ArrayList是一个基于数组实现的链表(List),这一点可以从源码中看出:
transient Object[] elementData; // non-private to simplify nested class access
可以看出ArrayList的内部是给予数组来处理的。
从ArrayList中查找一个元素的index,其时间复杂度是o(n),其源码如下所示:
public int indexOf(Object o) { if (o == null) { for (int i = 0; i < size; i++) if (elementData[i]==null) return i; } else { for (int i = 0; i < size; i++) if (o.equals(elementData[i])) return i; } return -1; }
ArrayList支持Clone,是使用Arrays.copyOf(Object[],int)来进行的:
public Object clone() { try { ArrayList v = (ArrayList ) super.clone(); v.elementData = Arrays.copyOf(elementData, size); v.modCount = 0; return v; } catch (CloneNotSupportedException e) { // this shouldn't happen, since we are Cloneable throw new InternalError(e); } }
ArrayList中根据index获取数组的时间复杂度是o(1),其源码如下:
@SuppressWarnings("unchecked") E elementData(int index) { return (E) elementData[index]; } public E get(int index) { //看这里 rangeCheck(index); return elementData(index); }
替换指定的位置的元素,时间复杂度也是o(1):
public E set(int index, E element) { rangeCheck(index); E oldValue = elementData(index); elementData[index] = element; return oldValue; }
在末尾添加一个元素的时间复杂度也是o(1):
public boolean add(E e) { ensureCapacityInternal(size + 1); // Increments modCount!! elementData[size++] = e; return true; }
这里需要注意的是,其容量是可以扩展的,其可以扩展的最大容量是Integer.MAX_VALUE-8,由
int newCapacity = oldCapacity + (oldCapacity >> 1)
可以看出,每次是尝试扩容原来的1.5倍:
private void ensureCapacityInternal(int minCapacity) { if (elementData == DEFAULTCAPACITY_EMPTY_ELEMENTDATA) { minCapacity = Math.max(DEFAULT_CAPACITY, minCapacity); } ensureExplicitCapacity(minCapacity); } private void ensureExplicitCapacity(int minCapacity) { modCount++; // overflow-conscious code if (minCapacity - elementData.length > 0) grow(minCapacity); } private static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8; private void grow(int minCapacity) { // overflow-conscious code int oldCapacity = elementData.length; int newCapacity = oldCapacity + (oldCapacity >> 1); if (newCapacity - minCapacity < 0) newCapacity = minCapacity; if (newCapacity - MAX_ARRAY_SIZE > 0) newCapacity = hugeCapacity(minCapacity); // minCapacity is usually close to size, so this is a win: elementData = Arrays.copyOf(elementData, newCapacity); }
添加到指定index位置的时间复杂度是o(n),这里需要先把这个位置以及之后的元素统一向后移一位:
public void add(int index, E element) { rangeCheckForAdd(index); ensureCapacityInternal(size + 1); // Increments modCount!! System.arraycopy(elementData, index, elementData, index + 1, size - index); elementData[index] = element; size++; }
删除指定index位置的元素时间复杂度也是o(n),这里需要把这个元素之后的所有的元素向前移一位:
public E remove(int index) { rangeCheck(index); modCount++; E oldValue = elementData(index); int numMoved = size - index - 1; if (numMoved > 0) System.arraycopy(elementData, index+1, elementData, index, numMoved); elementData[--size] = null; // clear to let GC do its work return oldValue; }
删除一个元素的时间复杂度也是o(n),显示查出来这个元素,删除,之后是把后面的元素向前进一位:
public boolean remove(Object o) { if (o == null) { for (int index = 0; index < size; index++) if (elementData[index] == null) { fastRemove(index); return true; } } else { for (int index = 0; index < size; index++) if (o.equals(elementData[index])) { fastRemove(index); return true; } } return false; } private void fastRemove(int index) { modCount++; int numMoved = size - index - 1; if (numMoved > 0) System.arraycopy(elementData, index+1, elementData, index, numMoved); elementData[--size] = null; // clear to let GC do its work }
虽然在申明存储数组的时候,申明了不可被序列化,但是只要保存的对象是可序列化的,这个ArrayList还是可以序列化的:
private void writeObject(java.io.ObjectOutputStream s) throws java.io.IOException{ // Write out element count, and any hidden stuff int expectedModCount = modCount; s.defaultWriteObject(); // Write out size as capacity for behavioural compatibility with clone() s.writeInt(size); // Write out all elements in the proper order. for (int i=0; i0) { // be like clone(), allocate array based upon size not capacity ensureCapacityInternal(size); Object[] a = elementData; // Read in all elements in the proper order. for (int i=0; i
从以上的情况来看,ArrayList不是线程安全的,在进行index查找和最后插入的时候具有比较明显的时间复杂度优势。
但是,ArrayList的扩容操作,以及扩容产生的空间浪费一直是被人诟病的地方,另外在其中间进行插入的操作也不尽人意,时间复杂度是o(n)。