In database management systems, B+ trees

A B tree in DBMS is a specialized version of a balanced tree, a type of tree data structure used in databases to store and retrieve data efficiently. Balanced trees are designed to maintain a roughly equal number of keys at each level, which helps to keep search times as low as possible. B trees are a popular choice for use in database management systems(DBMS) because they offer a number of benefits over other types of balanced trees, including faster search times and better space utilization.

What are B Trees?

A B tree is a self-balancing, ordered tree data structure that stores data in a sorted fashion. Each node in a B tree can have a variable number of keys and child pointers, with the exception of the leaf nodes, which only have keys and no child pointers. The keys in a B tree are arranged in a specific order, with all keys in a given node being less than any of the keys in its right child and greater than any of the keys in its left child.

B 树的特点是每个节点具有大量的键，这有助于保持树的高度较小和搜索时间较快。此外，B 树使用“基于指针”的结构，意味着每个节点包含一组指针，这些指针指向其子节点，而不是将子节点存储在父节点中。这有助于减小每个节点的大小，并实现更好的空间利用。

如何在C 中实现B 树？

在C 中实现B 树需要定义一个节点类，该类包含树中每个节点的键和指针。节点类还应包括一个用于将新键插入树中的函数和一个用于在树中搜索特定键的函数。

示例

下面是一个B 树节点类在C 中的实现示例 -

class BPlusTreeNode {
public:
   int *keys; // Array of keys
   int t; // Minimum degree (defines the range for number of keys)
   BPlusTreeNode **C; // An array of child pointers
   int n; // Current number of keys
   bool leaf; // Is true when node is leaf. Otherwise false
   BPlusTreeNode(int _t, bool _leaf); // Constructor

   // A function to traverse all nodes in a subtree rooted with this node
   void traverse();

   // A function to search a key in subtree rooted with this node.
   BPlusTreeNode *search(int k); // returns NULL if k is not present.

   // A function to traverse all nodes in a subtree rooted with this node
   void traverse();
 
   // A function to search a key in subtree rooted with this node.
   BPlusTreeNode *search(int k);   // returns NULL if k is not present.
 
   // A function that returns the index of the first key that is greater
   // or equal to k
   int findKey(int k);
 
   // A utility function to insert a new key in the subtree rooted with
   // this node. The assumption is, the node must be non-full when this
   // function is called
   void insertNonFull(int k);
 
   // A utility function to split the child y of this node. i is index of y in
   // child array C[].  The Child y must be full when this function is called
   void splitChild(int i, BPlusTreeNode *y);
 
   // Make BPlusTree friend of this so that we can access private members of
   // this class in BPlusTree functions
   friend class BPlusTree;
};

接下来，可以定义B 树类，该类将包含用于在树中插入和搜索键的函数。B 树类还应包括指向树的根节点的指针，并且如果根节点不存在，则应包括创建新根节点的函数。

Example

Here is an example of how the B Tree class might be implemented in C −

class BPlusTree {
   BPlusTreeNode *root; // Pointer to root node
   int t; // Minimum degree
   public:
   // Constructor (Initializes tree as empty)
   BPlusTree(int _t) {
      root = NULL;
      t = _t;
   }
   // function to traverse the tree
   void traverse() {
      if (root != NULL) root->traverse();
   }
   // function to search a key in this tree
   BPlusTreeNode* search(int k) {
      return (root == NULL) ? NULL : root->search(k);
   }
   // The main function that inserts a new key in this B+ tree
   void insert(int k);
};

对于B 树类的插入函数将处理新节点的创建以及在必要时分裂节点以保持树的平衡。以下是一个示例：

how the insert function might be implemented −

void BPlusTree::insert(int k) {
   // If tree is empty
   if (root == NULL) {
      // Allocate memory for root
      root = new BPlusTreeNode(t, true);
      root->keys[0] = k; // Insert key
      root->n = 1; // Update number of keys in root
   } else // If tree is not empty
   {
      // If root is full, then tree grows in height
      if (root->n == 2*t-1) {
         
         // Allocate memory for new root
         BPlusTreeNode *s = new BPlusTreeNode(t, false);
        
         // Make old root as child of new root
          s->C[0] = root;
       
         // Split the old root and move 1 key to the new root
         s->splitChild(0, root);
         
         // New root has two children now. Decide which of the
         // two children is going to have new key
         int i = 0;
         if (s->keys[0] < k)
         i++;
         s->C[i]->insertNonFull(k);
        
         // Change root
         root = s;
      } else // If root is not full, call insertNonFull for root
      root->insertNonFull(k);
   }
}

B 树相对于B树的优势

B 树相对于B树的主要优势之一是其更好的空间利用率。因为B 树使用基于指针的结构，每个节点能够存储更多的键并且使用比B树节点更少的空间。这在空间有限的大型数据库中尤其有益。

此外，B 树具有比B树更快的搜索时间，因为它们具有较小的高度，这要归功于每个节点的更多键值。这意味着需要遍历的节点较少，以找到特定的键值，这可以显著减少大型数据库中的搜索时间。

Conclusion

总之，B 树是一种专门用于在数据库中高效存储和检索数据的平衡树数据结构。与其他类型的平衡树相比，它们提供更快的搜索时间和更好的空间利用率，因此在数据库管理系统中被广泛采用。

在C 中实现B 树涉及定义一个节点类和一个B 树类，两者都包含用于在树中插入和搜索键的函数。B 树相对于B树具有许多优势，包括更好的空间利用和更快的搜索时间，使它们成为管理大型数据库的有价值工具。

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