java代码怎样实现布隆过滤器及去重功能 java代码布隆过滤器的实用编写教程​

import java.util.BitSet;
import java.util.function.ToIntFunction;

public class BloomFilter<T> {

    private final BitSet bitSet;
    private final int bitSetSize;
    private final int hashFunctionCount;
    private final ToIntFunction<T>[] hashFunctions;

    public BloomFilter(int expectedInsertions, double falsePositiveRate, ToIntFunction<T>... hashFunctions) {
        // 根据预期插入数量和误判率计算BitSet大小和哈希函数数量
        this.bitSetSize = optimalBitSetSize(expectedInsertions, falsePositiveRate);
        this.hashFunctionCount = hashFunctions.length; // 使用提供的哈希函数数量
        this.bitSet = new BitSet(bitSetSize);
        this.hashFunctions = hashFunctions;
    }

    private int optimalBitSetSize(int expectedInsertions, double falsePositiveRate) {
        return (int) (-expectedInsertions * Math.log(falsePositiveRate) / (Math.log(2) * Math.log(2)));
    }

    public void add(T element) {
        for (ToIntFunction<T> hashFunction : hashFunctions) {
            int index = Math.abs(hashFunction.applyAsInt(element) % bitSetSize);
            bitSet.set(index, true);
        }
    }

    public boolean mightContain(T element) {
        for (ToIntFunction<T> hashFunction : hashFunctions) {
            int index = Math.abs(hashFunction.applyAsInt(element) % bitSetSize);
            if (!bitSet.get(index)) {
                return false;
            }
        }
        return true;
    }

    // 示例哈希函数
    public static ToIntFunction<String> murmurHashFunction() {
        return (String s) -> {
            int hash = 31;
            for (int i = 0; i < s.length(); i++) {
                hash = (hash * 31) + s.charAt(i);
            }
            return hash;
        };
    }

    public static void main(String[] args) {
        BloomFilter<String> bloomFilter = new BloomFilter<>(1000, 0.01, BloomFilter.murmurHashFunction(), (String s) -> s.hashCode());

        bloomFilter.add("apple");
        bloomFilter.add("banana");
        bloomFilter.add("cherry");

        System.out.println("Contains apple: " + bloomFilter.mightContain("apple")); // true
        System.out.println("Contains grape: " + bloomFilter.mightContain("grape")); // 可能会返回true，也可能返回false，取决于误判
    }
}