算法 - 查找算法(顺序、折半、红黑树、AVL树、B+树、散列)
查找
顺序查找
查找算法原理:
顺序查找是一种简单的查找方法,从数组的第一个元素开始,依次比较每个元素,直到找到目标元素或者数组结束为止。
实现步骤:
- 从数组的第一个元素开始。
- 逐一比较数组中的元素与目标值。
- 如果找到目标值,返回其索引。
- 如果遍历完整个数组仍未找到,返回-1。
C语言代码:
#include <stdio.h>
int sequential_search(int arr[], int n, int target) {
for (int i = 0; i < n; i++) {
if (arr[i] == target) {
return i;
}
}
return -1;
}
int main() {
int arr[] = {2, 4, 6, 8, 10};
int target = 6;
int n = sizeof(arr) / sizeof(arr[0]);
int result = sequential_search(arr, n, target);
if (result != -1) {
printf("Element found at index %d\n", result);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
int sequential_search(int arr[], int n, int target)
: 定义顺序查找函数,参数为数组、数组长度和目标值。for (int i = 0; i < n; i++)
: 遍历数组。if (arr[i] == target)
: 如果找到目标值。return i
: 返回目标值的索引。return -1
: 如果未找到目标值,返回-1。
折半查找(也称二分查找)
查找算法原理:
折半查找是一种在有序数组中查找目标值的高效方法。它通过不断将查找范围减半,直到找到目标值或范围为空为止。
实现步骤:
- 确定查找范围的起始和结束索引。
- 计算中间索引。
- 比较中间元素与目标值。
- 如果中间元素等于目标值,返回其索引。
- 如果中间元素小于目标值,缩小查找范围至右半部分。
- 如果中间元素大于目标值,缩小查找范围至左半部分。
- 重复上述步骤直到找到目标值或范围为空。
C语言代码:
#include <stdio.h>
int binary_search(int arr[], int n, int target) {
int left = 0, right = n - 1;
while (left <= right) {
int mid = left + (right - left) / 2;
if (arr[mid] == target) {
return mid;
}
if (arr[mid] < target) {
left = mid + 1;
} else {
right = mid - 1;
}
}
return -1;
}
int main() {
int arr[] = {2, 4, 6, 8, 10};
int target = 6;
int n = sizeof(arr) / sizeof(arr[0]);
int result = binary_search(arr, n, target);
if (result != -1) {
printf("Element found at index %d\n", result);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
int binary_search(int arr[], int n, int target)
: 定义二分查找函数,参数为数组、数组长度和目标值。int left = 0, right = n - 1
: 初始化左右索引。while (left <= right)
: 当查找范围有效时。int mid = left + (right - left) / 2
: 计算中间索引。if (arr[mid] == target)
: 如果找到目标值。return mid
: 返回目标值的索引。if (arr[mid] < target)
: 如果中间元素小于目标值。left = mid + 1
: 调整左索引。else
: 如果中间元素大于目标值。right = mid - 1
: 调整右索引。return -1
: 如果未找到目标值,返回-1。
分块查找
查找算法原理:
分块查找将数据分成若干块,并在每块中进行线性查找。首先找到目标值可能所在的块,然后在该块中进行顺序查找。
实现步骤:
- 将数据分成若干块。
- 在块索引中找到目标值可能所在的块。
- 在该块中进行顺序查找。
C语言代码:
#include <stdio.h>
int block_search(int arr[], int n, int target, int block_size) {
int block_count = (n + block_size - 1) / block_size;
for (int i = 0; i < block_count; i++) {
int start = i * block_size;
int end = start + block_size;
if (end > n) end = n;
if (arr[end - 1] >= target) {
for (int j = start; j < end; j++) {
if (arr[j] == target) {
return j;
}
}
return -1;
}
}
return -1;
}
int main() {
int arr[] = {2, 4, 6, 8, 10, 12, 14, 16, 18};
int target = 10;
int n = sizeof(arr) / sizeof(arr[0]);
int block_size = 3;
int result = block_search(arr, n, target, block_size);
if (result != -1) {
printf("Element found at index %d\n", result);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
int block_search(int arr[], int n, int target, int block_size)
: 定义分块查找函数,参数为数组、数组长度、目标值和块大小。int block_count = (n + block_size - 1) / block_size
: 计算块的数量。for (int i = 0; i < block_count; i++)
: 遍历每个块。int start = i * block_size
: 计算当前块的起始索引。int end = start + block_size
: 计算当前块的结束索引。if (end > n) end = n
: 如果结束索引超过数组长度,调整结束索引。if (arr[end - 1] >= target)
: 如果目标值在当前块中。for (int j = start; j < end; j++)
: 在块中进行顺序查找。if (arr[j] == target)
: 如果找到目标值。return j
: 返回目标值的索引。return -1
: 如果未找到目标值,返回-1。
二叉排序树查找
查找算法原理:
二叉排序树(BST)是一种二叉树,每个节点的左子树所有值都小于该节点的值,右子树所有值都大于该节点的值。在BST中查找目标值时,通过比较当前节点值与目标值,决定在左子树或右子树中继续查找。
实现步骤:
- 从根节点开始。
- 比较当前节点值与目标值。
- 如果相等,返回该节点。
- 如果目标值小于当前节点值,在左子树中递归查找。
- 如果目标值大于当前节点值,在右子树中递归查找。
- 如果节点为空,返回未找到。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
struct TreeNode {
int val;
struct TreeNode *left, *right;
};
struct TreeNode* create_node(int key) {
struct TreeNode* new_node = (struct TreeNode*)malloc(sizeof(struct TreeNode));
new_node->val = key;
new_node->left = new_node->right = NULL;
return new_node;
}
struct TreeNode* insert(struct TreeNode* node, int key) {
if (node == NULL) return create_node(key);
if (key < node->val)
node->left = insert(node->left, key);
else if (key > node->val)
node->right = insert(node->right, key);
return node;
}
struct TreeNode* search(struct TreeNode* root, int target) {
if (root == NULL || root->val == target)
return root;
if (target < root->val)
return search(root->left, target);
return search(root->right, target);
}
int main() {
struct TreeNode* root = NULL;
int keys[] = {20, 8, 22
, 4, 12, 10, 14};
int n = sizeof(keys) / sizeof(keys[0]);
for (int i = 0; i < n; i++) {
root = insert(root, keys[i]);
}
int target = 10;
struct TreeNode* result = search(root, target);
if (result != NULL) {
printf("Element found: %d\n", result->val);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
struct TreeNode
: 定义二叉排序树节点结构。struct TreeNode* create_node(int key)
: 创建新节点。struct TreeNode* insert(struct TreeNode* node, int key)
: 插入节点。struct TreeNode* search(struct TreeNode* root, int target)
: 查找节点。int main()
: 主函数,演示插入和查找操作。
平衡二叉树(AVL树)
查找算法原理:
平衡二叉树是一种自平衡的二叉排序树,其左右子树的高度差最多为1,确保查找、插入、删除的时间复杂度为O(log n)。
实现步骤:
- 插入节点后,通过旋转操作保持树的平衡。
- 左旋和右旋操作用于重新平衡树。
- 计算每个节点的高度以保持平衡。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
struct TreeNode {
int val;
struct TreeNode *left, *right;
int height;
};
int max(int a, int b) {
return (a > b) ? a : b;
}
int height(struct TreeNode *N) {
return (N == NULL) ? 0 : N->height;
}
struct TreeNode* create_node(int key) {
struct TreeNode* node = (struct TreeNode*)malloc(sizeof(struct TreeNode));
node->val = key;
node->left = node->right = NULL;
node->height = 1;
return node;
}
struct TreeNode* right_rotate(struct TreeNode *y) {
struct TreeNode *x = y->left;
struct TreeNode *T2 = x->right;
x->right = y;
y->left = T2;
y->height = max(height(y->left), height(y->right)) + 1;
x->height = max(height(x->left), height(x->right)) + 1;
return x;
}
struct TreeNode* left_rotate(struct TreeNode *x) {
struct TreeNode *y = x->right;
struct TreeNode *T2 = y->left;
y->left = x;
x->right = T2;
x->height = max(height(x->left), height(x->right)) + 1;
y->height = max(height(y->left), height(y->right)) + 1;
return y;
}
int get_balance(struct TreeNode *N) {
return (N == NULL) ? 0 : height(N->left) - height(N->right);
}
struct TreeNode* insert(struct TreeNode* node, int key) {
if (node == NULL)
return create_node(key);
if (key < node->val)
node->left = insert(node->left, key);
else if (key > node->val)
node->right = insert(node->right, key);
else
return node;
node->height = 1 + max(height(node->left), height(node->right));
int balance = get_balance(node);
if (balance > 1 && key < node->left->val)
return right_rotate(node);
if (balance < -1 && key > node->right->val)
return left_rotate(node);
if (balance > 1 && key > node->left->val) {
node->left = left_rotate(node->left);
return right_rotate(node);
}
if (balance < -1 && key < node->right->val) {
node->right = right_rotate(node->right);
return left_rotate(node);
}
return node;
}
struct TreeNode* search(struct TreeNode* root, int target) {
if (root == NULL || root->val == target)
return root;
if (target < root->val)
return search(root->left, target);
return search(root->right, target);
}
int main() {
struct TreeNode* root = NULL;
int keys[] = {20, 8, 22, 4, 12, 10, 14};
int n = sizeof(keys) / sizeof(keys[0]);
for (int i = 0; i < n; i++) {
root = insert(root, keys[i]);
}
int target = 10;
struct TreeNode* result = search(root, target);
if (result != NULL) {
printf("Element found: %d\n", result->val);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
- 定义AVL树节点结构,包含节点值、左子树、右子树和节点高度。
create_node
函数用于创建新节点。right_rotate
和left_rotate
函数用于保持树的平衡。get_balance
函数用于计算节点的平衡因子。insert
函数用于插入节点并保持树的平衡。search
函数用于查找节点。
红黑树
查找算法原理:
红黑树是一种自平衡的二叉查找树,每个节点包含一个颜色(红色或黑色)。通过节点颜色和旋转操作保持树的平衡,确保查找、插入、删除操作的时间复杂度为O(log n)。
实现步骤:
- 插入节点后通过颜色调整和旋转操作保持树的平衡。
- 左旋和右旋操作用于重新平衡树。
- 确保树的性质:根节点是黑色,红色节点的子节点是黑色,从任一节点到叶子节点的路径上黑色节点数相同。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
enum Color { RED, BLACK };
struct TreeNode {
int val;
enum Color color;
struct TreeNode *left, *right, *parent;
};
struct TreeNode* create_node(int key) {
struct TreeNode* node = (struct TreeNode*)malloc(sizeof(struct TreeNode));
node->val = key;
node->color = RED;
node->left = node->right = node->parent = NULL;
return node;
}
void left_rotate(struct TreeNode** root, struct TreeNode* x) {
struct TreeNode* y = x->right;
x->right = y->left;
if (y->left != NULL) y->left->parent = x;
y->parent = x->parent;
if (x->parent == NULL)
*root = y;
else if (x == x->parent->left)
x->parent->left = y;
else
x->parent->right = y;
y->left = x;
x->parent = y;
}
void right_rotate(struct TreeNode** root, struct TreeNode* y) {
struct TreeNode* x = y->left;
y->left = x->right;
if (x->right != NULL) x->right->parent = y;
x->parent = y->parent;
if (y->parent == NULL)
*root = x;
else if (y == y->parent->left)
y->parent->left = x;
else
y->parent->right = x;
x->right = y;
y->parent = x;
}
void insert_fixup(struct TreeNode** root, struct TreeNode* z) {
while (z->parent != NULL && z->parent->color == RED) {
if (z->parent == z->parent->parent->left) {
struct TreeNode* y = z->parent->parent->right;
if (y != NULL && y->color == RED) {
z->parent->color = BLACK;
y->color = BLACK;
z->parent->parent->color = RED;
z = z->parent->parent;
} else {
if (z == z->parent->right) {
z = z->parent;
left_rotate(root, z);
}
z->parent->color = BLACK;
z->parent->parent->color = RED;
right_rotate(root, z->parent->parent);
}
} else {
struct TreeNode* y = z->parent->parent->left;
if (y != NULL && y->color == RED) {
z->parent->color = BLACK;
y->color = BLACK;
z->parent->parent->color = RED;
z = z->parent->parent;
} else {
if (z == z->parent->left) {
z = z->parent;
right_rotate(root, z);
}
z->parent->color = BLACK;
z->parent->parent->color = RED;
left_rotate(root, z->parent->parent);
}
}
}
(*root)->color = BLACK;
}
void insert(struct TreeNode** root, int key) {
struct TreeNode* z = create_node(key);
struct TreeNode* y = NULL;
struct TreeNode* x = *root;
while (x != NULL) {
y = x;
if (z->val < x->val)
x = x->left;
else
x = x->right;
}
z->parent = y;
if (y == NULL)
*root = z;
else if (z->val < y->val)
y->left = z;
else
y->right = z;
insert_fixup(root, z);
}
struct TreeNode* search(struct TreeNode* root, int target) {
while (root != NULL && root->val != target) {
if (target < root->val)
root
= root->left;
else
root = root->right;
}
return root;
}
int main() {
struct TreeNode* root = NULL;
int keys[] = {20, 8, 22, 4, 12, 10, 14};
int n = sizeof(keys) / sizeof(keys[0]);
for (int i = 0; i < n; i++) {
insert(&root, keys[i]);
}
int target = 10;
struct TreeNode* result = search(root, target);
if (result != NULL) {
printf("Element found: %d\n", result->val);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
- 定义红黑树节点结构,包含节点值、颜色、左子树、右子树和父节点。
create_node
函数用于创建新节点。left_rotate
和right_rotate
函数用于保持树的平衡。insert_fixup
函数用于插入节点后的颜色调整和旋转操作。insert
函数用于插入节点并保持树的平衡。search
函数用于查找节点。
B树
查找算法原理:
B树是一种自平衡的树数据结构,广泛应用于数据库和文件系统中。B树节点可以有多个子节点和关键字,确保查找、插入、删除操作的时间复杂度为O(log n)。
实现步骤:
- B树的每个节点可以包含多个关键字和子节点。
- 关键字和子节点根据值进行分布。
- 插入和删除操作需要保持树的平衡,通过节点分裂和合并操作实现。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
#define T 3
struct BTreeNode {
int *keys;
int t;
struct BTreeNode **C;
int n;
int leaf;
};
struct BTreeNode* create_node(int t, int leaf) {
struct BTreeNode* node = (struct BTreeNode*)malloc(sizeof(struct BTreeNode));
node->t = t;
node->leaf = leaf;
node->keys = (int*)malloc((2*t-1) * sizeof(int));
node->C = (struct BTreeNode**)malloc((2*t) * sizeof(struct BTreeNode*));
node->n = 0;
return node;
}
void traverse(struct BTreeNode* root) {
int i;
for (i = 0; i < root->n; i++) {
if (!root->leaf)
traverse(root->C[i]);
printf(" %d", root->keys[i]);
}
if (!root->leaf)
traverse(root->C[i]);
}
struct BTreeNode* search(struct BTreeNode* root, int k) {
int i = 0;
while (i < root->n && k > root->keys[i])
i++;
if (root->keys[i] == k)
return root;
if (root->leaf)
return NULL;
return search(root->C[i], k);
}
void insert_non_full(struct BTreeNode* x, int k);
void split_child(struct BTreeNode* x, int i, struct BTreeNode* y);
void insert(struct BTreeNode** root, int k) {
struct BTreeNode* r = *root;
if (r->n == 2*T-1) {
struct BTreeNode* s = create_node(r->t, 0);
s->C[0] = r;
split_child(s, 0, r);
int i = 0;
if (s->keys[0] < k)
i++;
insert_non_full(s->C[i], k);
*root = s;
} else {
insert_non_full(r, k);
}
}
void split_child(struct BTreeNode* x, int i, struct BTreeNode* y) {
struct BTreeNode* z = create_node(y->t, y->leaf);
z->n = T - 1;
for (int j = 0; j < T-1; j++)
z->keys[j] = y->keys[j+T];
if (!y->leaf) {
for (int j = 0; j < T; j++)
z->C[j] = y->C[j+T];
}
y->n = T - 1;
for (int j = x->n; j >= i+1; j--)
x->C[j+1] = x->C[j];
x->C[i+1] = z;
for (int j = x->n-1; j >= i; j--)
x->keys[j+1] = x->keys[j];
x->keys[i] = y->keys[T-1];
x->n = x->n + 1;
}
void insert_non_full(struct BTreeNode* x, int k) {
int i = x->n - 1;
if (x->leaf) {
while (i >= 0 && x->keys[i] > k) {
x->keys[i+1] = x->keys[i];
i--;
}
x->keys[i+1] = k;
x->n = x->n + 1;
} else {
while (i >= 0 && x->keys[i] > k)
i--;
if (x->C[i+1]->n == 2*T-1) {
split_child(x, i+1, x->C[i+1]);
if (x->keys[i+1] < k)
i++;
}
insert_non_full(x->C[i+1], k);
}
}
int main() {
struct BTreeNode* root = create_node(T, 1);
int keys[] = {10, 20, 5, 6, 12, 30, 7, 17};
int n = sizeof(keys) / sizeof(keys[0]);
for (int i = 0; i < n; i++) {
insert(&root, keys[i]);
}
printf("Traversal of the constructed tree is ");
traverse(root);
int target = 6;
struct BTreeNode* result = search(root, target);
if (result != NULL) {
printf("\nElement found");
} else {
printf("\nElement not found");
}
return 0;
}
代码解释:
- 定义B树节点结构,包含关键字、子节点、关键字数量和是否为叶子节点。
create_node
函数用于创建新节点。traverse
函数用于遍历B树。search
函数用于查找节点。insert
函数用于插入节点。split_child
函数用于分裂节点。insert_non_full
函数用于在非满节点中插入关键字。
B+树
查找算法原理:
B+树是B树的一种变种,所有数据都存储在叶子节点中,并且叶子节点通过链表相连。B+树的非叶子节点只存储索引,便于范围查找。
实现步骤:
- B+树的每个节点可以包含多个关键字和子节点。
- 关键字和子节点根据值进行分布。
- 插入和删除操作需要保持树的平衡,通过节点分裂和合并操作实现。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
#define T 3
struct BPlusTreeNode {
int *keys;
struct BPlusTreeNode **C;
struct BPlusTreeNode *next;
int n;
int leaf;
};
struct BPlusTreeNode* create_node(int leaf) {
struct BPlusTreeNode* node = (struct BPlusTreeNode*)malloc(sizeof(struct BPlusTreeNode));
node->keys = (int*)malloc((2*T-1) * sizeof(int));
node->C = (struct BPlusTreeNode**)malloc((2*T) * sizeof(struct BPlusTreeNode*));
node->next = NULL;
node->n = 0;
node->leaf = leaf;
return node;
}
void traverse(struct BPlusTreeNode* root) {
struct BPlusTreeNode* current = root;
while (!current->leaf)
current = current->C[0];
while (current) {
for (int i = 0; i < current->n; i++)
printf(" %d", current->keys[i]);
current = current->next;
}
}
struct BPlusTreeNode* search(struct BPlusTreeNode* root, int k) {
int i = 0;
while (i < root->n && k > root->keys[i])
i++;
if (i < root->n && root->keys[i] == k)
return root;
if (root->leaf)
return NULL;
return search(root->C[i], k);
}
void insert_non_full(struct BPlusTreeNode* x, int k);
void split_child
(struct BPlusTreeNode* x, int i, struct BPlusTreeNode* y);
void insert(struct BPlusTreeNode** root, int k) {
struct BPlusTreeNode* r = *root;
if (r->n == 2*T-1) {
struct BPlusTreeNode* s = create_node(0);
s->C[0] = r;
split_child(s, 0, r);
int i = 0;
if (s->keys[0] < k)
i++;
insert_non_full(s->C[i], k);
*root = s;
} else {
insert_non_full(r, k);
}
}
void split_child(struct BPlusTreeNode* x, int i, struct BPlusTreeNode* y) {
struct BPlusTreeNode* z = create_node(y->leaf);
z->n = T - 1;
for (int j = 0; j < T-1; j++)
z->keys[j] = y->keys[j+T];
if (!y->leaf) {
for (int j = 0; j < T; j++)
z->C[j] = y->C[j+T];
} else {
z->next = y->next;
y->next = z;
}
y->n = T - 1;
for (int j = x->n; j >= i+1; j--)
x->C[j+1] = x->C[j];
x->C[i+1] = z;
for (int j = x->n-1; j >= i; j--)
x->keys[j+1] = x->keys[j];
x->keys[i] = y->keys[T-1];
x->n = x->n + 1;
}
void insert_non_full(struct BPlusTreeNode* x, int k) {
int i = x->n - 1;
if (x->leaf) {
while (i >= 0 && x->keys[i] > k) {
x->keys[i+1] = x->keys[i];
i--;
}
x->keys[i+1] = k;
x->n = x->n + 1;
} else {
while (i >= 0 && x->keys[i] > k)
i--;
if (x->C[i+1]->n == 2*T-1) {
split_child(x, i+1, x->C[i+1]);
if (x->keys[i+1] < k)
i++;
}
insert_non_full(x->C[i+1], k);
}
}
int main() {
struct BPlusTreeNode* root = create_node(1);
int keys[] = {10, 20, 5, 6, 12, 30, 7, 17};
int n = sizeof(keys) / sizeof(keys[0]);
for (int i = 0; i < n; i++) {
insert(&root, keys[i]);
}
printf("Traversal of the constructed B+ tree is ");
traverse(root);
int target = 6;
struct BPlusTreeNode* result = search(root, target);
if (result != NULL) {
printf("\nElement found");
} else {
printf("\nElement not found");
}
return 0;
}
代码解释:
- 定义B+树节点结构,包含关键字、子节点、下一个节点、关键字数量和是否为叶子节点。
create_node
函数用于创建新节点。traverse
函数用于遍历B+树。search
函数用于查找节点。insert
函数用于插入节点。split_child
函数用于分裂节点。insert_non_full
函数用于在非满节点中插入关键字。
散列查找
查找算法原理:
散列查找通过散列函数将关键字映射到数组中的位置。使用链地址法处理散列冲突,每个数组位置存储一个链表,链表中的每个节点包含具有相同散列值的关键字。
实现步骤:
- 使用散列函数计算关键字的散列值。
- 根据散列值将关键字插入对应位置的链表中。
- 查找时,计算关键字的散列值,然后在链表中查找目标值。
C语言代码:
#include <stdio.h>
#include <stdlib.h>
#define TABLE_SIZE 10
struct Node {
int key;
struct Node* next;
};
struct Node* hash_table[TABLE_SIZE];
unsigned int hash(int key) {
return key % TABLE_SIZE;
}
void insert(int key) {
unsigned int index = hash(key);
struct Node* new_node = (struct Node*)malloc(sizeof(struct Node));
new_node->key = key;
new_node->next = hash_table[index];
hash_table[index] = new_node;
}
struct Node* search(int key) {
unsigned int index = hash(key);
struct Node* current = hash_table[index];
while (current != NULL) {
if (current->key == key)
return current;
current = current->next;
}
return NULL;
}
void display() {
for (int i = 0; i < TABLE_SIZE; i++) {
struct Node* current = hash_table[i];
printf("hash_table[%d]: ", i);
while (current != NULL) {
printf("%d -> ", current->key);
current = current->next;
}
printf("NULL\n");
}
}
int main() {
insert(10);
insert(20);
insert(15);
insert(7);
insert(32);
display();
int target = 15;
struct Node* result = search(target);
if (result != NULL) {
printf("Element found: %d\n", result->key);
} else {
printf("Element not found\n");
}
return 0;
}
代码解释:
- 定义链表节点结构,包含关键字和下一个节点指针。
- 定义哈希表为链表节点指针数组。
hash
函数用于计算关键字的散列值。insert
函数用于插入关键字到哈希表。search
函数用于查找关键字。display
函数用于显示哈希表的内容。
原文地址:https://blog.csdn.net/L6666688888/article/details/140589548
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