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Good way to think this problem. My solution is similar, but it bought up another question:
- Zhijing78 April 08, 2013My original design is a 2 column table:
Table( day, details) --- Detail is a concatenated string of numbers, like CSV file.
Then I day or the timestamp in your design is the Index.
Index normally is B tree(im not trying to use other types of indexes), then the search to day in my design is around O(log 365*5 ) , ignore the fact of bissextile years.
Then searching in detail will be O(60*60*12).
On the other hand, in your design,
searching indexes will be O(Log (5*365*12*60)), in the detail will be O(60).
so this becomes a math problem to find the extreme point for different search. (well, also depends on what kinda search those uses do most).
I am not going to do any math here, because I haven't done it. However, another thing we can do is to partition the table (maybe by range -- quarters of the year, or month) to divide the big data set. I have a feeling your design is more reasonable than mine, after partitioning. (since my Original design is "daily" based, so the data entry number is limited for the index. In this case, partitioning won't help too much. Your design suits it better. )
So to improve it, we can do a math here, to better adjust the index big O and detail big O, or ask for more details of how often do users use each search functions.