Question

I’m building a index which is just several sets of ordered 32 bit integers stored continuously in a binary file. The problem is that this file grows pretty large. I’ve been thinking of adding some compressions scheme but that’s a bit out of my expertise. So I’m wondering, what compression algorithm would work best in this case? Also, decompression has to be fast since this index will be used to make make look ups.

Answer 1

If you are storing integers which are close together (eg: 1, 3 ,4, 5, 9, 10 etc… ) rather than some random 32 bit integers (982346…, 3487623412.., etc) you can do one thing:

Find the differences between the adjacent numbers which would be like 2,1,1,4,1… etc.(in our example) and then Huffman encode this numbers.

I don’t think Huffman encoding will work if you directly apply them to the original list of numbers you have.

But if you have a sorted list of near-by numbers, the odds are good that you will get a very good compression ratio by doing Huffman encoding of the number differences, may be better ratio than using the LZW algorithm used in the Zip libraries.

Anyway thanks for posting this interesting question.