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Runtime Complexity of Java Collections
Below are the Big O performance of common functions of different Java Collections.
List | Add | Remove | Get | Contains | Next | Data Structure
---------------------|------|--------|------|----------|------|---------------
ArrayList | O(1) | O(n) | O(1) | O(n) | O(1) | Array
LinkedList | O(1) | O(1) | O(n) | O(n) | O(1) | Linked List
CopyOnWriteArrayList | O(n) | O(n) | O(1) | O(n) | O(1) | Array
Set | Add | Remove | Contains | Next | Size | Data Structure
----------------------|----------|----------|----------|----------|------|-------------------------
HashSet | O(1) | O(1) | O(1) | O(h/n) | O(1) | Hash Table
LinkedHashSet | O(1) | O(1) | O(1) | O(1) | O(1) | Hash Table + Linked List
EnumSet | O(1) | O(1) | O(1) | O(1) | O(1) | Bit Vector
TreeSet | O(log n) | O(log n) | O(log n) | O(log n) | O(1) | Red-black tree
CopyOnWriteArraySet | O(n) | O(n) | O(n) | O(1) | O(1) | Array
ConcurrentSkipListSet | O(log n) | O(log n) | O(log n) | O(1) | O(n) | Skip List
Queue | Offer | Peak | Poll | Remove | Size | Data Structure
------------------------|----------|------|----------|--------|------|---------------
PriorityQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
LinkedList | O(1) | O(1) | O(1) | O(1) | O(1) | Array
ArrayDequeue | O(1) | O(1) | O(1) | O(n) | O(1) | Linked List
ConcurrentLinkedQueue | O(1) | O(1) | O(1) | O(n) | O(n) | Linked List
ArrayBlockingQueue | O(1) | O(1) | O(1) | O(n) | O(1) | Array
PriorirityBlockingQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
SynchronousQueue | O(1) | O(1) | O(1) | O(n) | O(1) | None!
DelayQueue | O(log n) | O(1) | O(log n) | O(n) | O(1) | Priority Heap
LinkedBlockingQueue | O(1) | O(1) | O(1) | O(n) | O(1) | Linked List
Map | Get | ContainsKey | Next | Data Structure
----------------------|----------|-------------|----------|-------------------------
HashMap | O(1) | O(1) | O(h / n) | Hash Table
LinkedHashMap | O(1) | O(1) | O(1) | Hash Table + Linked List
IdentityHashMap | O(1) | O(1) | O(h / n) | Array
WeakHashMap | O(1) | O(1) | O(h / n) | Hash Table
EnumMap | O(1) | O(1) | O(1) | Array
TreeMap | O(log n) | O(log n) | O(log n) | Red-black tree
ConcurrentHashMap | O(1) | O(1) | O(h / n) | Hash Tables
ConcurrentSkipListMap | O(log n) | O(log n) | O(1) | Skip List
@agrawalankit006
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agrawalankit006 commented Jul 11, 2019

Thankyou! Only a small mistake that I think is LinkedList remove is O(N) not O(1) because it first needs to find the node before deleting it.

@HUAZHEYINy
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HUAZHEYINy commented Aug 5, 2019

thanks !!!

@LisaFan18
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LisaFan18 commented Sep 14, 2019

Very useful. Thank you!

@VasilSokolov
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VasilSokolov commented Nov 1, 2019

Great!!! Thanks!

@MariaForester
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MariaForester commented Nov 17, 2019

Thanks a lot! Very helpful!

@zeiadzaf
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zeiadzaf commented Dec 21, 2019

This is great! Thanks
you might need to swap datastructure of ArrayDeque and LinkedList under Deque

@lucallero
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lucallero commented Feb 23, 2020

Awesome! Great reference, but its missing Stack.

Very helpful indeed.
Please, add the stack as @firstpixel mentioned.
Thanks.

@o-x-y-g-e-n
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o-x-y-g-e-n commented Mar 9, 2020

Thank you for this!

@Hydor
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Hydor commented Apr 1, 2020

Wow! Thank you! That's very helpful!

@priyodas12
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priyodas12 commented Apr 26, 2020

How O(1) for adding in arraylist?

@ssavva05
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ssavva05 commented May 24, 2020

Thanks, Great Resource! I have to build my Programs in a way that saves time!

@shyamzzp
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shyamzzp commented Aug 10, 2020

Thankyou! Only a small mistake that I think is LinkedList remove is O(N) not O(1) because it first needs to find the node before deleting it.

Correct

@ashtnemi448
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ashtnemi448 commented Sep 23, 2020

To the point. Thanks man!

@Barry36
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Barry36 commented Nov 2, 2020

just curious how about the complexity of ArrayList.addAll(Collection)? is it Constant time?

@mcanalesmayo
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mcanalesmayo commented Nov 11, 2020

just curious how about the complexity of ArrayList.addAll(Collection)? is it Constant time?

@Barry36 nope, it's O(M+N) where M = array size (the ArrayList) and N = collection size (the function argument Collection).

FYI, the source code of ArrayList.addAll in JDK 11:

    /**
     * Appends all of the elements in the specified collection to the end of
     * this list, in the order that they are returned by the
     * specified collection's Iterator.  The behavior of this operation is
     * undefined if the specified collection is modified while the operation
     * is in progress.  (This implies that the behavior of this call is
     * undefined if the specified collection is this list, and this
     * list is nonempty.)
     *
     * @param c collection containing elements to be added to this list
     * @return {@code true} if this list changed as a result of the call
     * @throws NullPointerException if the specified collection is null
     */
    public boolean addAll(Collection<? extends E> c) {
        Object[] a = c.toArray();
        modCount++;
        int numNew = a.length;
        if (numNew == 0)
            return false;
        Object[] elementData;
        final int s;
        if (numNew > (elementData = this.elementData).length - (s = size))
            elementData = grow(s + numNew);
        System.arraycopy(a, 0, elementData, s, numNew);
        size = s + numNew;
        return true;
    }
  1. In the very first line of code, it converts collection to array. If the collections is for example a LinkedList, this means it needs to iterate over all the elements and insert it into a new array, so this is already O(N).
  2. In the worst case scenario, the array (of the ArrayList) doesn't have enough capacity to "accommodate" the new elements to be added, so it needs to create a copy of the current elements into a new bigger array (O(M)).
  3. Finally, it uses System.arraycopy to copy the array of new elements (of the Collection) into the grown array (of the ArrayList). I didn't see the source code of the System.arraycopy function, but the easiest and most intuitive way of implementing an array copy is iterating over all elements, which makes it O(N) again. But even if the implementation of this had better time complexity, the overall time complexity of the addAll function would not change. Imagine System.arraycopy is O(1), the complexity of the whole function would still be O(M+N). And if the complexity of the System.arraycopy was O(N), overall complexity would still be O(M+N).

@kumaresan-perumal
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kumaresan-perumal commented Mar 24, 2021

good thanks

@kumaresan-perumal
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kumaresan-perumal commented Apr 12, 2021

Hi, can you please add Vector?

@davitescobedo
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davitescobedo commented May 3, 2021

How O(1) for adding in arraylist?

Being a list, you always add at the end and having an array as the underlying data structure access is O(1).

If you are asking about having to grow the array and the time in reallocating that memory and copying it, it is done through amortized complexity: each time we add an element that goes beyond the total size of the array, the capacity is doubled. So that way, most of the times you add a new element you just add at the end with O(1) and doing an average, the runtime is constant https://stackoverflow.com/a/45243529/15001063

@ahmedghallab
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ahmedghallab commented Jun 5, 2021

LinkedList remove is only O(1) if you use its iterator. standard remove(Object) is O(n)

Thankyou! Only a small mistake that I think is LinkedList remove is O(N) not O(1) because it first needs to find the node before deleting it.

Yes.

Check out this link:
https://stackoverflow.com/questions/7294634/what-are-the-time-complexities-of-various-data-structures

@zhengyin
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zhengyin commented Nov 12, 2021

thanks !!!

@oziris78
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oziris78 commented Nov 17, 2021

best gist ever!

@nowshad-hasan
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nowshad-hasan commented Mar 28, 2022

ArrayDeque's remove - O(n), how is that possible?
If you consider,remove(Object o), then it's OK to be O(n). But for E remove(), it is O(1).
For LinkedList, you wrote O(1), I think you consider E remove() not boolean remove(Object o) or E remove(int index). Because for that two operations, it is O(n).
This is also true for PriorityQueue's Remove(). which should be O(log(n))

@eldavimost
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eldavimost commented Mar 28, 2022

ArrayDeque's remove - O(n), how is that possible?
If you consider,remove(Object o), then it's OK to be O(n). But for E remove(), it is O(1).

It comes from shifting all elements to fill in the new empty space left after the element you remove.

@nowshad-hasan
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nowshad-hasan commented Mar 29, 2022

@eldavimost
From Javadoc,

Most ArrayDeque operations run in amortized constant time. Exceptions include remove, removeFirstOccurrence, removeLastOccurrence, contains, iterator.remove(), and the bulk operations, all of which run in linear time.

So, if you consider amortized, then you can say O(n), but most of the time, it's O(1)

@eldavimost
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eldavimost commented Mar 29, 2022

ArrayDeque's remove - O(n), how is that possible?
If you consider,remove(Object o), then it's OK to be O(n). But for E remove(), it is O(1).
For LinkedList, you wrote O(1), I think you consider E remove() not boolean remove(Object o) or E remove(int index). Because for that two operations, it is O(n). This is also true for PriorityQueue's Remove(). which should be O(log(n))

Sorry I misread it. I thought you meant E remove(int index) in ArrayDeque which I checked and doesn't exist. E remove() removes the first element and being a circular queue it's O(1) of course (same as E removeFirst() and E removeLast()), while remove(Object o), it's O(n) from doing a linear scan O(n) to find the element and then shift all the elements O(n).

I guess @psayre23 chose one of them to keep the formatting of the table?

@oziris78
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oziris78 commented Mar 29, 2022

@psayre23 could you change the file extension to .md and create a good looking table? I feel like a lot of people are using this gist and it would be really good if we got a better looking table than this. I can help you re-write it if you aren't comfortable with markdown too...

@oziris78
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oziris78 commented Mar 29, 2022

@upanshu21
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upanshu21 commented May 23, 2022

shouldn't the worst time complexity for ArrayList add() operation be O(n) as in the worst case the element might need to be inserted in the middle.

@davitescobedo
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davitescobedo commented May 24, 2022

shouldn't the worst time complexity for ArrayList add() operation be O(n) as in the worst case the element might need to be inserted in the middle.

I'm guessing the Add operation of the table refers to add(E e) in the ArrayList doc, which inserts an element at the end. I agree that add(int index, E element) it's an O(n) operation due to possibly needing to shift all elements to the right.

@YemaneHadis
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YemaneHadis commented Aug 1, 2022

very help full thanks

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