【算法一】布隆过滤器算法学习附维基百科详细说明PDF文件

示例一来源：https://www.cnblogs.com/yueyue184/p/10037587.html

    /// <summary>
    /// 布隆过滤器
    /// </summary>
    public class BloomFilter
    {
        public BitArray _bloomArray;
        /// <summary>
        /// 布隆数组的大小
        /// </summary>
        public Int64 BloomArrayLength { get; set; }
        /// <summary>
        /// 数据长度
        /// </summary>
        public Int64 DataArrayLength { get; set; }
        /// <summary>
        /// hash数
        /// </summary>
        public Int64 BitIndexCount { get; set; }

        /// <summary>
        /// 布隆过滤器初始化
        /// </summary>
        /// <param name="bloomArrayLength">布隆数组的大小</param>
        /// <param name="dataArrayLength">数据长度</param>
        /// <param name="bitIndexCount">hash数</param>
        public BloomFilter(int bloomArrayLength, int dataArrayLength, int bitIndexCount)
        {
            _bloomArray = new BitArray(bloomArrayLength);

            this.BloomArrayLength = bloomArrayLength;
            this.DataArrayLength = dataArrayLength;
            this.BitIndexCount = bitIndexCount;
        }

        /// <summary>
        /// 添加
        /// </summary>
        /// <param name="str"></param>
        public void Add(string str)
        {
            var hashCode=str.GetHashCode();
            var random = new Random(hashCode);

            for (int i = 0; i < BitIndexCount; i++)
            {
                var c=random.Next((int)this.BloomArrayLength - 1);
                _bloomArray[c] = true;
            }
        }

        /// <summary>
        /// 判断是否存在
        /// </summary>
        /// <param name="str">字符串</param>
        /// <returns></returns>
        public bool IsExists(string str)
        {
            var hashCode = str.GetHashCode();
            var random = new Random(hashCode);
            for (int i = 0; i < BitIndexCount; i++)
            {
                if (!_bloomArray[random.Next((int)this.BloomArrayLength-1)])
                {
                    return false;
                }
            }
            return true;
        }

        /// <summary>
        /// 获取错误概率
        /// </summary>
        /// <returns></returns>
        public double GetFalsePositiveProbability()
        {
            // (1 - e^(-k * n / m)) ^ k
            return Math.Pow((1 - Math.Exp(-BitIndexCount * (double)DataArrayLength / BloomArrayLength)), BitIndexCount);
        }

    }

    class Program
    {
        static void Main(string[] args)
        {
            //五千万条数据
            var bloomFilter = new BloomFilter(200000000, 50000000, 3);

            //添加5千万个数做测试
            for (int i = 0; i < bloomFilter.DataArrayLength; i++)
            {
                bloomFilter.Add(i.ToString());
            }

            do
            {
                var str = Console.ReadLine();

                var stopwatch = new Stopwatch();
                stopwatch.Start();

                var temp = bloomFilter.IsExists(str);

                stopwatch.Stop();
                Console.WriteLine($"查找:{str}\n结果:{temp}\n总耗时:{stopwatch.ElapsedTicks}\n错误概率:{bloomFilter.GetFalsePositiveProbability()}");
            } while (true);
        }
    }