See my pet project, MemoryMeasurer. A tiny example:
long memory = MemoryMeasurer.measureBytes(new HashMap());
You may also derive more qualitative memory breakdown:
Footprint footprint = ObjectGraphMeasurer.measure(new HashMap());
For example, I used the latter to derive the per entry cost of various data structures, where the overhead is measured in number of objects created, references, and primitives, instead of just bytes (which is also doable). So, next time you use a (default) HashSet
, you can be informed that each element in it costs 1 new object (not your element), 5 references, and an int, which is the exact same cost for an entry in HashMap
(not unexpectedly, since any HashSet
element ends up in a HashMap
), and so on.
You can use it on any object graph. If your object graph contains links other structures you do wish to ignore, you should use a predicate to avoid exploring them.
Edit Instrumentation
is not available to Java 1.4 (wow, people still use that?!), so the memoryBytes
call above wouldn't work for you. But the second would. Then you can write something like this (if you are on a 32bit machine):
long memory = footprint.getObjects() * 8 + footprint.getReferences() * 4 +
footprint.getPrimitives().count(int.class) * 4 +
footprint.getPrimitives().count(long.class) * 8 + ...;
That gives you an approximation. A better answer would be to ceil this to the closest multiple of 16:
long alignedMemory = (x + 15) & (~0xF); //the last part zeros the lowest 4 bits
But the answer might still be off, since if you find, say, 16 booleans, it's one thing if they are found in the same object, and quite another if they are spread in multiple objects (and cause excessive space usage due to aligning). This logic could be implemented as another visitor (similar to how MemoryMeasurer and ObjectGraphMeasurer are implemented - quite simply as you may see), but I didn't bother, since that's what Instrumentation
does, so it would only make sense of Java versions below 1.5.