HashMap奪命14問，你能堅(jiān)持到第幾問？

final Node[] resize() {        //oldTab：引用擴(kuò)容前的哈希表        Node[] oldTab = table;        //oldCap：表示擴(kuò)容前的table數(shù)組的長度        int oldCap = (oldTab == null) ? 0 : oldTab.length;        //獲得舊哈希表的擴(kuò)容閾值        int oldThr = threshold;        //newCap:擴(kuò)容之后table數(shù)組大小        //newThr:擴(kuò)容之后下次觸發(fā)擴(kuò)容的條件        int newCap, newThr = 0;        //條件成立說明hashMap中的散列表已經(jīng)初始化過了，是一次正常擴(kuò)容        if (oldCap > 0) {            //判斷舊的容量是否大于等于最大容量，如果是，則無法擴(kuò)容，并且設(shè)置擴(kuò)容條件為int最大值，            //這種情況屬于非常少數(shù)的情況            if (oldCap >= MAXIMUM_CAPACITY) {                threshold = Integer.MAX_VALUE;                return oldTab;            }//設(shè)置newCap新容量為oldCap舊容量的二倍（<<1）,并且<最大容量，而且>=16，則新閾值等于舊閾值的兩倍            else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&                     oldCap >= DEFAULT_INITIAL_CAPACITY)                newThr = oldThr << 1; // double threshold        }        //如果oldCap=0并且邊界值大于0，說明散列表是null，但此時(shí)oldThr>0        //說明此時(shí)hashMap的創(chuàng)建是通過指定的構(gòu)造方法創(chuàng)建的,新容量直接等于閾值        //1.new HashMap(intitCap,loadFactor)        //2.new HashMap(initCap)        //3.new HashMap(map)        else if (oldThr > 0) // initial capacity was placed in threshold            newCap = oldThr;        //這種情況下oldThr=0;oldCap=0，說明沒經(jīng)過初始化，創(chuàng)建hashMap        //的時(shí)候是通過new HashMap()的方式創(chuàng)建的        else {               // zero initial threshold signifies using defaults            newCap = DEFAULT_INITIAL_CAPACITY;            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);        }        //newThr為0時(shí)，通過newCap和loadFactor計(jì)算出一個(gè)newThr        if (newThr == 0) {            //容量*0.75            float ft = (float)newCap * loadFactor;            newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?                      (int)ft : Integer.MAX_VALUE);        }        threshold = newThr;        @SuppressWarnings({"rawtypes","unchecked"})                //根據(jù)上面計(jì)算出的結(jié)果創(chuàng)建一個(gè)更長更大的數(shù)組            Node[] newTab = (Node[])new Node[newCap];        //將table指向新創(chuàng)建的數(shù)組        table = newTab;        //本次擴(kuò)容之前table不為null        if (oldTab != null) {            //對數(shù)組中的元素進(jìn)行遍歷            for (int j = 0; j < oldCap; ++j) {                //設(shè)置e為當(dāng)前node節(jié)點(diǎn)                Node e;                //當(dāng)前桶位數(shù)據(jù)不為空，但不能知道里面是單個(gè)元素，還是鏈表或紅黑樹，                //e = oldTab[j]，先用e記錄下當(dāng)前元素                if ((e = oldTab[j]) != null) {                    //將老數(shù)組j桶位置為空，方便回收                    oldTab[j] = null;                    //如果e節(jié)點(diǎn)不存在下一個(gè)節(jié)點(diǎn)，說明e是單個(gè)元素，則直接放置在新數(shù)組的桶位                    if (e.next == null)                        newTab[e.hash & (newCap - 1)] = e;                    //如果e是樹節(jié)點(diǎn)，證明該節(jié)點(diǎn)處于紅黑樹中                    else if (e instanceof TreeNode)                        ((TreeNode)e).split(this, newTab, j, oldCap);                    //e為鏈表節(jié)點(diǎn)，則對鏈表進(jìn)行遍歷                    else { // preserve order                        //低位鏈表：存放在擴(kuò)容之后的數(shù)組的下標(biāo)位置，與當(dāng)前數(shù)組下標(biāo)位置一致                        //loHead：低位鏈表頭節(jié)點(diǎn)                        //loTail低位鏈表尾節(jié)點(diǎn)                        Node loHead = null, loTail = null;                        //高位鏈表，存放擴(kuò)容之后的數(shù)組的下標(biāo)位置，=原索引+擴(kuò)容之前數(shù)組容量                        //hiHead:高位鏈表頭節(jié)點(diǎn)                        //hiTail:高位鏈表尾節(jié)點(diǎn)                        Node hiHead = null, hiTail = null;                        Node next;                        do {                            next = e.next;                            //oldCap為16:10000，與e.hsah做&運(yùn)算可以得到高位為1還是0                            //高位為0，放在低位鏈表                            if ((e.hash & oldCap) == 0) {                                if (loTail == null)                                    //loHead指向e                                    loHead = e;                                else                                    loTail.next = e;                                loTail = e;                            }                            //高位為1，放在高位鏈表                            else {                                if (hiTail == null)                                    hiHead = e;                                else                                    hiTail.next = e;                                hiTail = e;                            }                        } while ((e = next) != null);                        //低位鏈表已成，將頭節(jié)點(diǎn)loHead指向在原位                        if (loTail != null) {                            loTail.next = null;                            newTab[j] = loHead;                        }                        //高位鏈表已成，將頭節(jié)點(diǎn)指向新索引                        if (hiTail != null) {                            hiTail.next = null;                            newTab[j + oldCap] = hiHead;                        }                    }                }            }        }        return newTab;    }

 * Because TreeNodes are about twice the size of regular nodes, we * use them only when bins contain enough nodes to warrant use * (see TREEIFY_THRESHOLD). And when they become too small (due to * removal or resizing) they are converted back to plain bins.  In * usages with well-distributed user hashCodes, tree bins are * rarely used.  Ideally, under random hashCodes, the frequency of * nodes in bins follows a Poisson distribution * (http://en.wikipedia.org/wiki/Poisson_distribution) with a * parameter of about 0.5 on average for the default resizing * threshold of 0.75, although with a large variance because of * resizing granularity. Ignoring variance, the expected * occurrences of list size k are (exp(-0.5) * pow(0.5, k) / * factorial(k)).

因?yàn)闃涔?jié)點(diǎn)的大小大約是普通節(jié)點(diǎn)的兩倍，所以我們只在箱子包含足夠的節(jié)點(diǎn)時(shí)才使用樹節(jié)點(diǎn)（參見TREEIFY_THRESHOLD）。當(dāng)他們邊的太小（由于刪除或調(diào)整大小）時(shí)，就會(huì)被轉(zhuǎn)換回普通的桶，在使用分布良好的hashcode時(shí)，很少使用樹箱。理想情況下，在隨機(jī)哈希碼下，箱子中節(jié)點(diǎn)的頻率服從泊松分布第一個(gè)值是：
 * 0:    0.60653066 * 1:    0.30326533 * 2:    0.07581633 * 3:    0.01263606 * 4:    0.00157952 * 5:    0.00015795 * 6:    0.00001316 * 7:    0.00000094 * 8:    0.00000006 * more: less than 1 in ten million