1.TREEIFY_THRESHOLD 常量為什麼是 8 ?

參考

https://www.cnblogs.com/linghu-java/p/10598758.html

https://www.v2ex.com/t/651978

1.1 為什麼要從連結串列轉成紅黑樹

連結串列查詢效能是O(n)，而樹結構能將查詢效能提升到O(log(n))

1.2 為什麼一開始不用紅黑樹

• 當連結串列長度很小的時候，即使遍歷，速度也非常快，但是當連結串列長度不斷變長，肯定會對查詢效能有一定的影響，所以才需要轉成樹。
• TreeNodes佔用空間是普通Nodes的兩倍，所以只有當bin包含足夠多的節點時才會轉成TreeNodes

1.3TREEIFY_THRESHOLD 常量為什麼是 8

 * 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)). The first values are:
 *
 * 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
 

理想情況下隨機hashCode演算法下所有bin中節點的分佈會遵循泊松分佈。根據泊松分佈概率質量函式,一個雜湊桶達到 9 個元素的概率小於一千萬分之一



1.4 UNTREEIFY_THRESHOLD 為什麼是6

• 必須小於TREEIFY_THRESHOLD，如果都是 8,則可能陷入(樹化<=>樹退化)的死迴圈中. 若是 7,則當極端情況下(頻繁插入和刪除的都是同一個雜湊桶)對一個連結串列長度為 8 的的雜湊桶進行頻繁的刪除和插入，同樣也會導致頻繁的樹化<=>非樹化.
• 更低時，當連結串列長度很小的時候，即使遍歷，速度也非常快。而TreeNodes佔用空間是普通Nodes的兩倍。