如何完成各种搜索树效率比较的代码
时间: 2023-06-16 07:06:31 浏览: 103
首先,需要实现各种搜索树,如二叉搜索树、AVL树、红黑树、B树、B+树等。可以使用各种编程语言来实现,比如C++、Java、Python等。以下以C++为例。
接下来,需要实现插入、删除、查找等操作,并统计其时间复杂度和执行时间。可以使用C++的chrono库来计时,代码如下:
```c++
#include <chrono>
#include <iostream>
#include "bst.h" // 自己实现的二叉搜索树头文件
#include "avl.h" // 自己实现的AVL树头文件
#include "rbt.h" // 自己实现的红黑树头文件
#include "btree.h" // 自己实现的B树头文件
#include "bplustree.h" // 自己实现的B+树头文件
using namespace std;
using namespace chrono;
int main() {
int n = 1000000; // 插入元素个数
int m = 10000; // 查询元素个数
int max_val = 1000000000; // 元素最大值
// 二叉搜索树
BST bst;
auto start = high_resolution_clock::now();
for (int i = 0; i < n; i++) {
bst.insert(rand() % max_val);
}
auto stop = high_resolution_clock::now();
auto duration = duration_cast<milliseconds>(stop - start);
cout << "BST insert " << n << " elements costs " << duration.count() << " ms" << endl;
start = high_resolution_clock::now();
for (int i = 0; i < m; i++) {
bst.find(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "BST find " << m << " elements costs " << duration.count() << " ms" << endl;
// AVL树
AVL avl;
start = high_resolution_clock::now();
for (int i = 0; i < n; i++) {
avl.insert(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "AVL insert " << n << " elements costs " << duration.count() << " ms" << endl;
start = high_resolution_clock::now();
for (int i = 0; i < m; i++) {
avl.find(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "AVL find " << m << " elements costs " << duration.count() << " ms" << endl;
// 红黑树
RBT rbt;
start = high_resolution_clock::now();
for (int i = 0; i < n; i++) {
rbt.insert(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "RBT insert " << n << " elements costs " << duration.count() << " ms" << endl;
start = high_resolution_clock::now();
for (int i = 0; i < m; i++) {
rbt.find(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "RBT find " << m << " elements costs " << duration.count() << " ms" << endl;
// B树
BTree btree(5); // 阶数为5的B树
start = high_resolution_clock::now();
for (int i = 0; i < n; i++) {
btree.insert(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "BTree insert " << n << " elements costs " << duration.count() << " ms" << endl;
start = high_resolution_clock::now();
for (int i = 0; i < m; i++) {
btree.find(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "BTree find " << m << " elements costs " << duration.count() << " ms" << endl;
// B+树
BPlusTree bplustree(5); // 阶数为5的B+树
start = high_resolution_clock::now();
for (int i = 0; i < n; i++) {
bplustree.insert(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "BPlusTree insert " << n << " elements costs " << duration.count() << " ms" << endl;
start = high_resolution_clock::now();
for (int i = 0; i < m; i++) {
bplustree.find(rand() % max_val);
}
stop = high_resolution_clock::now();
duration = duration_cast<milliseconds>(stop - start);
cout << "BPlusTree find " << m << " elements costs " << duration.count() << " ms" << endl;
return 0;
}
```
以上代码可以同时测试各种搜索树的插入和查找操作的效率。
最后,将代码编译运行即可获得各种搜索树的效率比较结果。