
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
Write a SQL query to rank scores. If there is a tie between two scores, both should have the same ranking. Note that after a tie, the next ranking number should be the next consecutive integer value. In other words, there should be no "holes" between ranks.
For example, given the above
Scores
table, your query should generate the following report (order by highest score):这道题给了我们一个分数表,让我们给分数排序,要求是相同的分数在相同的名次,下一个分数在相连的下一个名次,中间不能有空缺数字,这道题我是完全照着史蒂芬大神的帖子来写的,膜拜大神中...大神总结了四种方法,那么我们一个一个的来膜拜学习,首先看第一种解法,解题的思路是对于每一个分数,找出表中有多少个大于或等于该分数的不同的分数,然后按降序排列即可,参见代码如下:
解法一:
跟上面的解法思想相同,就是写法上略有不同:
解法二:
下面这种解法使用了内交,Join是Inner Join的简写形式,自己和自己内交,条件是右表的分数大于等于左表,然后群组起来根据分数的降序排列,十分巧妙的解法:
解法三:
下面这种解法跟上面三种的画风就不太一样了,这里用了两个变量,变量使用时其前面需要加@,这里的:= 是赋值的意思,如果前面有Set关键字,则可以直接用=号来赋值,如果没有,则必须要使用:=来赋值,两个变量rank和pre,其中rank表示当前的排名,pre表示之前的分数,下面代码中的<>表示不等于,如果左右两边不相等,则返回true或1,若相等,则返回false或0。初始化rank为0,pre为-1,然后按降序排列分数,对于分数4来说,pre赋为4,和之前的pre值-1不同,所以rank要加1,那么分数4的rank就为1,下面一个分数还是4,那么pre赋值为4和之前的4相同,所以rank要加0,所以这个分数4的rank也是1,以此类推就可以计算出所有分数的rank了。
解法四:
参考资料:
https://leetcode.com/discuss/40116/simple-short-fast
LeetCode All in One 题目讲解汇总(持续更新中...)
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