Calculating top for a large time frame

One common problem is to find the top contributors out of a huge set of unique values. For instance, if you want to know what IP addresses are using the most bandwidth in a given day or week, you may have to keep a track of the total of request sizes across millions of unique hosts to definitively answer this question. When using summary indexes, this means storing millions of events in the summary index, quickly defeating the purpose of summary indexes.

Just to illustrate, let's look at a simple set of data:

Time 1.1.1.1 2.2.2.2 3.3.3.3 4.4.4.4 5.5.5.5 6.6.6.6 
12:00 99 100 100 100 
13:00 99 100 100 100 
14:00 99 100 101 100 
15:00 99 99 100 100 
16:00 99 100 100 100 
total 495 300 299 401 400 100 

If we only stored the top three IPs per hour, our dataset would look like the following:

Time 1.1.1.1 2.2.2.2 3.3.3.3 4.4.4.4 5.5.5.5 6.6.6.6 
12:00 100 100 100 
13:00 100 100 100 
14:00 100 101 100 
15:00 99 100 100 
16:00 100 100 100 
total 300 299 401 400...