I use a lot of lists and arrays but I have yet to come across a scenario in which the array list couldn't be used just as easily as, if not easier than, the linked list. I was hoping someone could give me some examples of when the linked list is notably better.
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arrays
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arraylist
linked-list
I did some benchmarking, and found that the list class is actually faster than LinkedList for random inserting:
using System;
using System.Collections.Generic;
using System.Diagnostics;
namespace ConsoleApplication1
{
class Program
{
static void Main(string[] args)
{
int count = 20000;
Random rand = new Random(12345);
Stopwatch watch = Stopwatch.StartNew();
LinkedList<int> ll = new LinkedList<int>();
ll.AddLast(0);
for (int i = 1; i < count; i++)
{
ll.AddBefore(ll.Find(rand.Next(i)),i);
}
Console.WriteLine("LinkedList/Random Add: {0}ms", watch.ElapsedMilliseconds);
watch = Stopwatch.StartNew();
List<int> list = new List<int>();
list.Add(0);
for (int i = 1; i < count; i++)
{
list.Insert(list.IndexOf(rand.Next(i)), i);
}
Console.WriteLine("List/Random Add: {0}ms", watch.ElapsedMilliseconds);
Console.ReadLine();
}
}
}
It takes 900 ms for the linked list and 100ms for the list class.
It creates lists of subsequent integer numbers. Each new integer is inserted after a random number which is already in the list. Maybe the List class uses something better than just an array.
I think that main difference is whether you frequently need to insert or remove stuff from the top of the list.
With an array, if you remove something from the top of list than the complexity is o(n) because all of the indices of the array elements will have to shift.
With a linked list, it is o(1) because you need only create the node, reassign the head and assign the reference to next as the previous head.
When frequently inserting or removing at the end of the list, arrays are preferable because the complexity will be o(1), no reindexing is required, but for a linked list it will be o(n) because you need to go from the head to the last node.
I think that searching in both linked list and arrays will be o(log n) because you will be probably be using a binary search.
To add to the other answers, most array list implementations reserve extra capacity at the end of the list so that new elements can be added to the end of the list in O(1) time. When the capacity of an array list is exceeded, a new, larger array is allocated internally, and all the old elements are copied over. Usually, the new array is double the size of the old one. This means that on average, adding new elements to the end of an array list is an O(1) operation in these implementations. So even if you don't know the number of elements in advance, an array list may still be faster than a linked list for adding elements, as long as you are adding them at the end. Obviously, inserting new elements at arbitrary locations in an array list is still an O(n) operation.
Accessing elements in an array list is also faster than a linked list, even if the accesses are sequential. This is because array elements are stored in contiguous memory and can be cached easily. Linked list nodes can potentially be scattered over many different pages.
I would recommend only using a linked list if you know that you're going to be inserting or deleting items at arbitrary locations. Array lists will be faster for pretty much everything else.
Arrays, by far, are the most widely used data structures. However, linked lists prove useful in their own unique way where arrays are clumsy - or expensive, to say the least.
Linked lists are useful to implement stacks and queues in situations where their size is subject to vary. Each node in the linked list can be pushed or popped without disturbing the majority of the nodes. Same goes for insertion/deletion of nodes somewhere in the middle. In arrays, however, all the elements have to be shifted, which is an expensive job in terms of execution time.
Binary trees and binary search trees, hash tables, and tries are some of the data structures wherein - at least in C - you need linked lists as a fundamental ingredient for building them up.
However, linked lists should be avoided in situations where it is expected to be able to call any arbitrary element by its index.
Use linked list for Radix Sort over arrays and for polynomial operations.
1) 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.
2) 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.
Hmm, Arraylist can be used in cases like follows I guess:
For eg, you need to import and access all elements in a contact list (the size of which is unknown to you)
The advantage of lists appears if you need to insert items in the middle and don't want to start resizing the array and shifting things around.
You're correct in that this is typically not the case. I've had a few very specific cases like that, but not too many.
In reality memory locality has a huge performance influence in real processing.
The increased use of disk streaming in "big data" processing vs random access shows how structuring your application around this can dramatically improve performance on a larger scale.
If there is any way to access an array sequentially that is by far the best performing. Designing with this as a goal should be at least considered if performance is important.
Those are the most common used implementations of Collection.
ArrayList:
insert/delete at the end generally O(1) worst case O(n)
insert/delete in the middle O(n)
retrieve any position O(1)
LinkedList:
insert/delete in any position O(1) (note if you have a reference to the element)
retrieve in the middle O(n)
retrieve first or last element O(1)
Vector: don't use it. It is an old implementation similar to ArrayList but with all methods synchronized. It is not the correct approach for a shared list in a multithreading environment.
HashMap
insert/delete/retrieve by key in O(1)
TreeSet insert/delete/contains in O(log N)
HashSet insert/remove/contains/size in O(1)
In reality memory locality has a huge performance influence in real processing.
The increased use of disk streaming in "big data" processing vs random access shows how structuring your application around this can dramatically improve performance on a larger scale.
If there is any way to access an array sequentially that is by far the best performing. Designing with this as a goal should be at least considered if performance is important.
Arrays have O(1) random access, but are really expensive to add stuff onto or remove stuff from.
Linked lists are really cheap to add or remove items anywhere and to iterate, but random access is O(n).
A simple answer to the question can be given using these points:
Arrays are to be used when a collection of similar type data elements is required. Whereas, linked list is a collection of mixed type data linked elements known as nodes.
In array, one can visit any element in O(1) time. Whereas, in linked list we would need to traverse entire linked list from head to the required node taking O(n) time.
For arrays, a specific size needs to be declared initially. But linked lists are dynamic in size.
Hmm, Arraylist can be used in cases like follows I guess:
For eg, you need to import and access all elements in a contact list (the size of which is unknown to you)
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)
ArrayLists are good for write-once-read-many or appenders, but bad at add/remove from the front or middle.
Arrays have O(1) random access, but are really expensive to add stuff onto or remove stuff from.
Linked lists are really cheap to add or remove items anywhere and to iterate, but random access is O(n).
I think that main difference is whether you frequently need to insert or remove stuff from the top of the list.
With an array, if you remove something from the top of list than the complexity is o(n) because all of the indices of the array elements will have to shift.
With a linked list, it is o(1) because you need only create the node, reassign the head and assign the reference to next as the previous head.
When frequently inserting or removing at the end of the list, arrays are preferable because the complexity will be o(1), no reindexing is required, but for a linked list it will be o(n) because you need to go from the head to the last node.
I think that searching in both linked list and arrays will be o(log n) because you will be probably be using a binary search.
Arrays, by far, are the most widely used data structures. However, linked lists prove useful in their own unique way where arrays are clumsy - or expensive, to say the least.
Linked lists are useful to implement stacks and queues in situations where their size is subject to vary. Each node in the linked list can be pushed or popped without disturbing the majority of the nodes. Same goes for insertion/deletion of nodes somewhere in the middle. In arrays, however, all the elements have to be shifted, which is an expensive job in terms of execution time.
Binary trees and binary search trees, hash tables, and tries are some of the data structures wherein - at least in C - you need linked lists as a fundamental ingredient for building them up.
However, linked lists should be avoided in situations where it is expected to be able to call any arbitrary element by its index.
Arrays have O(1) random access, but are really expensive to add stuff onto or remove stuff from.
Linked lists are really cheap to add or remove items anywhere and to iterate, but random access is O(n).
Use linked list for Radix Sort over arrays and for polynomial operations.
To add to the other answers, most array list implementations reserve extra capacity at the end of the list so that new elements can be added to the end of the list in O(1) time. When the capacity of an array list is exceeded, a new, larger array is allocated internally, and all the old elements are copied over. Usually, the new array is double the size of the old one. This means that on average, adding new elements to the end of an array list is an O(1) operation in these implementations. So even if you don't know the number of elements in advance, an array list may still be faster than a linked list for adding elements, as long as you are adding them at the end. Obviously, inserting new elements at arbitrary locations in an array list is still an O(n) operation.
Accessing elements in an array list is also faster than a linked list, even if the accesses are sequential. This is because array elements are stored in contiguous memory and can be cached easily. Linked list nodes can potentially be scattered over many different pages.
I would recommend only using a linked list if you know that you're going to be inserting or deleting items at arbitrary locations. Array lists will be faster for pretty much everything else.
It all depends what type of operation you are doing while iterating , all data structures have trade off between time and memory and depending on our needs we should choose the right DS. So there are some cases where LinkedList are faster then array and vice versa . Consider the three basic operation on data structures.
Since array is index based data structure searching array.get(index) will take O(1) time while linkedlist is not index DS so you will need to traverse up to index , where index <=n , n is size of linked list , so array is faster the linked list when have random access of elements.
Q.So what's the beauty behind this ?
As Arrays are contiguous memory blocks, large chunks of them will be loaded into the cache upon first access this makes it comparatively quick to access remaining elements of the array,as much as we access the elements in array locality of reference also increases thus less catch misses, Cache locality refers to the operations being in the cache and thus execute much faster as compared to in memory,basically In array we maximize the chances of sequential element access being in the cache. While Linked lists aren't necessarily in contiguous blocks of memory, there's no guarantee that items which appear sequentially in the list are actually arranged near each-other in memory, this means fewer cache hits e.g. more cache misses because we need to read from memory for every access of linked list element which increases the time it takes to access them and degraded performance so if we are doing more random access operation aka searching , array will be fast as explained below.
This is easy and fast in LinkedList as insertion is O(1) operation in LinkedList (in Java) as compared to array, consider the case when array is full, we need to copy contents to new array if array gets full which makes inserting an element into ArrayList of O(n) in worst case, while ArrayList also needs to update its index if you insert something anywhere except at the end of array , in case of linked list we needn't to be resize it, you just need to update pointers.
It works like insertions and better in LinkedList than array.
Those are the most common used implementations of Collection.
ArrayList:
insert/delete at the end generally O(1) worst case O(n)
insert/delete in the middle O(n)
retrieve any position O(1)
LinkedList:
insert/delete in any position O(1) (note if you have a reference to the element)
retrieve in the middle O(n)
retrieve first or last element O(1)
Vector: don't use it. It is an old implementation similar to ArrayList but with all methods synchronized. It is not the correct approach for a shared list in a multithreading environment.
HashMap
insert/delete/retrieve by key in O(1)
TreeSet insert/delete/contains in O(log N)
HashSet insert/remove/contains/size in O(1)
Hmm, Arraylist can be used in cases like follows I guess:
For eg, you need to import and access all elements in a contact list (the size of which is unknown to you)
The advantage of lists appears if you need to insert items in the middle and don't want to start resizing the array and shifting things around.
You're correct in that this is typically not the case. I've had a few very specific cases like that, but not too many.
To add to the other answers, most array list implementations reserve extra capacity at the end of the list so that new elements can be added to the end of the list in O(1) time. When the capacity of an array list is exceeded, a new, larger array is allocated internally, and all the old elements are copied over. Usually, the new array is double the size of the old one. This means that on average, adding new elements to the end of an array list is an O(1) operation in these implementations. So even if you don't know the number of elements in advance, an array list may still be faster than a linked list for adding elements, as long as you are adding them at the end. Obviously, inserting new elements at arbitrary locations in an array list is still an O(n) operation.
Accessing elements in an array list is also faster than a linked list, even if the accesses are sequential. This is because array elements are stored in contiguous memory and can be cached easily. Linked list nodes can potentially be scattered over many different pages.
I would recommend only using a linked list if you know that you're going to be inserting or deleting items at arbitrary locations. Array lists will be faster for pretty much everything else.
Hmm, Arraylist can be used in cases like follows I guess:
For eg, you need to import and access all elements in a contact list (the size of which is unknown to you)
A simple answer to the question can be given using these points:
Arrays are to be used when a collection of similar type data elements is required. Whereas, linked list is a collection of mixed type data linked elements known as nodes.
In array, one can visit any element in O(1) time. Whereas, in linked list we would need to traverse entire linked list from head to the required node taking O(n) time.
For arrays, a specific size needs to be declared initially. But linked lists are dynamic in size.
It all depends what type of operation you are doing while iterating , all data structures have trade off between time and memory and depending on our needs we should choose the right DS. So there are some cases where LinkedList are faster then array and vice versa . Consider the three basic operation on data structures.
Since array is index based data structure searching array.get(index) will take O(1) time while linkedlist is not index DS so you will need to traverse up to index , where index <=n , n is size of linked list , so array is faster the linked list when have random access of elements.
Q.So what's the beauty behind this ?
As Arrays are contiguous memory blocks, large chunks of them will be loaded into the cache upon first access this makes it comparatively quick to access remaining elements of the array,as much as we access the elements in array locality of reference also increases thus less catch misses, Cache locality refers to the operations being in the cache and thus execute much faster as compared to in memory,basically In array we maximize the chances of sequential element access being in the cache. While Linked lists aren't necessarily in contiguous blocks of memory, there's no guarantee that items which appear sequentially in the list are actually arranged near each-other in memory, this means fewer cache hits e.g. more cache misses because we need to read from memory for every access of linked list element which increases the time it takes to access them and degraded performance so if we are doing more random access operation aka searching , array will be fast as explained below.
This is easy and fast in LinkedList as insertion is O(1) operation in LinkedList (in Java) as compared to array, consider the case when array is full, we need to copy contents to new array if array gets full which makes inserting an element into ArrayList of O(n) in worst case, while ArrayList also needs to update its index if you insert something anywhere except at the end of array , in case of linked list we needn't to be resize it, you just need to update pointers.
It works like insertions and better in LinkedList than array.
1) 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.
2) 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.
I did some benchmarking, and found that the list class is actually faster than LinkedList for random inserting:
using System;
using System.Collections.Generic;
using System.Diagnostics;
namespace ConsoleApplication1
{
class Program
{
static void Main(string[] args)
{
int count = 20000;
Random rand = new Random(12345);
Stopwatch watch = Stopwatch.StartNew();
LinkedList<int> ll = new LinkedList<int>();
ll.AddLast(0);
for (int i = 1; i < count; i++)
{
ll.AddBefore(ll.Find(rand.Next(i)),i);
}
Console.WriteLine("LinkedList/Random Add: {0}ms", watch.ElapsedMilliseconds);
watch = Stopwatch.StartNew();
List<int> list = new List<int>();
list.Add(0);
for (int i = 1; i < count; i++)
{
list.Insert(list.IndexOf(rand.Next(i)), i);
}
Console.WriteLine("List/Random Add: {0}ms", watch.ElapsedMilliseconds);
Console.ReadLine();
}
}
}
It takes 900 ms for the linked list and 100ms for the list class.
It creates lists of subsequent integer numbers. Each new integer is inserted after a random number which is already in the list. Maybe the List class uses something better than just an array.
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)
ArrayLists are good for write-once-read-many or appenders, but bad at add/remove from the front or middle.
Source: Stackoverflow.com