Time complexity analysis of Java collection class

The blog of clayhub 2020-11-06 01:18:20
time complexity analysis java collection


introduction

The concept of progressive time complexity :
If there is a function f(n), Properly n Approaching infinity ,T(n)/ f(n) The limit value of is a constant not equal to zero , said f(n) yes T(n) Functions of the same order of magnitude of . Write it down as T(n)= O(f(n)), call O(f(n)) Is the incremental time complexity of the algorithm , Time complexity . Progressive time complexity in uppercase O To express , So it's also called big O notation .

Time complexity derivation principle :

  • If the run time is constant , With constant 1 Express .
  • Only the highest order term in the time function .
  • If the highest order term exists , Then the coefficient before the highest order term is omitted .

1、 List

1.1、ArrayList

  • add(E e) Method inserts... Directly at the end of the array , The time complexity is O(1)
  • add(int index, E element) Method to specify index insertion , There will be data movement , The time complexity is O(n)
  • get(int index) According to the index of the array , Time complexity O(1)
  • remove(int index) After deleting , There will be movement of data , Time complexity O(n)

1.2、LinkedList

  • add(E e) The tail interpolation , The time complexity is O(1)
  • add(int index, E element) Insert... At the specified location , Need to loop to get the insertion position , Time complexity O(n)
  • get(int index) Get the specified location node , Order traversal list , The time complexity is O(n)
  • remove() Delete header node , Time complexity O(1)

2、Set

2.1、HashSet

  • add(E e) The bottom is HashMap Of put(K key, V value) Method ,JDK1.8 Red black tree introduced , When hash The length of the list of nodes in the table reaches the treeling threshold 8 when , It will turn into a red black tree , The insertion time complexity is O(logn).

As long as the red and black trees are introduced , Insert 、 Delete 、 When looking for , The time complexity becomes O(logn).

2.2、TreeSet

The bottom layer is TreeMap, Use red black tree to achieve , The time complexity of insert delete search is O(logn).

2.3、LinkedHashSet

LinkedHashSet Inherited from LinkedHashSet, At the bottom LinkedHashMap, and LinkedHashMap Inherited from HashMap, So time complexity analysis and HashMap identical .

3、Map

Three common implementation classes HashMap,TreeMap,LinkedHashMap, Red and black trees have been introduced into the ground floor , The time complexity is also related to the red and black trees , Insert 、 Delete 、 Search for O(logn).

Reference resources

A set of pictures understand “ Time complexity ”
JAVA Set time complexity
Red and black trees ( One ) And The principle and algorithm are introduced in detail

tencent.jpg

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