This isn't a homework question but for clearity I think I'll phrase it like one since I'm teaching this year...
Let n be an abitrary positive integer value (assume at least 100)
Let A be the memory allocated by the following single command: Object x = new Object[n];
Let B be the memory allocated by the following single command: double y = new double[n];
What is the approximate value of A/B? Or, alternatively which is bigger and by what percentage?
For my situation, I have a large n^k dimensional matrix that uses a ton of space and I'm trying to determine if there would like be space saved using either implementation. [ September 13, 2006: Message edited by: Scott Selikoff ]
Well, it's implementation-dependent, but in general new Object[n] should take 4*n bytes (each reference is a 32-bit value), and new double[n] should take 8*n bytes (each double being a 64-bit value). So looking just at the arrays, the double takes twice as much space. However the Object will probably need some actual Objects too (Doubles perhaps?), and depending on how many different objects you have, there's a good chance that the Object version will end up taking more total memory. Unless the references are mostly null or mostly to shared instances.
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Joined: Jan 30, 2000
And in the event you do have a lot of nulls in there, you might want to use some sort of sparse matrix implementation, for greater memory savings.
Actually I am working with sparse matrixes, so perhaps I should rethink the construction. I thought using nulls (and then replacing with Double) would save space and it sounds like it would, but there are better ways to implement sparse matrices that I'm thinking I will try.
Thanks for the information though (I suspected 4*n but wasn't sure). Interestingly, if I used float[n] I'm guessing this would be the same as Object[n] plus the space for each object.
Problem solved.... using arrays with null elements instead of a fully initialized one saved insane amounts of space.
Part of the reason I was having trouble is because I'm creating a dynamic matrix on the fly using reflection so I had to modify the reflection classes used to construct the array (so don't construct nxnxn, construct nx3, and put  pointers in the columns initially set to null).
Joined: Jan 30, 2000
[Scott]: As an aside, do you know of good sparse matrix implementions and/or one that used prefix matching techniques?
Never used it myself, but I heard good things about Colt back when it came out, years ago. (Not about sparse matrices in particular, but the library in general.) Haven't heard much since - I haven't done much resembling real math in some time. No idea about prefix matching techniques in matrices, sorry. Though it sounds like you're in good shape now anyway...
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