容器的扩容

 扩容的容器： ArrayList 、HashSet、TreeSet、HashMap、WeakHashMap 、Hashtable 再加一个常用的StringBuilder

  LinkedList它的底层是用双向链表实现的，没有初始化大小，也没有扩容的机制；

 TreeMap由红黑树实现，容量方面没有限制；

1.ArrayList 

底层实现为数组存储在内存中，线程不同步；新增元素时

private static int calculateCapacity(Object[] elementData, int minCapacity) {
        if (elementData == DEFAULTCAPACITY_EMPTY_ELEMENTDATA) {
            return Math.max(DEFAULT_CAPACITY, minCapacity);
        }
        return minCapacity;
    }
/*计算长度，如果为空，则取默认长度10与参数的最大值*/

　　判断如果容器装不下，则调用grow方法扩容。

private void grow(int minCapacity) {
    // overflow-conscious code
    int oldCapacity = elementData.length;
    int newCapacity = oldCapacity + (oldCapacity >> 1);//原长度+原长度右移一位（可以看成1.5倍）
    if (newCapacity - minCapacity < 0)
        newCapacity = minCapacity;
    if (newCapacity - MAX_ARRAY_SIZE > 0)
        newCapacity = hugeCapacity(minCapacity);//太长了就调hugeCapacity方法
    // minCapacity is usually close to size, so this is a win:
    elementData = Arrays.copyOf(elementData, newCapacity);
}

2.HashSet

 我看这个是直接调用的HashMap的put方法

public boolean add(E e) {
   return map.put(e, PRESENT)==null;
}

3.TreeSet

调用的是map类的：put(K key, V value);方法

public boolean add(E e) {
        return m.put(e, PRESENT)==null;
    }

4.HashMap

/**
     * Initializes or doubles table size.  If null, allocates in
     * accord with initial capacity target held in field threshold.
     * Otherwise, because we are using power-of-two expansion, the
     * elements from each bin must either stay at same index, or move
     * with a power of two offset in the new table.
     *
     * @return the table
     */

初始化或加倍表大小。如果为空，则在符合场阈值内的初始容量目标。否则，因为我们使用的是二次展开的能力每个bin中的元素必须保持在同一索引中，或者移动在新表中有两个偏移量的幂。

    final Node<K,V>[] resize() {
        Node<K,V>[] oldTab = table;
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        int oldThr = threshold;
        int newCap, newThr = 0;
        if (oldCap > 0) {
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }
            else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                     oldCap >= DEFAULT_INITIAL_CAPACITY)
                newThr = oldThr << 1; // double threshold
        }
        else if (oldThr > 0) // initial capacity was placed in threshold
            newCap = oldThr;
        else {               // zero initial threshold signifies using defaults
            newCap = DEFAULT_INITIAL_CAPACITY;
            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
        }
        if (newThr == 0) {
            float ft = (float)newCap * loadFactor;
            newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
                      (int)ft : Integer.MAX_VALUE);
        }
        threshold = newThr;
        @SuppressWarnings({"rawtypes","unchecked"})
        Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
        table = newTab;
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
                            next = e.next;
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            else {
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }

https://www.iteye.com/topic/539465　　

　　当hashmap中的元素越来越多的时候，碰撞的几率也就越来越高（因为数组的长度是固定的），所以为了提高查询的效率，就要对hashmap的数组进行扩容，数组扩容这个操作也会出现在ArrayList中，所以这是一个通用的操作，很多人对它的性能表示过怀疑，不过想想我们的“均摊”原理，就释然了，而在hashmap数组扩容之后，最消耗性能的点就出现了：原数组中的数据必须重新计算其在新数组中的位置，并放进去，这就是resize。

         那么hashmap什么时候进行扩容呢？当hashmap中的元素个数超过数组大小*loadFactor时，就会进行数组扩容，loadFactor的默认值为0.75，也就是说，默认情况下，数组大小为16，那么当hashmap中元素个数超过16*0.75=12的时候，就把数组的大小扩展为2*16=32，即扩大一倍，然后重新计算每个元素在数组中的位置，而这是一个非常消耗性能的操作，所以如果我们已经预知hashmap中元素的个数，那么预设元素的个数能够有效的提高hashmap的性能。比如说，我们有1000个元素new HashMap(1000), 但是理论上来讲new HashMap(1024)更合适，不过上面annegu已经说过，即使是1000，hashmap也自动会将其设置为1024。 但是new HashMap(1024)还不是更合适的，因为0.75*1000 < 1000, 也就是说为了让0.75 * size > 1000, 我们必须这样new HashMap(2048)才最合适，既考虑了&的问题，也避免了resize的问题。

5.WeakHashMap  

public V put(K key, V value) {
        Object k = maskNull(key);
        int h = hash(k);
        Entry<K,V>[] tab = getTable();
        int i = indexFor(h, tab.length);

        for (Entry<K,V> e = tab[i]; e != null; e = e.next) {
            if (h == e.hash && eq(k, e.get())) {
                V oldValue = e.value;
                if (value != oldValue)
                    e.value = value;
                return oldValue;
            }
        }
        modCount++;
        Entry<K,V> e = tab[i];
        tab[i] = new Entry<>(k, value, queue, h, e);
        if (++size >= threshold)
            resize(tab.length * 2);
        return null;
}

　　调用了他自己的resize方法，入参是当前table长度的二倍

void resize(int newCapacity) {
        Entry<K,V>[] oldTable = getTable();
        int oldCapacity = oldTable.length;
        if (oldCapacity == MAXIMUM_CAPACITY) {
            threshold = Integer.MAX_VALUE;
            return;
        }

        Entry<K,V>[] newTable = newTable(newCapacity);
        transfer(oldTable, newTable);
        table = newTable;

        /*
         * If ignoring null elements and processing ref queue caused massive
         * shrinkage, then restore old table.  This should be rare, but avoids
         * unbounded expansion of garbage-filled tables.
         */
        if (size >= threshold / 2) {
            threshold = (int)(newCapacity * loadFactor);
        } else {
            expungeStaleEntries();
            transfer(newTable, oldTable);
            table = oldTable;
        }
 }

　　

6.Hashtable 

 value不能为空，有synchronized

public synchronized V put(K key, V value) {
        // Make sure the value is not null
        if (value == null) {
            throw new NullPointerException();
        }

        // Makes sure the key is not already in the hashtable.
        Entry<?,?> tab[] = table;
        int hash = key.hashCode();
        int index = (hash & 0x7FFFFFFF) % tab.length;
        @SuppressWarnings("unchecked")
        Entry<K,V> entry = (Entry<K,V>)tab[index];
        for(; entry != null ; entry = entry.next) {
            if ((entry.hash == hash) && entry.key.equals(key)) {
                V old = entry.value;
                entry.value = value;
                return old;
            }
        }

        addEntry(hash, key, value, index);
        return null;
 }

　　

7.StringBuilder

左移一位+2

private int newCapacity(int minCapacity) {
        // overflow-conscious code
        int newCapacity = (value.length << 1) + 2;
        if (newCapacity - minCapacity < 0) {
            newCapacity = minCapacity;
        }
        return (newCapacity <= 0 || MAX_ARRAY_SIZE - newCapacity < 0)
            ? hugeCapacity(minCapacity)
            : newCapacity;
 }

　　

private void ensureCapacityInternal(int minimumCapacity) {
        // overflow-conscious code
        if (minimumCapacity - value.length > 0) {
            value = Arrays.copyOf(value,
                    newCapacity(minimumCapacity));
        }
    }

　　

@Override
    public AbstractStringBuilder append(CharSequence s, int start, int end) {
        if (s == null)
            s = "null";
        if ((start < 0) || (start > end) || (end > s.length()))
            throw new IndexOutOfBoundsException(
                "start " + start + ", end " + end + ", s.length() "
                + s.length());
        int len = end - start;
        ensureCapacityInternal(count + len);
        for (int i = start, j = count; i < end; i++, j++)
            value[j] = s.charAt(i);
        count += len;
        return this;
    }