1576 - Extractor
Time Limit : 1 Second
Memory Limit : 128 MB
Submission: 341
Solved: 154
- Description
- Large scale data is very hard to processing with single server. With larger and larger scale data, Google introduced a large scale data processing model named Map/Reduce.
A Map/Reduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. A framework sorts the outputs of the maps, which are then input to the reduce tasks. Typically both the input and the output of the job are stored in a file-system.(Copyed at hadoop official site, MapReduce Tutorial)
For a common use, the map tasks, usually just input some structured data list, separate by Tab character (‘\t’, ASCII is 9) and Line feed character (‘\n’, ASCII is 10), and choose some row rearranged with requirement, then output it. All the processing are line-based. We called this kind of application with extractor.
Now we just want you to write a simple extractor.
- Input
- First line is a number indicate the test case number(equal or less then 50).
For each case, first line are three number, n(1<=n<=200), m, p(1<=m,p<=50), indicate line number, row number, and chose row number.
Next line has p number, indicating the chosen row index (count start with 0), ordered with we want.
Next n lines each line has m part separate by Tab character (‘\t’), each part just contain letters and digits, and the length not longer then 25. { not 20 } - Output
- For each case, the first line output “Case X:” X means the X case.
For each case, output the extracted data set with N lines and each line p part separate by Tab character (‘\t’).
- sample input
-
2 2 4 2 2 0 A B C D YXB XY LKQ XH 4 3 2 0 2 Tenc 100 AC Bidu 200 BC RR 300 CD Ali 400 XX
- sample output
-
Case 1: C A LKQ YXB Case 2: Tenc AC Bidu BC RR CD Ali XX
- hint
- source
- Hong Zehua