I have a problem that involves biology area. Right now I have 4 VERY LARGE files(each with 0.1 billion lines), but the structure is rather simple, each line of these files has only 2 fields, both stands for a type of gene.
My goal is: design an efficient algorithm that can achieves the following:
Find a circle within the contents of these 4 files. The circle is defined as:
field #1 in a line in file 1 == field #1 in a line in file 2 and
field #2 in a line in file 2 == field #1 in a line in file 3 and
field #2 in a line in file 3 == field #1 in a line in file 4 and
field #2 in a line in file 4 == field #2 in a line in file 1
I cannot think of a decent way to solve this, so I just wrote a brute-force-stupid-4-layer-nested loop for now. I’m thinking about sorting them as alphabetical order, even if that might help a little, but then it’s also obvious that the computer memory would not allow me to load everything at once. Can anybody tell me a good way to solve this problem in a both time and space efficient way? Thanks!!
First of all, I note that you can sort a file without holding it memory all at once, and that most operating systems have some program that does this, often called just “sort”. Usually you can get it to sort on a field within a file, but if not you can rewrite each line to get it to sort the way you want.
Given this, you can connect two files by sorting them so that the first is sorted on field #1 and the second on field #2. You can then create one record for each match, combining all the fields, and only holding in memory a chunk from each file where all the fields you have sorted on have the same value. This will allow you to connect the result with another file – four such connections should solve your problem.
Depending on your data, the time it takes to solve your problem may depend on the order in which you make the connections. One rather naive way to make use of this is, at each stage, to take a small random sample from each file, and use this to see how many results will follow from each possible connection, and choose the connection that produces the fewest results. One way to take a random sample of N items from a large file is to take the first N lines in the file and then, when you have read in m lines so far, read the next line, and then with probability N/(m + 1) exchange one of the N lines held for it, else throw it away. Keep on until you have read through the whole file.