I am trying to implement a plane sweep algorithm and for this I need to know the time complexity of java.util.HashMap class' keySet() method. I suspect that it is O(n log n). Am I correct?
Point of clarification: I am talking about the time complexity of the keySet() method; iterating through the returned Set will take obviously O(n) time.
Surely it would be O(1). All that it is doing is returning a wrapper object on the HashMap.
If you are talking about walking over the keyset, then this is O(n), since each next() call is O(1), and this needs to be performed n times.
This should be doable in O(n) time... A hash map is usually implemented as a large bucket array, the bucket's size is (usually) directly proportional to the size of the hash map. In order to retrieve the key set, the bucket must be iterated through, and for each set item, the key must be retrieved (either through an intermediate collection or an iterator with direct access to the bucket)...
**EDIT: As others have pointed out, the actual keyset() method will run in O(1) time, however, iterating over the keyset or transferring it to a dedicated collection will be an O(n) operation. Not quite sure which one you are looking for **
Java collections have a lot of space and thus don't take much time. That method is, I believe, O(1). The collection is just sitting there.
Actually, getting the keyset is
O(1)
and cheap. This is because HashMap.keyset() returns the actual KeySet object associated with the HashMap.The returned Set is not a copy of the keys, but a wrapper for the actual HashMap's state. Indeed, if you update the set you can actually change the HashMap's state; e.g. calling
clear()
on the set will clear the HashMap!To address the "iterating through the returned Set will take obviously O(n) time" comment, this is not actually correct per the doc comments of
HashMap
:So in other words, iterating over the returned
Set
will takeO(n + c)
wheren
is the size of the map andc
is its capacity, notO(n)
. If an inappropriately sized initial capacity or load factor were chosen, the value ofc
could outweigh the actual size of the map in terms of iteration time.