HiveServer2负载均衡-CFANZ编程社区

1 文本格式

using System;

namespace Legalsoft.Truffer
{
/// <summary>
/// K-Means classification
/// </summary>
public class Kmeans
{
private int nn { get; set; }
private int mm { get; set; }
private int kk { get; set; }
private int nchg { get; set; }
private double[,] data { get; set; }
private double[,] means { get; set; }
private int[] assign { get; set; }
private int[] count { get; set; }

public Kmeans(double[,] ddata, double[,] mmeans)
{
this.nn = ddata.GetLength(0);
this.mm = ddata.GetLength(1);
this.kk = mmeans.GetLength(0);
this.data = Globals.CopyFrom(ddata);
this.means = Globals.CopyFrom(mmeans);
this.assign = new int[nn];
this.count = new int[kk];

estep();
mstep();
}

public int estep()
{
int kmin = 0;
nchg = 0;
for (int k = 0; k < kk; k++)
{
count[k] = 0;
}
for (int n = 0; n < nn; n++)
{
double dmin = 9.99e99;
for (int k = 0; k < kk; k++)
{
double d = 0.0;
for (int m = 0; m < mm; m++)
{
d += Globals.SQR(data[n, m] - means[k, m]);
}
if (d < dmin)
{
dmin = d;
kmin = k;
}
}
if (kmin != assign[n])
{
nchg++;
}
assign[n] = kmin;
count[kmin]++;
}
return nchg;
}

public void mstep()
{
for (int k = 0; k < kk; k++)
{
for (int m = 0; m < mm; m++)
{
means[k, m] = 0.0;
}
}
for (int n = 0; n < nn; n++)
{
for (int m = 0; m < mm; m++)
{
means[assign[n], m] += data[n, m];
}
}
for (int k = 0; k < kk; k++)
{
if (count[k] > 0)
{
for (int m = 0; m < mm; m++)
{
means[k, m] /= count[k];
}
}
}
}
}
}

2 代码格式

using System;

namespace Legalsoft.Truffer
{
    /// <summary>
    /// K-Means classification
    /// </summary>
    public class Kmeans
    {
        private int nn { get; set; }
        private int mm { get; set; }
        private int kk { get; set; }
        private int nchg { get; set; }
        private double[,] data { get; set; }
        private double[,] means { get; set; }
        private int[] assign { get; set; }
        private int[] count { get; set; }

        public Kmeans(double[,] ddata, double[,] mmeans)
        {
            this.nn = ddata.GetLength(0);
            this.mm = ddata.GetLength(1);
            this.kk = mmeans.GetLength(0);
            this.data = Globals.CopyFrom(ddata);
            this.means = Globals.CopyFrom(mmeans);
            this.assign = new int[nn];
            this.count = new int[kk];

            estep();
            mstep();
        }

        public int estep()
        {
            int kmin = 0;
            nchg = 0;
            for (int k = 0; k < kk; k++)
            {
                count[k] = 0;
            }
            for (int n = 0; n < nn; n++)
            {
                double dmin = 9.99e99;
                for (int k = 0; k < kk; k++)
                {
                    double d = 0.0;
                    for (int m = 0; m < mm; m++)
                    {
                        d += Globals.SQR(data[n, m] - means[k, m]);
                    }
                    if (d < dmin)
                    {
                        dmin = d;
                        kmin = k;
                    }
                }
                if (kmin != assign[n])
                {
                    nchg++;
                }
                assign[n] = kmin;
                count[kmin]++;
            }
            return nchg;
        }

        public void mstep()
        {
            for (int k = 0; k < kk; k++)
            {
                for (int m = 0; m < mm; m++)
                {
                    means[k, m] = 0.0;
                }
            }
            for (int n = 0; n < nn; n++)
            {
                for (int m = 0; m < mm; m++)
                {
                    means[assign[n], m] += data[n, m];
                }
            }
            for (int k = 0; k < kk; k++)
            {
                if (count[k] > 0)
                {
                    for (int m = 0; m < mm; m++)
                    {
                        means[k, m] /= count[k];
                    }
                }
            }
        }
    }
}