical ring of n nodes, each taking responsibility for 1/n of the keyspace. Once you add a node to the network, it finds a place on the ring to sit between two other nodes, and takes responsibility for some of the keys in its sibling nodes. The beauty of this approach is that none of the other nodes in the ring are affected; only the two sibling nodes have to redistribute keys.
For example, say in a three node ring the first node has keys 0-10, the second 11-20 and the third 21-30. If a fourth node comes along and inserts itself between nodes 3 and 0 (remember, they're in a ring), it can take responsibility for say half of 3's keyspace, so now it deals with 26-30 and node 3 deals with 21-25.
There are many other overlay structures such as this that use content-based routing to find the right node on which to store a key. Locating a key in a ring requires searching round the ring one node at a time (unless you keep a local look-up table, problematic in a DHT of thousands of nodes), which is O(n)-hop routing. Other structures - including augmented rings - guarantee O(log n)-hop routing, and some claim to O(1)-hop routing at the cost of more maintenance.
This gives a lot of fault-tolerance and reliability, and possibly some performance benefit, but it also throws up a lot of headaches. For example, what happens when a node leaves the network, by failing or otherwise? And how do you redistribute keys when a node joins so that the load is roughly balanced. Come to think of it, how do you evenly distribute keys anyhow? And when a node joins, how do you avoid rehashing everything? (Remember you'd have to do this in a normal hash table if you increase the number of buckets).
One example DHT that tackles some of these problems is a logical ring of n nodes, each taking responsibility for 1/n of the keyspace. Once you add a node to the network, it finds a place on the ring to sit between two other nodes, and takes responsibility for some of the keys in its sibling nodes. The beauty of this approach is that none of the other nodes in the ring are affected; only the two sibling nodes have to redistribute keys.
For example, say in a three node ring the first node has keys 0-10, the second 11-20 and the third 21-30. If a fourth node comes along and inserts itself between nodes 3 and 0 (remember, they're in a ring), it can take responsibility for say half of 3's keyspace, so now it deals with 26-30 and node 3 deals with 21-25.
There are many other overlay structures such as this that use content-based routing to find the right node on which to store a key. Locating a key in a ring requires searching round the ring one node at a time (unless you keep a local look-up table, problematic in a DHT of thousands of nodes), which is O(n)-hop routing. Other structures - including augmented rings - guarantee O(log n)-hop routing, and some claim to O(1)-hop routing at the cost of more maintenance.
每一個人對自己會有些期望，希望自己像德雷莎修女一樣悲天憫人，希望自己像顏回一樣好學深思，希望自己像諸葛亮一樣足智多謀，希望自己像比爾蓋茲有創意又多金。你希望自己可以成為什麼樣的人，請寫出對自己的期望，並說明原因。
giphy.gif (271×246)
https://media.giphy.com/media/3o7TKvHOyKHOvRAlm8/giphy.gif
https://media.giphy.com/media/3o7TKvHOyKHOvRAlm8/giphy.gif
I scored 6160 points at 2048, a game where you join numbers to score high! @2048_game https://itunes.apple.com/app/2048/id840919914
Football GIF - Find & Share on GIPHY
http://giphy.com/gifs/own-goal-3o6ZsU2KPRdP2FODGU
http://giphy.com/gifs/own-goal-3o6ZsU2KPRdP2FODGU
日行一善當好人 做愛次數比壞人高 | 必PO TV
http://bepo.ctitv.com.tw/2016/08/110915/
http://bepo.ctitv.com.tw/2016/08/110915/
要我買hTC 10的意思嗎 (?
http://chinese.engadget.com/2016/08/14/htc-10-review/#/
http://chinese.engadget.com/2016/08/14/htc-10-review/#/
一邊上載一邊下載 覺得Router累累der (?
https://img.chris.taipei/20160814201157.png
https://img.chris.taipei/20160814201157.png
CLOUDSEC Taiwan 2016 - CLOUDSEC
https://www.cloudsec.com/event/cloudsec-taiwan-2016/
https://www.cloudsec.com/event/cloudsec-taiwan-2016/
so，aria2的rpc就因为是nginx reverse proxy的帮助所以，只能从被设置好的directory access rpc的port？
有寫程式的朋友推薦你們三本書
一定要讀但是不要死記，上面的寫法是一個正規化的做法
如果死讀會扼殺掉一成功的coder，但是不讀就不會進步所以自己拿捏分寸
一定要讀但是不要死記，上面的寫法是一個正規化的做法
如果死讀會扼殺掉一成功的coder，但是不讀就不會進步所以自己拿捏分寸
