b-tree | 易学教程

Keeping avl tree balanced without rotations

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问题 B Tree is self balancing tree like AVL tree. HERE we can see how left and right rotations are used to keep AVL tree balanced. And HERE is a link which explains insertion in B tree. This insertion technique does not involve any rotations, if I am not wrong, to keep tree balanced. And therefore it looks simpler. Question: Is there any similar (or any other technique without using rotations) to keep avl tree balanced ? 回答1: The answer is... yes and no. B-trees don't need to perform rotations

Print BTree by level

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问题 I am trying to create a Java applet that animates a BTree. I have code to create the tree but now I am trying to display it. I thought the easiest way would be to print by level but I can't figure out how. The below code is the constructor for my nodes. Also, if anyone has a better suggestion for displaying my tree I would appreciate it. /*********************************************************************** * Class BTNode * The BTNode is nothing else than a Node in the BTree. This nodes can

Haskell 2-3-4 Tree

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问题 We've been asked to create a 2-3-4 tree in Haskell, as in write the data type, the insert function, and a display function. I'm finding it very difficult to get information on this kind of tree, even in a language I'm comfortable with (Java, C++). What I have so far - data Tree t = Empty | Two t (Tree t)(Tree t) | Three t t (Tree t)(Tree t)(Tree t) | Four t t t (Tree t)(Tree t)(Tree t)(Tree t) deriving (Eq, Ord, Show) leaf2 a = Two a Empty Empty leaf3 a b = Three a b Empty Empty Empty leaf4 a

Non-clustered index and clustered index on the same column

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问题 I came across this post in Stackoverflow. The first answer mentions something like A clustered index has all the data for the table while a non clustered index only has the column + the location of the clustered index or the row if it is on a heap (a table without a clustered index). How can a non-clustered index have the location of the clustered index? It only contains the column values sorted as nodes in a B-treee with each node pinting to the row where the column has that node-value,

C++ post-increment operator overload in iterators (compiling with -Wall -Werror)

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问题 I'm currently creating my own iterator for a b-tree, and I'm stuck on how to implement the post-increment operator without the compiler complaining. The error message is as follows, and is expected (since I am doing exactly what the error message says) cc1plus: warnings being treated as errors error: reference to local variable 'temp' returned I am required to write the function with the -Wall and -Werror tags, so hopefully someone is able to help me with a solution around that. Here is the

How to decide order of b tree

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问题 B trees are said to be particularly useful in case of huge amount of data that cannot fit in main memory. My question is then how do we decide order of B tree or how many keys to store in a node ? Or how many children a node should have ? I came across that everywhere people are using 4/5 keys per node. How does it solve the huge data and disk read problem ? 回答1: Typically, you'd choose the order so that the resulting node is as large as possible while still fitting into the block device page

二叉查找树、平衡二叉树（AVLTree）、平衡多路查找树（B-Tree），B+树

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B+树索引是B+树在数据库中的一种实现，是最常见也是数据库中使用最为频繁的一种索引。 B+树中的B代表平衡（balance），而不是二叉（binary），因为B+树是从最早的平衡二叉树演化而来的。在讲B+树之前必须先了解二叉查找树、平衡二叉树（AVLTree）和平衡多路查找树（B-Tree），B+树即由这些树逐步优化而来。二叉查找树二叉树具有以下性质：左子树的键值小于根的键值，右子树的键值大于根的键值。如下图所示就是一棵二叉查找树，对该二叉树的节点进行查找发现深度为1的节点的查找次数为1，深度为2的查找次数为2，深度为n的节点的查找次数为n，因此其平均查找次数为 (1+2+2+3+3+3) / 6 = 2.3次二叉查找树可以任意地构造，同样是2,3,5,6,7,8这六个数字，也可以按照下图的方式来构造：但是这棵二叉树的查询效率就低了。因此若想二叉树的查询效率尽可能高，需要这棵二叉树是平衡的，从而引出新的定义——平衡二叉树，或称AVL树。平衡二叉树（AVL Tree）----（基于【二插树】改善，查询效率提高）平衡二叉树（AVL树）在符合二叉查找树的条件下，还满足任何节点的两个子树的高度最大差为1 。下面的两张图片：左边是AVL树，它的任何节点的两个子树的高度差<=1；右边的不是AVL树，其根节点的左子树高度为3，而右子树高度为1；

Why does CouchDB use an append-only B+ tree and not a HAMT

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问题 I'm reading up on datastructures, especially immutable ones like the append-only B+ tree used in CouchDB and the Hash array mapped trie used in Clojure and some other functional programming languages. The main reason datastructures that work well in memory might not work well on disk appears to be time spent on disk seeks due to fragmentation, as with a normal binary tree. However, HAMT is also very shallow, so doesn't require any more seeks than a B tree. Another suggested reason is that

Persisting B-Tree nodes to RandomAccessFile

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问题 My project is trying to write a B-Tree. I am having trouble persisting nodes of the tree to a random access file. I am constantly encountering EOFexceptions and StreamCorruptionExceptions . some resources that I am currently using are: Converting any object to a byte array in java https://inaved-momin.blogspot.com/2012/08/understanding-javaiostreamcorruptedexce.html current Problem: reading a link position from a node and then trying to read it from the random access file is causing a

Indexing count of buckets

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问题 So, here is my little problem. Let's say I have a list of buckets a 0 ... a n which respectively contain L <= c 0 ... c n < H items. I can decide of the L and H limits. I could even update them dynamically, though I don't think it would help much. The order of the buckets matter. I can't go and swap them around. Now, I'd like to index these buckets so that: I know the total count of items I can look-up the ith element I can add/remove items from any bucket and update the index efficiently