Ultimately you always have a finite max of heap to use no matter what platform you are running on. In Windows 32 bit this is around 2GB
(not specifically heap but total amount of memory per process). It just happens that Java chooses to make the default smaller (presumably so that the programmer can't create programs that have runaway memory allocation without running into this problem and having to examine exactly what they are doing).
So this given there are several approaches you could take to either determine what amount of memory you need or to reduce the amount of memory you are using. One common mistake with garbage collected languages such as Java or C# is to keep around references to objects that you no longer are using, or allocating many objects when you could reuse them instead. As long as objects have a reference to them they will continue to use heap space as the garbage collector will not delete them.
In this case you can use a Java memory profiler to determine what methods in your program are allocating large number of objects and then determine if there is a way to make sure they are no longer referenced, or to not allocate them in the first place. One option which I have used in the past is "JMP" http://www.khelekore.org/jmp/.
If you determine that you are allocating these objects for a reason and you need to keep around references (depending on what you are doing this might be the case), you will just need to increase the max heap size when you start the program. However, once you do the memory profiling and understand how your objects are getting allocated you should have a better idea about how much memory you need.
In general if you can't guarantee that your program will run in some finite amount of memory (perhaps depending on input size) you will always run into this problem. Only after exhausting all of this will you need to look into caching objects out to disk etc. At this point you should have a very good reason to say "I need Xgb of memory" for something and you can't work around it by improving your algorithms or memory allocation patterns. Generally this will only usually be the case for algorithms operating on large datasets (like a database or some scientific analysis program) and then techniques like caching and memory mapped IO become useful.
Summary ArrayList
with ArrayDeque
are preferable in many more use-cases than LinkedList
. If you're not sure — just start with ArrayList
.
TLDR, in ArrayList accessing an element takes constant time [O(1)] and adding an element takes O(n) time [worst case]. In LinkedList adding an element takes O(n) time and accessing also takes O(n) time but LinkedList uses more memory than ArrayList.
LinkedList
and ArrayList
are two different implementations of the List interface. LinkedList
implements it with a doubly-linked list. ArrayList
implements it with a dynamically re-sizing array.
As with standard linked list and array operations, the various methods will have different algorithmic runtimes.
For LinkedList<E>
get(int index)
is O(n) (with n/4 steps on average), but O(1) when index = 0
or index = list.size() - 1
(in this case, you can also use getFirst()
and getLast()
). One of the main benefits of LinkedList<E>
add(int index, E element)
is O(n) (with n/4 steps on average), but O(1) when index = 0
or index = list.size() - 1
(in this case, you can also use addFirst()
and addLast()
/add()
). One of the main benefits of LinkedList<E>
remove(int index)
is O(n) (with n/4 steps on average), but O(1) when index = 0
or index = list.size() - 1
(in this case, you can also use removeFirst()
and removeLast()
). One of the main benefits of LinkedList<E>
Iterator.remove()
is O(1). One of the main benefits of LinkedList<E>
ListIterator.add(E element)
is O(1). One of the main benefits of LinkedList<E>
Note: Many of the operations need n/4 steps on average, constant number of steps in the best case (e.g. index = 0), and n/2 steps in worst case (middle of list)
For ArrayList<E>
get(int index)
is O(1). Main benefit of ArrayList<E>
add(E element)
is O(1) amortized, but O(n) worst-case since the array must be resized and copied
add(int index, E element)
is O(n) (with n/2 steps on average)
remove(int index)
is O(n) (with n/2 steps on average)
Iterator.remove()
is O(n) (with n/2 steps on average)
ListIterator.add(E element)
is O(n) (with n/2 steps on average)
Note: Many of the operations need n/2 steps on average, constant number of steps in the best case (end of list), n steps in the worst case (start of list)
LinkedList<E>
allows for constant-time insertions or removals using iterators, but only sequential access of elements. In other words, you can walk the list forwards or backwards, but finding a position in the list takes time proportional to the size of the list. Javadoc says "operations that index into the list will traverse the list from the beginning or the end, whichever is closer", so those methods are O(n) (n/4 steps) on average, though O(1) for index = 0
.
ArrayList<E>
, on the other hand, allow fast random read access, so you can grab any element in constant time. But adding or removing from anywhere but the end requires shifting all the latter elements over, either to make an opening or fill the gap. Also, if you add more elements than the capacity of the underlying array, a new array (1.5 times the size) is allocated, and the old array is copied to the new one, so adding to an ArrayList
is O(n) in the worst case but constant on average.
So depending on the operations you intend to do, you should choose the implementations accordingly. Iterating over either kind of List is practically equally cheap. (Iterating over an ArrayList
is technically faster, but unless you're doing something really performance-sensitive, you shouldn't worry about this -- they're both constants.)
The main benefits of using a LinkedList
arise when you re-use existing iterators to insert and remove elements. These operations can then be done in O(1) by changing the list locally only. In an array list, the remainder of the array needs to be moved (i.e. copied). On the other side, seeking in a LinkedList
means following the links in O(n) (n/2 steps) for worst case, whereas in an ArrayList
the desired position can be computed mathematically and accessed in O(1).
Another benefit of using a LinkedList
arises when you add or remove from the head of the list, since those operations are O(1), while they are O(n) for ArrayList
. Note that ArrayDeque
may be a good alternative to LinkedList
for adding and removing from the head, but it is not a List
.
Also, if you have large lists, keep in mind that memory usage is also different. Each element of a LinkedList
has more overhead since pointers to the next and previous elements are also stored. ArrayLists
don't have this overhead. However, ArrayLists
take up as much memory as is allocated for the capacity, regardless of whether elements have actually been added.
The default initial capacity of an ArrayList
is pretty small (10 from Java 1.4 - 1.8). But since the underlying implementation is an array, the array must be resized if you add a lot of elements. To avoid the high cost of resizing when you know you're going to add a lot of elements, construct the ArrayList
with a higher initial capacity.
If the data structures perspective is used to understand the two structures, a LinkedList is basically a sequential data structure which contains a head Node. The Node is a wrapper for two components : a value of type T [accepted through generics] and another reference to the Node linked to it. So, we can assert it is a recursive data structure (a Node contains another Node which has another Node and so on...). Addition of elements takes linear time in LinkedList as stated above.
An ArrayList, is a growable array. It is just like a regular array. Under the hood, when an element is added at index i, it creates another array with a size which is 1 greater than previous size (So in general, when n elements are to be added to an ArrayList, a new array of size previous size plus n is created). The elements are then copied from previous array to new one and the elements that are to be added are also placed at the specified indices.
Best Solution
-Xmx15G
will set the maximum heap size to 15 gig. Java will only allocate what it needs as it runs. If you don't set it, it will only use the default. For info on the default, see this post.-Xms15G
sets the minimum heap to 15 gig. This forces java to allocate 15 gig of heap space before it starts executing, whether it needs it or not.Usually you can set them both to appropriate values depending on how you're tuning the JVM.