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I've always been one to simply use:

List<String> names = new ArrayList<>();

I use the interface as the type name for portability, so that when I ask questions such as these I can rework my code.

When should LinkedList be used over ArrayList and vice-versa?

Steve Chambers
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sdellysse
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    See also: [Array versus linked-list](http://stackoverflow.com/questions/166884/array-versus-linked-list?rq=1) – Hawkeye Parker Oct 12 '16 at 03:58
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    Just see the quote from the author of LinkedList https://stackoverflow.com/a/42529652/2032701 and you'll get a practical sense of the issue. – Ruslan Dec 26 '17 at 19:17

33 Answers33

3577

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 arise 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.

TurtleBot
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Jonathan Tran
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  • One thing many people forget is that ArrayList is compact in memory which means that it's more cache friendly than LinkedList. LinkedList could be spread out all over RAM, while ArrayList is always snuggly packed together to take advantage of spacial locality. This has important real world ramifications. – AminM Mar 26 '21 at 01:52
  • Would removing an element from the end of ArrayList be constant time complexity? Since I believe it doesn't require any shifting of elements? Ex. index = list.size() - 1. remove(index) – william cage May 20 '21 at 22:50
656

Thus far, nobody seems to have addressed the memory footprint of each of these lists besides the general consensus that a LinkedList is "lots more" than an ArrayList so I did some number crunching to demonstrate exactly how much both lists take up for N null references.

Since references are either 32 or 64 bits (even when null) on their relative systems, I have included 4 sets of data for 32 and 64 bit LinkedLists and ArrayLists.

Note: The sizes shown for the ArrayList lines are for trimmed lists - In practice, the capacity of the backing array in an ArrayList is generally larger than its current element count.

Note 2: (thanks BeeOnRope) As CompressedOops is default now from mid JDK6 and up, the values below for 64-bit machines will basically match their 32-bit counterparts, unless of course you specifically turn it off.


Graph of LinkedList and ArrayList No. of Elements x Bytes


The result clearly shows that LinkedList is a whole lot more than ArrayList, especially with a very high element count. If memory is a factor, steer clear of LinkedLists.

The formulas I used follow, let me know if I have done anything wrong and I will fix it up. 'b' is either 4 or 8 for 32 or 64 bit systems, and 'n' is the number of elements. Note the reason for the mods is because all objects in java will take up a multiple of 8 bytes space regardless of whether it is all used or not.

ArrayList:

ArrayList object header + size integer + modCount integer + array reference + (array oject header + b * n) + MOD(array oject, 8) + MOD(ArrayList object, 8) == 8 + 4 + 4 + b + (12 + b * n) + MOD(12 + b * n, 8) + MOD(8 + 4 + 4 + b + (12 + b * n) + MOD(12 + b * n, 8), 8)

LinkedList:

LinkedList object header + size integer + modCount integer + reference to header + reference to footer + (node object overhead + reference to previous element + reference to next element + reference to element) * n) + MOD(node object, 8) * n + MOD(LinkedList object, 8) == 8 + 4 + 4 + 2 * b + (8 + 3 * b) * n + MOD(8 + 3 * b, 8) * n + MOD(8 + 4 + 4 + 2 * b + (8 + 3 * b) * n + MOD(8 + 3 * b, 8) * n, 8)

Masterfego
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Numeron
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    The problem with your math is that your graph greatly exaggerates the impact. You are modelling objects which each contain only an ```int```, so 4 or 8 bytes of data. In the linked list, there are essentially 4 "words" of overhead. Your graph thus gives the impression that linked lists use "five times" the storage of array lists. This is wrong. The overhead is 16 or 32 bytes per object, as an additive adjustment, not a scaling factor. – Heath Hunnicutt Sep 06 '13 at 00:18
268

ArrayList is what you want. LinkedList is almost always a (performance) bug.

Why LinkedList sucks:

  • It uses lots of small memory objects, and therefore impacts performance across the process.
  • Lots of small objects are bad for cache-locality.
  • Any indexed operation requires a traversal, i.e. has O(n) performance. This is not obvious in the source code, leading to algorithms O(n) slower than if ArrayList was used.
  • Getting good performance is tricky.
  • Even when big-O performance is the same as ArrayList, it is probably going to be significantly slower anyway.
  • It's jarring to see LinkedList in source because it is probably the wrong choice.
Tom Hawtin - tackline
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145
Algorithm           ArrayList   LinkedList
seek front            O(1)         O(1)
seek back             O(1)         O(1)
seek to index         O(1)         O(N)
insert at front       O(N)         O(1)
insert at back        O(1)         O(1)
insert after an item  O(N)         O(1)

Algorithms: Big-Oh Notation (archived)

ArrayLists are good for write-once-read-many or appenders, but bad at add/remove from the front or middle.

drac_o
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Michael Munsey
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    You can't compare big-O values directly without thinking about constant factors. For small lists (and most lists are small), ArrayList's O(N) is faster than LinkedList's O(1). – Porculus Sep 10 '10 at 17:23
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    I don't care about small lists performance, and neither does my computer *unless* it is used in a loop somehow. – Maarten Bodewes Aug 18 '11 at 16:35
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    LinkedList can't really insert in the middle in `O(1)`. It has to run through half the list to find the insertion point. – Thomas Ahle Dec 30 '11 at 15:02
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    LinkedList: insert in middle O(1) - is WRONG! I found out that even insertion into 1/10th position of the LinkedList size is slower than inserting an element into 1/10th position of an ArrayList. And even worse: the end of collection. inserting into last positions (not the very last) of ArrayList is faster then into last positions (not the very last) of LinkedList – kachanov May 13 '12 at 14:29
  • See http://stackoverflow.com/questions/840648/why-is-inserting-in-the-middle-of-a-linked-list-o1 – Michael Munsey May 21 '12 at 22:43
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    @kachanov Inserting in a `LinkedList` *is* `O(1)` **if you have an iterator to the insert position**, i.e. `ListIterator.add` is supposedly `O(1)` for a `LinkedList`. – Has QUIT--Anony-Mousse Aug 18 '13 at 08:13
  • @Anony-Mousse: right. "If you have an iterator to the insert position". But if you don't have it, inseting in a LinkedList is NOT O(1). As you can see the original post, it says: "insert in middle" it does not say "insert in middle where you have a position found by iterator" – kachanov Sep 16 '13 at 08:21
  • Bad wording by the author. I'll edit his answer to clarify. Yes, seeking to the arithemetic average of the lists length will take `O(N)`. – Has QUIT--Anony-Mousse Sep 16 '13 at 09:40
  • I might would word it as "Insert after a node." You can insert after a given node whether you have an iterator or not. I still think insert in the middle means the same thing, and is clearer. – Michael Munsey Sep 30 '13 at 21:21
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    Nice answer. A small thing though : For `ArrayList` inserting at back is not always O(1). Maybe most of the times. But when it needs to reallocate the internal array a full copy will occur and a cost of O(n) will be incurred. – Andrei Rînea Jan 29 '15 at 13:08
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    True. This is still considered amortized O(1), ie http://anh.cs.luc.edu/363/notes/06A_Amortizing.html – Michael Munsey Feb 04 '15 at 00:00
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    @Anony-Mousse mind that manipulating a `List` via an iterator will invalidate all other potentially existing iterators of that list, so it is impossible to keep multiple iterators to interesting spots in a large list; you can keep at most one iterator for manipulations which has to be moved to the next location sequentially. This makes the scenario where you have an iterator pointing to the desired position, to make a manipulation in `O(1)` an entirely theoretical one. That’s not a deficiency of linked lists in general, it’s just that Java’s Collection API is not really designed for them. – Holger May 14 '19 at 16:52
  • @Holger it's easy to imagine workload that involves *searching* for an insert position first, then inserting at that position. In this case you *do* have such an iterator, and can avoid searching again. – Has QUIT--Anony-Mousse May 14 '19 at 18:48
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    @Anony-Mousse sure, if your task only involves inserting at the same position over and over again, you have the promised O(1) time complexity when keeping the iterator. It’s just a very unlikely scenario, to have a large list (where the time complexity matters), but only care for a bunch of elements inserted at a particular position. As soon is you start using the list for other purposes, you’ll likely lose anything you gained from that. – Holger May 15 '19 at 10:37
145

As someone who has been doing operational performance engineering on very large scale SOA web services for about a decade, I would prefer the behavior of LinkedList over ArrayList. While the steady-state throughput of LinkedList is worse and therefore might lead to buying more hardware -- the behavior of ArrayList under pressure could lead to apps in a cluster expanding their arrays in near synchronicity and for large array sizes could lead to lack of responsiveness in the app and an outage, while under pressure, which is catastrophic behavior.

Similarly, you can get better throughput in an app from the default throughput tenured garbage collector, but once you get java apps with 10GB heaps you can wind up locking up the app for 25 seconds during a Full GCs which causes timeouts and failures in SOA apps and blows your SLAs if it occurs too often. Even though the CMS collector takes more resources and does not achieve the same raw throughput, it is a much better choice because it has more predictable and smaller latency.

ArrayList is only a better choice for performance if all you mean by performance is throughput and you can ignore latency. In my experience at my job I cannot ignore worst-case latency.

lamont
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    Wouldn't another solution be managing the size of the list programmatically by using the ArrayList's ensureCapacity() method? My question is why are so many things being stored in a bunch of brittle data structures when they might better be stored in a caching or db mechanism? I had an interview the other day where they swore up and down about the evils of ArrayList, but I come here and I find that the complexity analysis is all-around better! GREAT POINT FOR DISCUSSION, THOUGH. THANKS! – ingyhere Oct 30 '12 at 05:33
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    *once you get java apps with 10GB heaps you can wind up locking up the app for 25 seconds during a Full GCs which causes timeouts* Actually with LinkedList you murder the garbage collector during full GCs, it has to iterate the overly large LinkedList with cache miss on each node. – bestsss Dec 17 '14 at 20:15
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    @bestsss What he is saying that you will never trigger a full GC cycle with link lists; the list will grow and shrink in increments of one element and the CMS GC will run continually; no hiccups. – Andreas Jun 16 '15 at 22:06
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    That's... a horrible solution. you're basically reliant on the GC cleaning up for you, which is incredibly expensive, when you can just call ensureCapacity() on an arraylist instead... – Philip Devine Jun 19 '15 at 14:03
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    @Andreas: when a list grows and shrinks in increments of one element, there is no problem with `ArrayList` at all, as it doesn’t even need additional memory for that. Considering the possibility that the `ArrayList` has to increase its capacity *once* during the entire life time of a web service as a reason to downgrade performance with a `LinkedList`, is quite strange, especially, if you consider the cost of the web service’s I/O in comparison. Expanding the capacity of an `ArrayList`, even with millions of elements, is rather unlikely to be noticed as latency. – Holger Jul 04 '16 at 10:20
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    @Holger An array list that increments over its capacity allocates a new list with 50% more room. For that increment you need 2.5 times the memory (and you likely need full gc cycle afterwards). I'm not concerned about day to day response time, I'm worried about running out of heap memory when a peak hour hits slightly harder than it hit yesterday and a couple big arraylists deciding they need room for 2.5 times their count for a second or two. One instance of that type of behavior during peak usage blows my sla for the whole month. – Andreas Jul 05 '16 at 03:46
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    @Andreas: A `LinkedList` *always* allocates five times the memory than a plain array of references, so an `ArrayList` temporarily requiring 2.5 times still consumes far less memory, even while the memory is not reclaimed. Since large array allocation bypasses the Eden space, they don’t have any impact on GC behavior, unless there is really not enough memory, in which case, the `LinkedList` blew up much earlier… – Holger Jul 05 '16 at 09:04
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Yeah, I know, this is an ancient question, but I'll throw in my two cents:

LinkedList is almost always the wrong choice, performance-wise. There are some very specific algorithms where a LinkedList is called for, but those are very, very rare and the algorithm will usually specifically depend on LinkedList's ability to insert and delete elements in the middle of the list relatively quickly, once you've navigated there with a ListIterator.

There is one common use case in which LinkedList outperforms ArrayList: that of a queue. However, if your goal is performance, instead of LinkedList you should also consider using an ArrayBlockingQueue (if you can determine an upper bound on your queue size ahead of time, and can afford to allocate all the memory up front), or this CircularArrayList implementation. (Yes, it's from 2001, so you'll need to generify it, but I got comparable performance ratios to what's quoted in the article just now in a recent JVM)

Daniel Martin
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    From Java 6 you can use `ArrayDeque`. http://docs.oracle.com/javase/6/docs/api/java/util/ArrayDeque.html – Thomas Ahle Dec 30 '11 at 15:01
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    `ArrayDeque` is slower than `LinkedList` unless all operations are at the same end. It's OK when used as a stack but it doesn't make a good queue. – Jeremy List Apr 30 '15 at 02:12
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    Untrue - at least for Oracle's implementation in jdk1.7.0_60 and in the following test. I created a test where I loop for 10 million times and I have a Deque of 10 million random Integers. Inside the loop I poll one element from and offer a constant element. On my computer, LinkedList is over 10 times slower than ArrayDeque and uses less memory). The reason is that unlike ArrayList, ArrayDeque keeps a pointer to the head of the array so that it doesn't have to move all elements when the head is removed. – Henno Vermeulen May 22 '15 at 10:18
  • This was in reply to Jeremy. Daniel is right. If I use a List as a queue in the same test, ArrayList is 300 times slower than LinkedList if I reduce both the loop and queue size to 300_000. I'm not even going to try the 10 million times. I guess the mentioned CircularArrayList is similar to ArrayDeque in keeping a pointer to the head instead of shifting elements. – Henno Vermeulen May 22 '15 at 10:28
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    `ArrayDeque` is likely to be faster than `Stack` when used as a stack, and faster than `LinkedList` when used as a queue. – akhil_mittal Jun 17 '15 at 15:44
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    Note that akhil_mittal's comment is a quote from the `ArrayDeque` documentation. – Stuart Marks Nov 28 '15 at 22:47
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It's an efficiency question. LinkedList is fast for adding and deleting elements, but slow to access a specific element. ArrayList is fast for accessing a specific element but can be slow to add to either end, and especially slow to delete in the middle.

Array vs ArrayList vs LinkedList vs Vector goes more in depth, as does Linked List.

Tudor
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dgtized
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    worth to mention here, that `LinkedList` is fast for adding/removing only at first and last positions - then complexity will be O(1), but adding in the middle still will be O(n), because we need to run through approx n/2 elements of `LinkedList`. – Dmitriy Fialkovskiy Dec 10 '20 at 10:02
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Joshua Bloch, the author of LinkedList:

Does anyone actually use LinkedList? I wrote it, and I never use it.

Link: https://twitter.com/joshbloch/status/583813919019573248

I'm sorry for the answer for being not that informative as the other answers, but I thought it would be the most interesting and self-explanatory.

Ruslan
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Correct or Incorrect: Please execute test locally and decide for yourself!

Edit/Remove is faster in LinkedList than ArrayList.

ArrayList, backed by Array, which needs to be double the size, is worse in large volume application.

Below is the unit test result for each operation.Timing is given in Nanoseconds.


Operation                       ArrayList                      LinkedList  

AddAll   (Insert)               101,16719                      2623,29291 

Add      (Insert-Sequentially)  152,46840                      966,62216

Add      (insert-randomly)      36527                          29193

remove   (Delete)               20,56,9095                     20,45,4904

contains (Search)               186,15,704                     189,64,981

Here's the code:

import org.junit.Assert;
import org.junit.Test;

import java.util.*;

public class ArrayListVsLinkedList {
    private static final int MAX = 500000;
    String[] strings = maxArray();

    ////////////// ADD ALL ////////////////////////////////////////
    @Test
    public void arrayListAddAll() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        watch.start();
        arrayList.addAll(stringList);
        watch.totalTime("Array List addAll() = ");//101,16719 Nanoseconds
    }

    @Test
    public void linkedListAddAll() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);

        watch.start();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(stringList);
        watch.totalTime("Linked List addAll() = ");  //2623,29291 Nanoseconds
    }

    //Note: ArrayList is 26 time faster here than LinkedList for addAll()

    ///////////////// INSERT /////////////////////////////////////////////
    @Test
    public void arrayListAdd() {
        Watch watch = new Watch();
        List<String> arrayList = new ArrayList<String>(MAX);

        watch.start();
        for (String string : strings)
            arrayList.add(string);
        watch.totalTime("Array List add() = ");//152,46840 Nanoseconds
    }

    @Test
    public void linkedListAdd() {
        Watch watch = new Watch();

        List<String> linkedList = new LinkedList<String>();
        watch.start();
        for (String string : strings)
            linkedList.add(string);
        watch.totalTime("Linked List add() = ");  //966,62216 Nanoseconds
    }

    //Note: ArrayList is 9 times faster than LinkedList for add sequentially

    /////////////////// INSERT IN BETWEEN ///////////////////////////////////////

    @Test
    public void arrayListInsertOne() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX + MAX / 10);
        arrayList.addAll(stringList);

        String insertString0 = getString(true, MAX / 2 + 10);
        String insertString1 = getString(true, MAX / 2 + 20);
        String insertString2 = getString(true, MAX / 2 + 30);
        String insertString3 = getString(true, MAX / 2 + 40);

        watch.start();

        arrayList.add(insertString0);
        arrayList.add(insertString1);
        arrayList.add(insertString2);
        arrayList.add(insertString3);

        watch.totalTime("Array List add() = ");//36527
    }

    @Test
    public void linkedListInsertOne() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(stringList);

        String insertString0 = getString(true, MAX / 2 + 10);
        String insertString1 = getString(true, MAX / 2 + 20);
        String insertString2 = getString(true, MAX / 2 + 30);
        String insertString3 = getString(true, MAX / 2 + 40);

        watch.start();

        linkedList.add(insertString0);
        linkedList.add(insertString1);
        linkedList.add(insertString2);
        linkedList.add(insertString3);

        watch.totalTime("Linked List add = ");//29193
    }


    //Note: LinkedList is 3000 nanosecond faster than ArrayList for insert randomly.

    ////////////////// DELETE //////////////////////////////////////////////////////
    @Test
    public void arrayListRemove() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        arrayList.addAll(stringList);
        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        arrayList.remove(searchString0);
        arrayList.remove(searchString1);
        watch.totalTime("Array List remove() = ");//20,56,9095 Nanoseconds
    }

    @Test
    public void linkedListRemove() throws Exception {
        Watch watch = new Watch();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(Arrays.asList(strings));

        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        linkedList.remove(searchString0);
        linkedList.remove(searchString1);
        watch.totalTime("Linked List remove = ");//20,45,4904 Nanoseconds
    }

    //Note: LinkedList is 10 millisecond faster than ArrayList while removing item.

    ///////////////////// SEARCH ///////////////////////////////////////////
    @Test
    public void arrayListSearch() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        arrayList.addAll(stringList);
        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        arrayList.contains(searchString0);
        arrayList.contains(searchString1);
        watch.totalTime("Array List addAll() time = ");//186,15,704
    }

    @Test
    public void linkedListSearch() throws Exception {
        Watch watch = new Watch();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(Arrays.asList(strings));

        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        linkedList.contains(searchString0);
        linkedList.contains(searchString1);
        watch.totalTime("Linked List addAll() time = ");//189,64,981
    }

    //Note: Linked List is 500 Milliseconds faster than ArrayList

    class Watch {
        private long startTime;
        private long endTime;

        public void start() {
            startTime = System.nanoTime();
        }

        private void stop() {
            endTime = System.nanoTime();
        }

        public void totalTime(String s) {
            stop();
            System.out.println(s + (endTime - startTime));
        }
    }


    private String[] maxArray() {
        String[] strings = new String[MAX];
        Boolean result = Boolean.TRUE;
        for (int i = 0; i < MAX; i++) {
            strings[i] = getString(result, i);
            result = !result;
        }
        return strings;
    }

    private String getString(Boolean result, int i) {
        return String.valueOf(result) + i + String.valueOf(!result);
    }
}
Azeem
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Ash
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    ArrayList need not to be doubled, to be precise. Please check the sources first. – Danubian Sailor May 06 '13 at 14:40
  • It should be noted that your example is flawed... You are removing from string of between: 18 + [2, 12] bytes ("true0false", "true500000false"), on average 25 bytes, which are the sizes of the elements in the middle. It's known that as element byte size increases linked list performs better, as list size increases, a contiguous array(list) will do better. Most importantly, you are doing .equals() on strings - which is not a cheap operation. If you instead used integers, I think there would be a difference. – Centril Aug 21 '14 at 09:40
  • - and that's probably also why there is so little difference for remove/contains. – Centril Aug 21 '14 at 09:46
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    "... *is worse in large volume application*": This is a misunderstanding. `LinkedList` has far more memory overhead because for every element there is a node object with five fields. On many systems that makes 20 bytes overhead. The average memory overhead per element for `ArrayList` is one and a half word, which makes 6 bytes, and 8 bytes in the worst case. – Lii Sep 15 '15 at 09:53
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    I've done a better version of your benchmark [here, with results](https://gist.github.com/svanoort/4256d1801d97a2b7eef3) - the append-on-end performance for the arraylist is artificially low for yours, because addAll is giving a storage array of EXACTLY initial size, so the first insert always triggers an arraycopy. Also, this includes warmup cycles to allow for JIT compilation before data is collected. – BobMcGee Mar 10 '16 at 18:48
  • `Edit/Remove is faster in LinkedList than ArrayList.` That's a bit too simplified. It depends heavily on where the removal is happening, if it is at the end then ArrayList will be faster, because there is no extra object that has to be GCed at some point. – Xerus May 27 '18 at 20:20
  • `ArrayList, backed by Array, which needs to be double the size, is worse in large volume application.` The opposite is true. An array has much less overhead than an additional object created for _each element in the list_, which is what linkedList does. – Xerus May 27 '18 at 20:21
  • LinkedList has a specific (if short) set of uses. Try performance of deleting WHILE you are iterating over a linked list (iterator.remove()). The performance difference should be immense. Also create a list of a few million items using only "addFirst" and see what you get. (ArrayList obviously shouldn't even have an add first because it's such a dumb thing to do on an arraylist.) – Bill K Sep 20 '18 at 16:11
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    @BillK since Java 8, you can use `removeIf(element -> condition)` where it fits, which can be significantly faster for an `ArrayList`, compared to looping and removing via iterator, as it is not required to shift the entire remainder for every individual element. Whether this performs better or worse than `LinkedList` depends on the particular scenario, as a `LinkedList` is O(1) in theory, but removing just a single node requires several memory accesses, which can easily exceed the number needed for the `ArrayList` when removing a significant number of elements. – Holger May 14 '19 at 17:05
55

ArrayList is essentially an array. LinkedList is implemented as a double linked list.

The get is pretty clear. O(1) for ArrayList, because ArrayList allow random access by using index. O(n) for LinkedList, because it needs to find the index first. Note: there are different versions of add and remove.

LinkedList is faster in add and remove, but slower in get. In brief, LinkedList should be preferred if:

  1. there are no large number of random access of element
  2. there are a large number of add/remove operations

=== ArrayList ===

  • add(E e)
    • add at the end of ArrayList
    • require memory resizing cost.
    • O(n) worst, O(1) amortized
  • add(int index, E element)
    • add to a specific index position
    • require shifting & possible memory resizing cost
    • O(n)
  • remove(int index)
    • remove a specified element
    • require shifting & possible memory resizing cost
    • O(n)
  • remove(Object o)
    • remove the first occurrence of the specified element from this list
    • need to search the element first, and then shifting & possible memory resizing cost
    • O(n)

=== LinkedList ===

  • add(E e)

    • add to the end of the list
    • O(1)
  • add(int index, E element)

    • insert at specified position
    • need to find the position first
    • O(n)
  • remove()
    • remove first element of the list
    • O(1)
  • remove(int index)
    • remove element with specified index
    • need to find the element first
    • O(n)
  • remove(Object o)
    • remove the first occurrence of the specified element
    • need to find the element first
    • O(n)

Here is a figure from programcreek.com (add and remove are the first type, i.e., add an element at the end of the list and remove the element at the specified position in the list.):

enter image description here

Premraj
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Ryan
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42

TL;DR due to modern computer architecture, ArrayList will be significantly more efficient for nearly any possible use-case - and therefore LinkedList should be avoided except some very unique and extreme cases.


In theory, LinkedList has an O(1) for the add(E element)

Also adding an element in the mid of a list should be very efficient.

Practice is very different, as LinkedList is a Cache Hostile Data structure. From performance POV - there are very little cases where LinkedList could be better performing than the Cache-friendly ArrayList.

Here are results of a benchmark testing inserting elements in random locations. As you can see - the array list if much more efficient, although in theory each insert in the middle of the list will require "move" the n later elements of the array (lower values are better):

enter image description here

Working on a later generation hardware (bigger, more efficient caches) - the results are even more conclusive:

enter image description here

LinkedList takes much more time to accomplish the same job. source Source Code

There are two main reasons for this:

  1. Mainly - that the nodes of the LinkedList are scattered randomly across the memory. RAM ("Random Access Memory") isn't really random and blocks of memory need to be fetched to cache. This operation takes time, and when such fetches happen frequently - the memory pages in the cache need to be replaced all the time -> Cache misses -> Cache is not efficient. ArrayList elements are stored on continuous memory - which is exactly what the modern CPU architecture is optimizing for.

  2. Secondary LinkedList required to hold back/forward pointers, which means 3 times the memory consumption per value stored compared to ArrayList.

DynamicIntArray, btw, is a custom ArrayList implementation holding Int (primitive type) and not Objects - hence all data is really stored adjacently - hence even more efficient.

A key elements to remember is that the cost of fetching memory block, is more significant than the cost accessing a single memory cell. That's why reader 1MB of sequential memory is up to x400 times faster than reading this amount of data from different blocks of memory:

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD
Read 1 MB sequentially from memory     250,000   ns      250 us
Round trip within same datacenter      500,000   ns      500 us
Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
Read 1 MB sequentially from disk    20,000,000   ns   20,000 us   20 ms  80x memory, 20X SSD
Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms

Source: Latency Numbers Every Programmer Should Know

Just to make the point even clearer, please check the benchmark of adding elements to the beginning of the list. This is a use-case where, in-theory, the LinkedList should really shine, and ArrayList should present poor or even worse-case results:

enter image description here

Note: this is a benchmark of the C++ Std lib, but my previous experience shown the C++ and Java results are very similar. Source Code

Copying a sequential bulk of memory is an operation optimized by the modern CPUs - changing theory and actually making, again, ArrayList/Vector much more efficient


Credits: All benchmarks posted here are created by Kjell Hedström. Even more data can be found on his blog

Lior Bar-On
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  • I wouldn't call a queue unique or extreme! A fifo queue is much easier implemented on a LinkedList instead of an ArrayList. It's actually a nightmare on an ArrayList as you have to track your own start, stop and do your own reallocating, you might as well use an array, but a Linked List IS a fifo. I'm not sure about Java's implementation, but a LinkedList can do O(1) for both queue and dequeue operations (Requires a special pointer to the tail element for the remove, which I assume java has but I haven't double-checked.) – Bill K Dec 28 '18 at 18:26
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    inserting into the middle of a `ArrayList` array uses the native method `java.lang.System.arraycopy()` which is written in C++ in the OpenJDK. so while in theory a `LinkedList` has less work to do in practice there are so many extra-linguistic mechanisms that make "Big O" largely irrelevant. Particularly how cache friendly things are as per this excellent answer. – simbo1905 Feb 20 '21 at 12:30
36

ArrayList is randomly accessible, while LinkedList is really cheap to expand and remove elements from. For most cases, ArrayList is fine.

Unless you've created large lists and measured a bottleneck, you'll probably never need to worry about the difference.

Azeem
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Dustin
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    LinkedList is not cheap to add elements to. It is almost always quicker to add a million elements to an ArrayList than to add them to a LinkedList. And most lists in real-world code are not even a million elements long. – Porculus Sep 10 '10 at 17:21
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    At any given point, you know the cost of adding an item to your LinkedList. The ArrayList you do not (in general). Adding a single item to an ArrayList containing a million items *could* take a very long time -- it's an O(n) operation plus double the storage unless you preallocated space. Adding an item to a LinkedList is O(1). My last statement stands. – Dustin Sep 10 '10 at 23:03
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    Adding a single item to an ArrayList is O(1) no matter it is 1 million or 1 billion. Adding an item to a LinkedList is also O(1). "Adding" means ADDING TO THE END. – kachanov May 13 '12 at 14:36
  • You must've read the implementation differently than I do. In my experience, copying a 1 billion element array takes longer than copying a 1 million element array. – Dustin May 14 '12 at 05:57
  • when you add element you add it at the end of the array. there is no copying at all. Copying (shifting) happens when you INSERT into the array. – kachanov May 14 '12 at 14:25
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    @kachanov you must misunderstand Dustin. Unless you have declared an array of 1 billion items you will eventually need to resize your array in which case you will need to copy all elements into a new bigger array hence sometimes you will get O (N) however with a linked list you will always get O (1) – Stan R. Mar 18 '13 at 21:51
  • @Stan R, you must have misunderstood me. If I declare an arry of 1 billion items and adding 99999th item at the end, there is no copying to a bigger array and no resizing. – kachanov Apr 11 '13 at 00:23
  • @Dustin:For `LinkedList` class , I see in Oracle JDK-8 that methods with label - **Positional Access Operations** are implemented - `public E get(int index)` , `public E set(int index, E element)` , `public void add(int index, E element)` & `public E remove(int index)` so I am confused about your statement that only **ArrayList is randomly accessible**. even though you haven't specifically said that LinkedList is not randomly accessible but I guess, you meant that. – Sabir Khan Mar 12 '18 at 11:17
  • Dustin is of course correct that adding to the end of an `ArrayList` is O(n) in the worst case. Most of the other commenters are talking about the O(1) amortized complexity of the same operation. So adding to the end of an `ArrayList` might be faster on average. – Guildenstern Feb 23 '21 at 20:10
25

If your code has add(0) and remove(0), use a LinkedList and it's prettier addFirst() and removeFirst() methods. Otherwise, use ArrayList.

And of course, Guava's ImmutableList is your best friend.

Azeem
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Jesse Wilson
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I usually use one over the other based on the time complexities of the operations that I'd perform on that particular List.

|---------------------|---------------------|--------------------|------------|
|      Operation      |     ArrayList       |     LinkedList     |   Winner   |
|---------------------|---------------------|--------------------|------------|
|     get(index)      |       O(1)          |         O(n)       | ArrayList  |
|                     |                     |  n/4 steps in avg  |            |
|---------------------|---------------------|--------------------|------------|
|      add(E)         |       O(1)          |         O(1)       | LinkedList |
|                     |---------------------|--------------------|            |
|                     | O(n) in worst case  |                    |            |
|---------------------|---------------------|--------------------|------------|
|    add(index, E)    |       O(n)          |         O(n)       | LinkedList |
|                     |     n/2 steps       |      n/4 steps     |            |
|                     |---------------------|--------------------|            |
|                     |                     |  O(1) if index = 0 |            |
|---------------------|---------------------|--------------------|------------|
|  remove(index, E)   |       O(n)          |         O(n)       | LinkedList |
|                     |---------------------|--------------------|            |
|                     |     n/2 steps       |      n/4 steps     |            |
|---------------------|---------------------|--------------------|------------|
|  Iterator.remove()  |       O(n)          |         O(1)       | LinkedList |
|  ListIterator.add() |                     |                    |            |
|---------------------|---------------------|--------------------|------------|


|--------------------------------------|-----------------------------------|
|              ArrayList               |            LinkedList             |
|--------------------------------------|-----------------------------------|
|     Allows fast read access          |   Retrieving element takes O(n)   |
|--------------------------------------|-----------------------------------|
|   Adding an element require shifting | o(1) [but traversing takes time]  |
|       all the later elements         |                                   |
|--------------------------------------|-----------------------------------|
|   To add more elements than capacity |
|    new array need to be allocated    |
|--------------------------------------|
Gayan Weerakutti
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    The ArrayDeque balances things a bit more towards the arrays since insert/remove front/back are all O(1) the only thing Linked List still wins at is adding/removing while traversing (the Iterator operations). – Bill K Feb 21 '19 at 18:24
22

I know this is an old post, but I honestly can't believe nobody mentioned that LinkedList implements Deque. Just look at the methods in Deque (and Queue); if you want a fair comparison, try running LinkedList against ArrayDeque and do a feature-for-feature comparison.

Azeem
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Ajax
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Let's compare LinkedList and ArrayList w.r.t. below parameters:

1. Implementation

ArrayList is the resizable array implementation of list interface , while

LinkedList is the Doubly-linked list implementation of the list interface.


2. Performance

  • get(int index) or search operation

    ArrayList get(int index) operation runs in constant time i.e O(1) while

    LinkedList get(int index) operation run time is O(n) .

    The reason behind ArrayList being faster than LinkedList is that ArrayList uses an index based system for its elements as it internally uses an array data structure, on the other hand,

    LinkedList does not provide index-based access for its elements as it iterates either from the beginning or end (whichever is closer) to retrieve the node at the specified element index.

  • insert() or add(Object) operation

    Insertions in LinkedList are generally fast as compare to ArrayList. In LinkedList adding or insertion is O(1) operation .

    While in ArrayList, if the array is the full i.e worst case, there is an extra cost of resizing array and copying elements to the new array, which makes runtime of add operation in ArrayList O(n), otherwise it is O(1).

  • remove(int) operation

    Remove operation in LinkedList is generally the same as ArrayList i.e. O(n).

    In LinkedList, there are two overloaded remove methods. one is remove() without any parameter which removes the head of the list and runs in constant time O(1). The other overloaded remove method in LinkedList is remove(int) or remove(Object) which removes the Object or int passed as a parameter. This method traverses the LinkedList until it found the Object and unlink it from the original list. Hence this method runtime is O(n).

    While in ArrayList remove(int) method involves copying elements from the old array to new updated array, hence its runtime is O(n).


3. Reverse Iterator

LinkedList can be iterated in reverse direction using descendingIterator() while

there is no descendingIterator() in ArrayList , so we need to write our own code to iterate over the ArrayList in reverse direction.


4. Initial Capacity

If the constructor is not overloaded, then ArrayList creates an empty list of initial capacity 10, while

LinkedList only constructs the empty list without any initial capacity.


5. Memory Overhead

Memory overhead in LinkedList is more as compared to ArrayList as a node in LinkedList needs to maintain the addresses of the next and previous node. While

In ArrayList each index only holds the actual object(data).


Source

Yoon5oo
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Abhijeet Ashok Muneshwar
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20

Here is the Big-O notation in both ArrayList and LinkedList and also CopyOnWrite-ArrayList:

ArrayList

get                 O(1)
add                 O(1)
contains            O(n)
next                O(1)
remove              O(n)
iterator.remove     O(n)

LinkedList

get                 O(n)
add                 O(1)
contains            O(n)
next                O(1)
remove              O(1)
iterator.remove     O(1)

CopyOnWrite-ArrayList

get                 O(1)
add                 O(n)
contains            O(n)
next                O(1)
remove              O(n)
iterator.remove     O(n)

Based on these you have to decide what to choose. :)

Azeem
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Rajith Delantha
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15

In addition to the other good arguments above, you should notice ArrayList implements RandomAccess interface, while LinkedList implements Queue.

So, somehow they address slightly different problems, with difference of efficiency and behavior (see their list of methods).

Azeem
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PhiLho
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11

It depends upon what operations you will be doing more on the List.

ArrayList is faster to access an indexed value. It is much worse when inserting or deleting objects.

To find out more, read any article that talks about the difference between arrays and linked lists.

Azeem
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Matthew Schinckel
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    To find out more do not read, just write the code. and you will find out that ArrayList implementation is faster then LinkedList in insertion and deletion. – kachanov May 18 '12 at 02:53
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An array list is essentially an array with methods to add items etc. (and you should use a generic list instead). It is a collection of items which can be accessed through an indexer (for example [0]). It implies a progression from one item to the next.

A linked list specifies a progression from one item to the next (Item a -> item b). You can get the same effect with an array list, but a linked list absolutely says what item is supposed to follow the previous one.

kemiller2002
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9

See the Java Tutorials - List Implementations.

chharvey
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    Hi @chharvey , Link only answers get 6 Upvotes ? Please add some points that could support the link .What if oracle changes their link? –  Nov 14 '17 at 06:08
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An important feature of a linked list (which I didn't read in another answer) is the concatenation of two lists. With an array this is O(n) (+ overhead of some reallocations) with a linked list this is only O(1) or O(2) ;-)

Important: For Java its LinkedList this is not true! See Is there a fast concat method for linked list in Java?

Community
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Karussell
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    How is that? This may be true with linked list data structures but not a Java LinkList object. You can't just point a `next` from one list to the first node in the second list. The only way is to use `addAll()` which adds elements sequentially, though it is better than looping through and calling `add()` for each element. To do this quickly in O(1) you would need a compositing class (like org.apache.commons.collections.collection.CompositeCollection) but then this would work for any kind of List/Collection. – Kevin Brock Mar 23 '10 at 00:42
  • yes, true. I edited the answer accordingly. but see this answer for 'how' to do it with LinkedList: http://stackoverflow.com/questions/2494031/is-there-a-fast-concat-method-for-linked-list-in-java/2494884#2494884 – Karussell Mar 23 '10 at 12:47
8

ArrayList and LinkedList have their own pros and cons.

ArrayList uses contiguous memory address compared to LinkedList which uses pointers toward the next node. So when you want to look up an element in an ArrayList is faster than doing n iterations with LinkedList.

On the other hand, insertion and deletion in a LinkedList are much easier because you just have to change the pointers whereas an ArrayList implies the use of shift operation for any insertion or deletion.

If you have frequent retrieval operations in your app use an ArrayList. If you have frequent insertion and deletion use a LinkedList.

Nesan Mano
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7

1) Underlying Data Structure

The first difference between ArrayList and LinkedList comes with the fact that ArrayList is backed by Array while LinkedList is backed by LinkedList. This will lead to further differences in performance.

2) LinkedList implements Deque

Another difference between ArrayList and LinkedList is that apart from the List interface, LinkedList also implements Deque interface, which provides first in first out operations for add() and poll() and several other Deque functions. 3) Adding elements in ArrayList Adding element in ArrayList is O(1) operation if it doesn't trigger re-size of Array, in which case it becomes O(log(n)), On the other hand, appending an element in LinkedList is O(1) operation, as it doesn't require any navigation.

4) Removing an element from a position

In order to remove an element from a particular index e.g. by calling remove(index), ArrayList performs a copy operation which makes it close to O(n) while LinkedList needs to traverse to that point which also makes it O(n/2), as it can traverse from either direction based upon proximity.

5) Iterating over ArrayList or LinkedList

Iteration is the O(n) operation for both LinkedList and ArrayList where n is a number of an element.

6) Retrieving element from a position

The get(index) operation is O(1) in ArrayList while its O(n/2) in LinkedList, as it needs to traverse till that entry. Though, in Big O notation O(n/2) is just O(n) because we ignore constants there.

7) Memory

LinkedList uses a wrapper object, Entry, which is a static nested class for storing data and two nodes next and previous while ArrayList just stores data in Array.

So memory requirement seems less in the case of ArrayList than LinkedList except for the case where Array performs the re-size operation when it copies content from one Array to another.

If Array is large enough it may take a lot of memory at that point and trigger Garbage collection, which can slow response time.

From all the above differences between ArrayList vs LinkedList, It looks ArrayList is the better choice than LinkedList in almost all cases, except when you do a frequent add() operation than remove(), or get().

It's easier to modify a linked list than ArrayList, especially if you are adding or removing elements from start or end because linked list internally keeps references of those positions and they are accessible in O(1) time.

In other words, you don't need to traverse through the linked list to reach the position where you want to add elements, in that case, addition becomes O(n) operation. For example, inserting or deleting an element in the middle of a linked list.

In my opinion, use ArrayList over LinkedList for most of the practical purpose in Java.

Wolfson
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Anjali Suman
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    I think this is the best stated answer of the entire group here. It's accurate and informative. I would suggest changing the last line--at the end add "aside from queues" which are very important structures that really don't make sense for a linked list at all. – Bill K Dec 28 '18 at 18:33
6

I have read the responses, but there is one scenario where I always use a LinkedList over an ArrayList that I want to share to hear opinions:

Every time I had a method that returns a list of data obtained from a DB I always use a LinkedList.

My rationale was that because it is impossible to know exactly how many results am I getting, there will be not memory wasted (as in ArrayList with the difference between the capacity and actual number of elements), and there would be no time wasted trying to duplicate the capacity.

As far a ArrayList, I agree that at least you should always use the constructor with the initial capacity, to minimize the duplication of the arrays as much as possible.

gaijinco
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Operation get(i) in ArrayList is faster than LinkedList, because:
ArrayList: Resizable-array implementation of the List interface
LinkedList: Doubly-linked list implementation of the List and Deque interfaces

Operations that index into the list will traverse the list from the beginning or the end, whichever is closer to the specified index.

L Joey
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Amitābha
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5

ArrayList and LinkedList both implements List interface and their methods and results are almost identical. However there are few differences between them which make one better over another depending on the requirement.

ArrayList Vs LinkedList

1) Search: ArrayList search operation is pretty fast compared to the LinkedList search operation. get(int index) in ArrayList gives the performance of O(1) while LinkedList performance is O(n).

Reason: ArrayList maintains index based system for its elements as it uses array data structure implicitly which makes it faster for searching an element in the list. On the other side LinkedList implements doubly linked list which requires the traversal through all the elements for searching an element.

2) Deletion: LinkedList remove operation gives O(1) performance while ArrayList gives variable performance: O(n) in worst case (while removing first element) and O(1) in best case (While removing last element).

Conclusion: LinkedList element deletion is faster compared to ArrayList.

Reason: LinkedList’s each element maintains two pointers (addresses) which points to the both neighbor elements in the list. Hence removal only requires change in the pointer location in the two neighbor nodes (elements) of the node which is going to be removed. While In ArrayList all the elements need to be shifted to fill out the space created by removed element.

3) Inserts Performance: LinkedList add method gives O(1) performance while ArrayList gives O(n) in worst case. Reason is same as explained for remove.

4) Memory Overhead: ArrayList maintains indexes and element data while LinkedList maintains element data and two pointers for neighbor nodes

hence the memory consumption is high in LinkedList comparatively.

There are few similarities between these classes which are as follows:

  • Both ArrayList and LinkedList are implementation of List interface.
  • They both maintain the elements insertion order which means while displaying ArrayList and LinkedList elements the result set would be having the same order in which the elements got inserted into the List.
  • Both these classes are non-synchronized and can be made synchronized explicitly by using Collections.synchronizedList method.
  • The iterator and listIterator returned by these classes are fail-fast (if list is structurally modified at any time after the iterator is created, in any way except through the iterator’s own remove or add methods, the iterator will throw a ConcurrentModificationException).

When to use LinkedList and when to use ArrayList?

  • As explained above the insert and remove operations give good performance (O(1)) in LinkedList compared to ArrayList(O(n)).

    Hence if there is a requirement of frequent addition and deletion in application then LinkedList is a best choice.

  • Search (get method) operations are fast in Arraylist (O(1)) but not in LinkedList (O(n))

    so If there are less add and remove operations and more search operations requirement, ArrayList would be your best bet.

Real73
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3

One of the tests I saw on here only conducts the test once. But what I have noticed is that you need to run these tests many times and eventually their times will converge. Basically the JVM needs to warm up. For my particular use case I needed to add/remove items to a list that grows to about 500 items. In my tests LinkedList came out faster, with LinkedList coming in around 50,000 NS and ArrayList coming in at around 90,000 NS... give or take. See the code below.

public static void main(String[] args) {
    List<Long> times = new ArrayList<>();
    for (int i = 0; i < 100; i++) {
        times.add(doIt());
    }
    System.out.println("avg = " + (times.stream().mapToLong(x -> x).average()));
}

static long doIt() {
    long start = System.nanoTime();
    List<Object> list = new LinkedList<>();
    //uncomment line below to test with ArrayList
    //list = new ArrayList<>();
    for (int i = 0; i < 500; i++) {
        list.add(i);
    }

    Iterator it = list.iterator();
    while (it.hasNext()) {
        it.next();
        it.remove();
    }
    long end = System.nanoTime();
    long diff = end - start;
    //uncomment to see the JVM warmup and get faster for the first few iterations
    //System.out.println(diff)
    return diff;
}
Jose Martinez
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2

Both remove() and insert() have a runtime efficiency of O(n) for both ArrayLists and LinkedLists. However, the reason behind the linear processing time comes from two very different reasons:

In an ArrayList, you get to the element in O(1), but actually removing or inserting something makes it O(n) because all the following elements need to be changed.

In a LinkedList, it takes O(n) to actually get to the desired element, because we have to start at the very beginning until we reach the desired index. Actually removing or inserting is constant, because we only have to change 1 reference for remove() and 2 references for insert().

Which of the two is faster for inserting and removing depends on where it happens. If we are closer to the beginning the LinkedList will be faster, because we have to go through relatively few elements. If we are closer to the end an ArrayList will be faster, because we get there in constant time and only have to change the few remaining elements that follow it. When done precisely in the middle the LinkedList will be faster because going through n elements is quicker than moving n values.

Bonus: While there is no way of making these two methods O(1) for an ArrayList, there actually is a way to do this in LinkedLists. Let's say we want to go through the entire List removing and inserting elements on our way. Usually, you would start from the very beginning for each element using the LinkedList, we could also "save" the current element we're working on with an Iterator. With the help of the Iterator, we get an O(1) efficiency for remove() and insert() when working in a LinkedList. Making it the only performance benefit I'm aware of where a LinkedList is always better than an ArrayList.

Wolfson
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pietz
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1

ArrayList extends AbstractList and implements the List Interface. ArrayList is dynamic array.
It can be said that it was basically created to overcome the drawbacks of arrays

The LinkedList class extends AbstractSequentialList and implements List,Deque, and Queue interface.
Performance
arraylist.get() is O(1) whereas linkedlist.get() is O(n)
arraylist.add() is O(1) and linkedlist.add() is 0(1)
arraylist.contains() is O(n) andlinkedlist.contains() is O(n)
arraylist.next() is O(1) and linkedlist.next() is O(1)
arraylist.remove() is O(n) whereas linkedlist.remove() is O(1)
In arraylist
iterator.remove() is O(n)
whereas In linkedlist
iterator.remove()is O(1)

Randhawa
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1

My rule of thumb is if I need a Collection (i.e. doesn't need to be a List) then use ArrayList if you know the size in advance, or can know the size confidently, or know that it won't vary much. If you need random access (i.e. you use get(index)) then avoid LinkedList. Basically, use LinkedList only if you don't need index access and don't know the (approximate) size of the collection you're allocating. Also if you're going to be making lots of additions and removals (again through the Collection interface) then LinkedList may be preferable.

Sina Madani
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-2

When should I use LinkedList? When working with stacks mostly, or when working with buffers. When should I use ArrayList? Only when working with indexes, otherwise you can use HashTable with linked list, then you get:

Hash table + linked list

  • Access by key O(1),
  • Insert by key O(1),
  • Remove by key O(1)
  • and there is a trick to implement RemoveAll / SetAll with O(1) when using versioning

It seems like a good solution, and in most of the cases it is, how ever you should know: HashTable takes a lot of disc space, so when you need to manage 1,000,000 elements list it can become a thing that matters. This can happen in server implementations, in clients it is rarely the case.

Also take a look at Red-Black-Tree

  • Random access Log(n),
  • Insert Log(n),
  • Remove Log(n)
Ilya Gazman
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    I wish I could give this more than one -1: LinkedList gives O(N) on all of insert, remove and random access because you have to traverse the list to get to the correct point first. Also it might surprise you to learn that hashmap/table use resizing arrays just like ArrayList and given that the most common usage of lists is to just be indexed by a number, using one of those over an ArrayList is the worst idea. – Numeron Jul 29 '13 at 06:40
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    @Numeron you are right, it wasn't clear what I answered. Indeed when you try accessing linked list by index, it will be O(n), how ever I meant inserting to linked list by items. Then it's O(1) and also interacting over all the list it's same as array list. – Ilya Gazman Oct 03 '13 at 06:58
-4

First of all use Vector instead ArrayList because you can overrite insureCapasity method , in ArrayList is private and add 1.5 size of current array https://docs.oracle.com/javase/8/docs/api/java/util/Vector.html#ensureCapacity-int-

in many case it can be better that linkedList, the las has big advantage one you insert data with high freqency so size of you list changes very fast and you can't allocate size for number elements. In the theory you can get error like not "enough memory" but in modern computers you have 16G and swaping disk, so if you list is billoins elements you can fail, comparing 15-20 years ago.

Boris Fain
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    ```Vector``` is slower compared to ```ArrayList``` because ```Vector``` is thread-safe. The best practice is not using a ```Vector``` unless thread safety is needed. ```Vector``` doubles its size by default, ```ArrayList``` multiplies its size by 3/2. See:https://stackoverflow.com/questions/17471913/java-vector-vs-arraylist-performance-test – Doga Oruc Oct 08 '20 at 08:29