Java – High CPU usage in Eclipse when idle

The three most influential factors for Eclipse speed are:

• Using the latest version of Eclipse (2020-06 as on 26 June 2020)
  Note that David Balažic's comment (July 2014) contradicts that criteria which was working six years ago:

The "same" workspace in Indigo (3.7.2) SR2 loads in 4 seconds, in Kepler SR2 (4.3.2) in 7 seconds and in Luna (4.4.0) in 10 seconds. All are Java EE bundles. Newer versions have more bundled plugins, but still the trend is obvious. (by "same" workspace I mean: same (additionally installed) plugins used, same projects checked out from version control).

• Launching it with the latest JDK (Java 14 at the time of writing, which does not prevent you to compile in your Eclipse project with any other JDK you want: 1.4.2, 1.5, 1.6 older...)

    -vm jdk1.6.0_10\jre\bin\client\jvm.dll
  

• Configuring the eclipse.ini (see this question for a complete eclipse.ini)

    -Xms512m
    -Xmx4096m
    [...]
  

The Xmx argument is the amount of memory Eclipse will get (in simple terms). With -Xmx4g, it gets 4 GB of RAM, etc.

Note:

1. Referring to the jvm.dll has advantages:

• Splash screen coming up sooner.
• Eclipse.exe in the process list instead of java.exe.
• Firewalls: Eclipse wants access to the Internet instead of Java.
• Window management branding issues, especially on Windows and Mac.

Dec. 2020, Udo conforms in the comments

From version 4.8 (Photon) an up there was a steady speed gain after each version.
The main platform was optimized every release to load faster, enable more features for the dark theme and to add more features for newer Java versions for the Java development tools.
Especially with-in the last 3 versions the startup time was increased a lot. There should be a significant increase in start-up time with the newest version of Eclipse 2020-12.

In my experience it started a lot faster with each new version.
But: There are still plug-ins which do not follow the new way of using the Eclipse API and are therefore still slow to start.
Since the change to Java 11 as the minimum runtime version starting from Eclipse version 2020-09 at least the core system uses the newer features of the JVM. It is up to the providers of the other plug-ins to upgrade to newer APIs and to use the full power of modern CPUs (e.g. concurrent programming model).

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.