假如有上亿条数据，你如何快速找到其中一条你想要的数据（几种简单的算法）

java复制代码import java.util.HashMap;
import java.util.Map;

public class HashTableExample {
    public static void main(String[] args) {
        Map<String, String> hashTable = new HashMap<>();

        // 假设插入上亿条数据
        for (int i = 0; i < 100000000; i++) {
            hashTable.put("user" + i, "data" + i);
        }

        // 查找某一条数据
        String userId = "user12345678";
        String userData = hashTable.get(userId);

        System.out.println("Data for " + userId + ": " + userData);
    }
}

java复制代码class TreeNode {
    int value;
    TreeNode left;
    TreeNode right;

    TreeNode(int value) {
        this.value = value;
    }
}

public class BSTExample {
    public static TreeNode insert(TreeNode root, int value) {
        if (root == null) {
            return new TreeNode(value);
        }
        if (value < root.value) {
            root.left = insert(root.left, value);
        } else {
            root.right = insert(root.right, value);
        }
        return root;
    }

    public static TreeNode search(TreeNode root, int value) {
        if (root == null || root.value == value) {
            return root;
        }
        if (value < root.value) {
            return search(root.left, value);
        } else {
            return search(root.right, value);
        }
    }

    public static void main(String[] args) {
        TreeNode root = null;

        // 假设插入上亿条数据
        for (int i = 0; i < 100000000; i++) {
            root = insert(root, i);
        }

        // 查找某一条数据
        int target = 12345678;
        TreeNode result = search(root, target);

        if (result != null) {
            System.out.println("Found: " + result.value);
        } else {
            System.out.println("Not found");
        }
    }
}

java复制代码import java.util.Arrays;

public class PartitionSearch {

    public static int binarySearch(int[] arr, int x) {
        int l = 0, r = arr.length - 1;
        while (l <= r) {
            int m = l + (r - l) / 2;
            if (arr[m] == x) return m;
            if (arr[m] < x) l = m + 1;
            else r = m - 1;
        }
        return -1;
    }

    public static void main(String[] args) {
        // 假设有上亿条���据
        int n = 100000000;
        int[] data = new int[n];
        for (int i = 0; i < n; i++) {
            data[i] = i;
        }

        // 划分区块，每个区块大小为100万
        int blockSize = 1000000;
        int[][] blocks = new int[n / blockSize][blockSize];
        for (int i = 0; i < n; i++) {
            blocks[i / blockSize][i % blockSize] = data[i];
        }

        // 查找某一条数据
        int target = 12345678;
        int blockIndex = target / blockSize;
        int resultIndex = binarySearch(blocks[blockIndex], target);

        if (resultIndex != -1) {
            System.out.println("Found: " + target);
        } else {
            System.out.println("Not found");
        }
    }
}

java复制代码import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class InvertedIndexExample {
    public static void main(String[] args) {
        // 构建倒排索引
        Map<String, List<Integer>> invertedIndex = new HashMap<>();
        String[] documents = new String[100000000];
        for (int i = 0; i < documents.length; i++) {
            documents[i] = "Document content " + i;
            String[] words = documents[i].split(" ");
            for (String word : words) {
                invertedIndex.computeIfAbsent(word, k -> new ArrayList<>()).add(i);
            }
        }

        // 查找包含特定词的文档
        String keyword = "content";
        List<Integer> result = invertedIndex.get(keyword);

        if (result != null) {
            System.out.println("Documents containing '" + keyword + "': " + result);
        } else {
            System.out.println("No documents found containing '" + keyword + "'");
        }
    }
}

java复制代码// B+ 树的实现较为复杂，这里不展示具体代码
// 可以使用现成的数据库或文件系统来利用B+树结构