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用R语言实现密度聚类dbscan

R的极客理想系列文章,涵盖了R的思想,使用,工具,创新等的一系列要点,以我个人的学习和体验去诠释R的强大。

R语言作为统计学一门语言,一直在小众领域闪耀着光芒。直到大数据的爆发,R语言变成了一门炙手可热的数据分析的利器。随着越来越多的工程背景的人的加入,R语言的社区在迅速扩大成长。现在已不仅仅是统计领域,教育,银行,电商,互联网….都在使用R语言。

要成为有理想的极客,我们不能停留在语法上,要掌握牢固的数学,概率,统计知识,同时还要有创新精神,把R语言发挥到各个领域。让我们一起动起来吧,开始R的极客理想。

关于作者:

  • 张丹(Conan), 程序员/Quant: Java,R,Nodejs
  • blog: http://blog.fens.me
  • email: bsspirit@gmail.com

转载请注明出处:
http://blog.fens.me/r-cluster-dbscan

前言

聚类是一种将数据点按一定规则分群的机器学习技术,k-Means聚类是被用的最广泛的也最容易理解的一种。除了K-Means的方法,其实还有很多种不同的聚类方法,本文将给大家介绍基于密度的聚类,我们可以通过使用dbscan包来实现。

目录

  1. DBSCAN基于密度的聚类
  2. dbscan包介绍
  3. kNN()函数使用
  4. dbscan()函数使用
  5. hdbscan()函数使用

1. DBSCAN基于密度的聚类

DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法,它是一种基于高密度连通区域的基于密度的聚类算法,能够将具有足够高密度的区域划分为簇,并在具有噪声的数据中发现任意形状的簇。

DBSCAN需要两个重要参数:epsilon(eps)和最小点(minPts)。参数eps定义了点x附近的邻域半径ε,它被称为x的最邻居。参数minPts是eps半径内的最小邻居数。

上图中(a),数据集中的任何点x邻居(6=minPts)都被标记为核心点,ε是半径。上图中(b),x为核心点,y的邻居小于(4<minpts)是边界点,但它属于核心点x的最邻居。z点既不是核心也不是边界点,它被称为噪声点或异常值。

dbscan算法将数据点分为三类:

  • 核心点:在半径eps内含有超过minPts数目的点。
  • 边界点:在半径eps内点的数量小于使用DBSCAN进行聚类的时候,不需要预先指定簇的个数,最终的簇的个数不确定。minPts,但是落在核心点的邻域内的点。
  • 噪音点:既不是核心点也不是边界点的点

DBSCAN算法的执行过程

1、DBSCAN算法随机从一个未被访问的数据点x开始,以eps为半径搜索范围内的所有邻域点。

2、如果x点在该邻域内有足够数量的点,数量大于等于minPts,则聚类过程开始,并且当前数据点成为新簇中的第一个核心点。否则,该点将被标记为噪声。该点都会被标记为“已访问”。

3、新簇中的每个核心点x,它的eps距离邻域内的点会归为同簇。eps邻域内的所有点都属于同一个簇,然后对才添加到簇中的所有新点重复上述过程。

4、重复步骤2和3两个过程,直到确定了簇中的所有点才停止,即访问和标记了聚类的eps邻域内的所有点。

5、当完成了这个簇的划分,就开始处理新的未访问的点,发现新的簇或者是噪声。重复上述过程,直到所有点被标记为已访问才停止。这样就完成了,对所有点的聚类过程。

优点和缺点

DBSCAN具有很多优点,提前不需要确定簇的数量。不同于Mean-shift算法,当数据点非常不同时,会将它们单纯地引入簇中,DBSCAN能将异常值识别为噪声。另外,它能够很好地找到任意大小和任意形状的簇。

DBSCAN算法的主要缺点是,当数据簇密度不均匀时,它的效果不如其他算法好。这是因为当密度变化时,用于识别邻近点的距离阈值ε和minPoints的设置将随着簇而变化。在处理高维数据时也会出现这种缺点,因为难以估计距离阈值eps。

2. dbscan包介绍

dbscan包,提供了基于密度的有噪声聚类算法的快速实现,包括 DBSCAN(基于密度的具有噪声的应用的空间聚类),OPTICS(用于识别聚类结构的排序点),HDBSCAN(分层DBSCAN)和LOF(局部异常因子)算法,dbscan底层使用C++编程,并建立kd树的数据结构进行更快的K最近邻搜索,从而实现加速。

本文的系统环境为:

  • Win10 64bit
  • R 3.4.2 x86_64

dbscan包的安装非常简单,只需要一条命令就能完成。


~ R
> install.packages("dbscan")
> library(dbscan)

函数列表:

  • dbscan(), 实现DBSCAN算法
  • optics(), 实现OPTICS算法
  • hdbscan(), 实现带层次DBSCAN算法
  • sNNclust(), 实现共享聚类算法
  • jpclust(), Jarvis-Patrick聚类算法
  • lof(), 局部异常因子得分算法
  • extractFOSC(),集群优选框架,可以通过参数化来执行聚类。
  • frNN(), 找到固定半径最近的邻居
  • kNN(), 最近邻算法,找到最近的k个邻居
  • sNN(), 找到最近的共享邻居数量
  • pointdensity(), 计算每个数据点的局部密度
  • kNNdist(),计算最近的k个邻居的距离
  • kNNdistplot(),画图,最近距离
  • hullplot(), 画图,集群的凸壳

dbscan包,提供了多个好用的函数,我们接下来先介绍3个函数,分别是kNN(),dbscan(), hdbscan(),其他的函数等以后有时间,再单独进行使用介绍。

3. kNN()函数使用

kNN()函数,使用kd-tree数据结构,用来快速查找数据集中的所有k个最近邻居。

函数定义:


kNN(x, k, sort = TRUE, search = "kdtree", bucketSize = 10, splitRule = "suggest", approx = 0)

参数列表

  • x,数据矩阵,dist对象或kNN对象。
  • k,要查找的邻居数量。
  • sort,按距离对邻居进行排序。
  • search,最近邻搜索策略,使用kdtree,linear或dist三选一,默认为kdtree。
  • bucketSize,kd-tree叶子节点的最大值。
  • splitRule,kd-tree的拆分规则,默认用SUGGEST。
  • approx,使用近似方法,加速计算。

函数使用:以iris鸢尾花的数据集,做为样本。聚类是不需要有事前有定义的,所以我们把iris的种属列去掉。

# 去掉种属列
> iris2 <- iris[, -5]
> head(iris2)
  Sepal.Length Sepal.Width Petal.Length Petal.Width
1          5.1         3.5          1.4         0.2
2          4.9         3.0          1.4         0.2
3          4.7         3.2          1.3         0.2
4          4.6         3.1          1.5         0.2
5          5.0         3.6          1.4         0.2
6          5.4         3.9          1.7         0.4

使用kNN()函数,来计算iris2数据集中,每个值最近的5个点。


# 查询最近邻的5个点
> nn <- kNN(iris2, k=5)

# 打印nn对象
> nn
k-nearest neighbors for 150 objects (k=5).
Available fields: dist, id, k, sort

# 查询nn的属性列表
> attributes(nn)
$names
[1] "dist" "id"   "k"    "sort"

$class
[1] "kNN" "NN" 

打印出,每个点最近邻的5个点。行,为每个点索引值,列,为最近邻的5个点,输出的矩阵为索引值。


> head(nn$id)
      1  2  3  4  5
[1,] 18  5 40 28 29
[2,] 35 46 13 10 26
[3,] 48  4  7 13 46
[4,] 48 30 31  3 46
[5,] 38  1 18 41  8
[6,] 19 11 49 45 20

打印出,每个点与最近的5个点的距离值。行,为每个点的索引,列,为最近邻的5个点,输出的矩阵为距离值。


> head(nn$dist)
             1         2         3         4         5
[1,] 0.1000000 0.1414214 0.1414214 0.1414214 0.1414214
[2,] 0.1414214 0.1414214 0.1414214 0.1732051 0.2236068
[3,] 0.1414214 0.2449490 0.2645751 0.2645751 0.2645751
[4,] 0.1414214 0.1732051 0.2236068 0.2449490 0.2645751
[5,] 0.1414214 0.1414214 0.1732051 0.1732051 0.2236068
[6,] 0.3316625 0.3464102 0.3605551 0.3741657 0.3872983

如果我们要查看索引为33的点,与哪5个点最紧邻,可以用下面的方法。


# 设置索引
> idx<-33

# 打印与33,最近邻的5个点的索引
> nn$id[idx,]
 1  2  3  4  5 
34 47 20 49 11 

# 画图
> cols = ifelse(1:nrow(iris2) %in% nn$id[idx,],"red", "black")
> cols[idx]<-'blue'
> plot(iris2,pch = 19, col = cols)

我们的数据集是多列的,把每2列组合形成的二维平面,都进行输出。蓝色表示索引为33的点,红色表示最紧邻的5个点,黑色表示其他的点。

从图中,可以很直观的看到,这几点确实是密集的在一起,也就是找到了最近邻。

接下来,我们画出连线图,选取第一列(Sepal.Length)和第二列(Sepal.Width),按取画出最紧邻前5连接路径。

> plot(nn, iris2)

通过连接路径,我们就能很清晰的看到,最紧邻算法的分组过程,连接在一起的就够成了一个分组,没有连接在一起的就是另外的分组,上图中可以看出来分成了2个组。

再对nn进行二次最近邻计算,画出前2的连接路径。

> plot(kNN(nn, k = 2), iris2)

通过2次的最紧邻缩减,连接路径大幅度减少了,又形成了新的独立区块。

2. dbscan()函数使用

dbscan是一种基于密度的聚类算法,这类密度聚类算法一般假定类别可以通过样本分布的紧密程度决定。同一类别的样本,他们之间的紧密相连的,也就是说,在该类别任意样本周围不远处一定有同类别的样本存在。

函数定义:

dbscan(x, eps, minPts = 5, weights = NULL, borderPoints = TRUE, ...)

参数解释:

  • x, 矩阵或者距离对象,frNN对象。
  • eps,半径的大小。
  • minPts, 半径区域中的最小点数量,默认为5
  • weights, 数据点的权重,仅用于加权聚类
  • borderPoints,边界点是否为噪声,默认为TRUE;为FALSE时,边界点为噪声。
  • …,将附加参数传递给固定半径最近邻搜索算法,调用frNN。

函数使用:以iris鸢尾花的数据集,做为样本。聚类是不需要有事前有定义的,所以我们把iris的种属列去掉。

# 去掉种属列
> iris2 <- iris[, -5]
> head(iris2)
  Sepal.Length Sepal.Width Petal.Length Petal.Width
1          5.1         3.5          1.4         0.2
2          4.9         3.0          1.4         0.2
3          4.7         3.2          1.3         0.2
4          4.6         3.1          1.5         0.2
5          5.0         3.6          1.4         0.2
6          5.4         3.9          1.7         0.4

在使用dbscan函数时,我们要输出2个参数,eps和minPts。

  • eps,值可以使用绘制k-距离曲线(k-distance graph)方法得到,在k-距离曲线图明显拐点位置为较好的参数。若参数设置过小,大部分数据不能聚类;若参数设置过大,多个簇和大部分对象会归并到同一个簇中。
  • minPts,通常让minPts≥dim+1,其中dim表示数据集聚类数据的维度。若该值选取过小,则稀疏簇中结果由于密度小于minPts,从而被认为是边界点儿不被用于在类的进一步扩展;若该值过大,则密度较大的两个邻近簇可能被合并为同一簇。

下面我们通过绘制k-距离曲线,寻找knee,即明显拐点位置为对应较好的参数,找到适合的eps值。使用kNNdistplot()函数,让参数k=dim + 1,dim为数据集列的个数,iris2是4列,那么设置k=5。

# 画出最近距离图
> kNNdistplot(iris2, k = 5)
> abline(h=0.5, col = "red", lty=2)

kNNdistplot()会计算点矩阵中的k=5的最近邻的距离,然后按距离从小到大排序后,以图形进行展示。x轴为距离的序号,y轴为距离的值。图中黑色的线,从左到右y值越来越大。

通过人眼识别,k-距离曲线上有明显拐点,我们以y=0.5平行于x轴画一条红色线,突出标识。所以,最后确认的eps为0.5。

调用dbscan()函数,进行对iris2数据集进行聚类,eps=0.5,minPts=5。

> res <- dbscan(iris2, eps = 0.5, minPts = 5)
> res
DBSCAN clustering for 150 objects.
Parameters: eps = 0.5, minPts = 5
The clustering contains 2 cluster(s) and 17 noise points.

 0  1  2 
17 49 84 

Available fields: cluster, eps, minPts

聚类后,一共分成了2组,第1组49个值,第2组84个值,另外,第0组17个值为噪声点。把聚类的结果画图展示。

> pairs(iris, col = res$cluster + 1L)

数据集是多列的,把每2列组合形成的二维平面,都进行输出。红色点表示第1组,绿色点表示为第2组,黑色点表示噪声点。这样就完成了有噪声的基于密度的dbscan聚类。

5. hdbscan()函数使用

hdbscan(),快速实现了分层DBSCAN算法,与stats包中的hclust()方法形成的传统分层聚类方法类似。

函数定义:

hdbscan(x, minPts, xdist = NULL,gen_hdbscan_tree = FALSE, gen_simplified_tree = FALSE)

参数解释:

  • x,矩阵或者距离对象
  • minPts,区域中的最小点数量
  • xdist,dist对象,可以提前算出来,当参数传入
  • gen_hdbscan_tree,生成一个hdbscan树
  • gen_simplified_tree,生成一个简化的树结构

5.1 iris鸢尾花的数据集
以iris鸢尾花的数据集,做为样本,去掉种属列。设置minPts =5让当前群集中最小的数量为5,开始聚类。

> hcl<-hdbscan(iris2, minPts = 5);hcl
HDBSCAN clustering for 150 objects.
Parameters: minPts = 5
The clustering contains 2 cluster(s) and 0 noise points.

  1   2 
100  50 

Available fields: cluster, minPts, cluster_scores, membership_prob, outlier_scores, hc

聚类后,一共分成了2组,第1组100个值,第2组50个值,没有噪声点。生成的hcl对象包括6个属性。
属性解释

  • cluster,表明属性哪个群集,零表示噪声点。
  • minPts,群集中最小的数量
  • cluster_scores,每个突出(“平坦”)群集的稳定性分数之和。
  • membership_prob,群集内某点的“概率”或个体稳定性
  • outlier_scores,每个点的异常值
  • hc,层次结构对象

把聚类的结果画图展示。

> plot(iris2, col=hcl$cluster+1, pch=20)

数据集是多列的,把每2列组合形成的二维平面,都进行输出。红色点表示第1组,绿色点表示为第2组,这样就完成了hdbscan聚类。

打印hcl对象层次结构,包括150个数据,聚法方法是健壮单一的,距离是相互可达。

> hcl$hc

Call:
hdbscan(x = iris2, minPts = 5)

Cluster method   : robust single 
Distance         : mutual reachability 
Number of objects: 150 

画出层次的合并过程图

> plot(hcl$hc, main="HDBSCAN* Hierarchy")

从图可以清楚的看出,主要的2类的分支,区分度比较高。

5.2 moons数据集
由于iris数据集用hdbscan聚类获得的结果,与真实的数据分类结果不一致。我们再用dbscan包自带的数据集moons做一下测试。

先准备数据,加载moons数据集,了解数据基本情况,画出散点图。

# 加载dbscan自带数据集
> data("moons")
> head(moons)
            X          Y
1 -0.41520756  1.0357347
2  0.05878098  0.3043343
3  1.10937860 -0.5097378
4  1.54094828 -0.4275496
5  0.92909498 -0.5323878
6 -0.86932470  0.5471548

# 画出散点图
> plot(moons, pch=20)

用hdbscan()函数,实现层次dbscan算法。


> cl <- hdbscan(moons, minPts = 5)
> cl
HDBSCAN clustering for 100 objects.
Parameters: minPts = 5
The clustering contains 3 cluster(s) and 0 noise points.

 1  2  3 
25 25 50 

Available fields: cluster, minPts, cluster_scores, membership_prob, outlier_scores, hc

一共100条数据,被分成了3类,没有噪声。把聚类的结果画图展示。


# 画图
> plot(moons, col=cl$cluster+1, pch=20)

打印层次结构


> cl$hc
Call:
hdbscan(x = moons, minPts = 5)

Cluster method   : robust single 
Distance         : mutual reachability 
Number of objects: 100 

画出层次的合并过程图

> plot(cl$hc, main="HDBSCAN* Hierarchy")

从图可以清楚的看出,主要的3类的分支,区分度比较高。

如果我们想省略分层的细节,我们可以只画出主要分支,并标识类别。

plot(cl, gradient = c("purple", "blue", "green", "yellow"), show_flat = T)

接下来,我们要对群集的稳定性做一些优化,cluster_scores属性可以查看集群的得分。

> cl$cluster_scores
        1         2         3 
110.70613  90.86559  45.62762 

通过membership_prob属性,画图表示个体的稳定性。

# 打印membership_prob
> head(cl$membership_prob)
[1] 0.4354753 0.2893287 0.4778663 0.4035933 0.4574012 0.4904582

# 计算群集的数量
> num<-length(cl$cluster_scores)

# 从彩虹色中取得对应数量的颜色
> rains<-rainbow(num)
> cols<-cl$cluster
> cols[which(cols==1)]<-rains[1]
> cols[which(cols==2)]<-rains[2]
> cols[which(cols==3)]<-rains[3]

# 设置透明度,表示个体的稳定性
> plot(moons, col=alpha(cols,cl$membership_prob), pch=19)

最后,我们可以在图中,在标记出异常值得分最高的前6个点。

# 对异常值进行排序,取得分最高的
> top_outliers <- order(cl$outlier_scores, decreasing = TRUE) %>% head
> plot(moons, col=alpha(cols,cl$outlier_scores), pch=19)
> text(moons[top_outliers, ], labels = top_outliers, pos=3)

从图中看到,异常得分高的点(outlier_scores)与个体的稳定性(membership_prob),并不是同一类点。异常值通常被认为是,偏离其假定的基础分布的离群点。

通过上面3个函数的使用案例,我们了解了如何用dbscan包实现基于密度的聚类方法。真实世界的数据是复杂的,我们用来分析数据的工具也是多样的,多掌握一种工具、多一些知识积累,让我们迎接真实世界数据的挑战吧。

转载请注明出处:
http://blog.fens.me/r-cluster-dbscan

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Mahout分步式程序开发 聚类Kmeans

Hadoop家族系列文章,主要介绍Hadoop家族产品,常用的项目包括Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, Chukwa,新增加的项目包括,YARN, Hcatalog, Oozie, Cassandra, Hama, Whirr, Flume, Bigtop, Crunch, Hue等。

从2011年开始,中国进入大数据风起云涌的时代,以Hadoop为代表的家族软件,占据了大数据处理的广阔地盘。开源界及厂商,所有数据软件,无一不向Hadoop靠拢。Hadoop也从小众的高富帅领域,变成了大数据开发的标准。在Hadoop原有技术基础之上,出现了Hadoop家族产品,通过“大数据”概念不断创新,推出科技进步。

作为IT界的开发人员,我们也要跟上节奏,抓住机遇,跟着Hadoop一起雄起!

关于作者:

  • 张丹(Conan), 程序员Java,R,PHP,Javascript
  • weibo:@Conan_Z
  • blog: http://blog.fens.me
  • email: bsspirit@gmail.com

转载请注明出处:
http://blog.fens.me/hadoop-mahout-kmeans/

mahout-kmeans

前言

Mahout是基于Hadoop用于机器学习的程序开发框架,Mahout封装了3大类的机器学习算法,其中包括聚类算法。kmeans是我们经常会提到用到的聚类算法之一,特别处理未知数据集的时,都会先聚类一下,看看数据集会有一些什么样的规则。

本文主要讲解,基于Mahout程序开发,实现分步式的kmeans算法。

目录

  1. 聚类算法kmeans
  2. Mahout开发环境介绍
  3. 用Mahout实现聚类算法kmeans
  4. 用R语言可视化结果
  5. 模板项目上传github

1. 聚类算法kmeans

聚类分析是数据挖掘及机器学习领域内的重点问题之一,在数据挖掘、模式识别、决策支持、机器学习及图像分割等领域有广泛的应用,是最重要的数据分析方法之一。聚类是在给定的数据集合中寻找同类的数据子集合,每一个子集合形成一个类簇,同类簇中的数据具有更大的相似性。聚类算法大体上可分为基于划分的方法、基于层次的方法、基于密度的方法、基于网格的方法以及基于模型的方法。

k-means algorithm算法是一种得到最广泛使用的基于划分的聚类算法,把n个对象分为k个簇,以使簇内具有较高的相似度。相似度的计算根据一个簇中对象的平均值来进行。它与处理混合正态分布的最大期望算法很相似,因为他们都试图找到数据中自然聚类的中心。

算法首先随机地选择k个对象,每个对象初始地代表了一个簇的平均值或中心。对剩余的每个对象根据其与各个簇中心的距离,将它赋给最近的簇,然后重新计算每个簇的平均值。这个过程不断重复,直到准则函数收敛。

kmeans介绍摘自:http://zh.wikipedia.org/wiki/K平均算法

2. Mahout开发环境介绍

接上一篇文章:Mahout分步式程序开发 基于物品的协同过滤ItemCF

所有环境变量 和 系统配置 与上文一致!

3. 用Mahout实现聚类算法kmeans

实现步骤:

  • 1. 准备数据文件: randomData.csv
  • 2. Java程序:KmeansHadoop.java
  • 3. 运行程序
  • 4. 聚类结果解读
  • 5. HDFS产生的目录

1). 准备数据文件: randomData.csv
数据文件randomData.csv,由R语言通过“随机正太分布函数”程序生成,单机内存实验请参考文章:
用Maven构建Mahout项目

原始数据文件:这里只截取了一部分数据。


~ vi datafile/randomData.csv

-0.883033363823402 -3.31967192630249
-2.39312626419456 3.34726861118871
2.66976353341256 1.85144276077058
-1.09922906899594 -6.06261735207489
-4.36361936997216 1.90509905380532
-0.00351835125495037 -0.610105996559153
-2.9962958796338 -3.60959839525735
-3.27529418132066 0.0230099799641799
2.17665594420569 6.77290756817957
-2.47862038335637 2.53431833167278
5.53654901906814 2.65089785582474
5.66257474538338 6.86783609641077
-0.558946883114376 1.22332819416237
5.11728525486132 3.74663871584768
1.91240516693351 2.95874731384062
-2.49747101306535 2.05006504756875
3.98781883213459 1.00780938946366
5.47470532716682 5.35084411045171

注:由于Mahout中kmeans算法,默认的分融符是” “(空格),因些我把逗号分隔的数据文件,改成以空格分隔。

2). Java程序:KmeansHadoop.java

kmeans的算法实现,请查看Mahout in Action。

mahout-kmeans-process


package org.conan.mymahout.cluster08;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.mapred.JobConf;
import org.apache.mahout.clustering.conversion.InputDriver;
import org.apache.mahout.clustering.kmeans.KMeansDriver;
import org.apache.mahout.clustering.kmeans.RandomSeedGenerator;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.distance.EuclideanDistanceMeasure;
import org.apache.mahout.utils.clustering.ClusterDumper;
import org.conan.mymahout.hdfs.HdfsDAO;
import org.conan.mymahout.recommendation.ItemCFHadoop;

public class KmeansHadoop {
    private static final String HDFS = "hdfs://192.168.1.210:9000";

    public static void main(String[] args) throws Exception {
        String localFile = "datafile/randomData.csv";
        String inPath = HDFS + "/user/hdfs/mix_data";
        String seqFile = inPath + "/seqfile";
        String seeds = inPath + "/seeds";
        String outPath = inPath + "/result/";
        String clusteredPoints = outPath + "/clusteredPoints";

        JobConf conf = config();
        HdfsDAO hdfs = new HdfsDAO(HDFS, conf);
        hdfs.rmr(inPath);
        hdfs.mkdirs(inPath);
        hdfs.copyFile(localFile, inPath);
        hdfs.ls(inPath);

        InputDriver.runJob(new Path(inPath), new Path(seqFile), "org.apache.mahout.math.RandomAccessSparseVector");

        int k = 3;
        Path seqFilePath = new Path(seqFile);
        Path clustersSeeds = new Path(seeds);
        DistanceMeasure measure = new EuclideanDistanceMeasure();
        clustersSeeds = RandomSeedGenerator.buildRandom(conf, seqFilePath, clustersSeeds, k, measure);
        KMeansDriver.run(conf, seqFilePath, clustersSeeds, new Path(outPath), measure, 0.01, 10, true, 0.01, false);

        Path outGlobPath = new Path(outPath, "clusters-*-final");
        Path clusteredPointsPath = new Path(clusteredPoints);
        System.out.printf("Dumping out clusters from clusters: %s and clusteredPoints: %s\n", outGlobPath, clusteredPointsPath);

        ClusterDumper clusterDumper = new ClusterDumper(outGlobPath, clusteredPointsPath);
        clusterDumper.printClusters(null);
    }
    
    public static JobConf config() {
        JobConf conf = new JobConf(ItemCFHadoop.class);
        conf.setJobName("ItemCFHadoop");
        conf.addResource("classpath:/hadoop/core-site.xml");
        conf.addResource("classpath:/hadoop/hdfs-site.xml");
        conf.addResource("classpath:/hadoop/mapred-site.xml");
        return conf;
    }

}

3). 运行程序
控制台输出:


Delete: hdfs://192.168.1.210:9000/user/hdfs/mix_data
Create: hdfs://192.168.1.210:9000/user/hdfs/mix_data
copy from: datafile/randomData.csv to hdfs://192.168.1.210:9000/user/hdfs/mix_data
ls: hdfs://192.168.1.210:9000/user/hdfs/mix_data
==========================================================
name: hdfs://192.168.1.210:9000/user/hdfs/mix_data/randomData.csv, folder: false, size: 36655
==========================================================
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
2013-10-14 15:39:31 org.apache.hadoop.util.NativeCodeLoader 
警告: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2013-10-14 15:39:31 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:31 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:31 org.apache.hadoop.io.compress.snappy.LoadSnappy 
警告: Snappy native library not loaded
2013-10-14 15:39:31 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0001
2013-10-14 15:39:31 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:31 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:31 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:31 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0001_m_000000_0 is allowed to commit now
2013-10-14 15:39:31 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0001_m_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/seqfile
2013-10-14 15:39:31 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:31 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0001_m_000000_0' done.
2013-10-14 15:39:32 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 0%
2013-10-14 15:39:32 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0001
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息: Counters: 11
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=31390
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=36655
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=475910
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=36655
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=506350
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=68045
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=0
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=188284928
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=124
2013-10-14 15:39:32 org.apache.hadoop.mapred.Counters log
信息:     Map output records=1000
2013-10-14 15:39:32 org.apache.hadoop.io.compress.CodecPool getCompressor
信息: Got brand-new compressor
2013-10-14 15:39:32 org.apache.hadoop.io.compress.CodecPool getDecompressor
信息: Got brand-new decompressor
2013-10-14 15:39:32 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:32 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:32 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0002
2013-10-14 15:39:32 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:32 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:32 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:32 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:33 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:33 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0002_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:33 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0002_m_000000_0' done.
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:33 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:33 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 623 bytes
2013-10-14 15:39:33 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0002_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:33 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0002_r_000000_0 is allowed to commit now
2013-10-14 15:39:33 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0002_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-1
2013-10-14 15:39:33 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:33 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0002_r_000000_0' done.
2013-10-14 15:39:33 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:33 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0002
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=4239303
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=203963
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=4457168
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=140321
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=627
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=612
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=376569856
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:33 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:34 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:34 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:34 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0003
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:34 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:34 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:34 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:34 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:34 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0003_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:34 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0003_m_000000_0' done.
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:34 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:34 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:34 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:34 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0003_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:34 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0003_r_000000_0 is allowed to commit now
2013-10-14 15:39:34 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0003_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-2
2013-10-14 15:39:34 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:34 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0003_r_000000_0' done.
2013-10-14 15:39:35 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:35 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0003
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=7527467
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=271193
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=7901744
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=142099
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=575930368
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:35 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:35 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:35 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:35 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0004
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:35 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:35 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:35 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:35 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:35 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0004_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:35 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0004_m_000000_0' done.
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:35 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:35 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:35 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0004_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:35 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0004_r_000000_0 is allowed to commit now
2013-10-14 15:39:35 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0004_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-3
2013-10-14 15:39:35 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:35 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0004_r_000000_0' done.
2013-10-14 15:39:36 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:36 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0004
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=10815685
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=338143
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=11346320
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=143877
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=775290880
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:36 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:36 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:36 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:36 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0005
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:36 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:36 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:36 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:36 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:36 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0005_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:36 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0005_m_000000_0' done.
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:36 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:36 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:36 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0005_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:36 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0005_r_000000_0 is allowed to commit now
2013-10-14 15:39:36 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0005_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-4
2013-10-14 15:39:36 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:36 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0005_r_000000_0' done.
2013-10-14 15:39:37 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:37 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0005
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=14103903
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=405093
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=14790888
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=145655
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=974651392
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:37 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:37 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:37 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:37 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0006
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:37 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:37 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:37 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:37 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:37 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0006_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:37 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0006_m_000000_0' done.
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:37 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:37 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:37 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0006_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:37 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0006_r_000000_0 is allowed to commit now
2013-10-14 15:39:37 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0006_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-5
2013-10-14 15:39:37 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:37 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0006_r_000000_0' done.
2013-10-14 15:39:38 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:38 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0006
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=17392121
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=472043
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=18235456
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=147433
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1174011904
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:38 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:38 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:38 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:38 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0007
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:38 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:38 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:38 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:38 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:38 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0007_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:38 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0007_m_000000_0' done.
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:38 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:38 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:38 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0007_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:38 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0007_r_000000_0 is allowed to commit now
2013-10-14 15:39:38 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0007_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-6
2013-10-14 15:39:38 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:38 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0007_r_000000_0' done.
2013-10-14 15:39:39 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:39 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0007
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=20680339
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=538993
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=21680040
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=149211
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1373372416
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:39 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:39 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:39 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:39 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0008
2013-10-14 15:39:39 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:39 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:39 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:39 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:39 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:40 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0008_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:40 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0008_m_000000_0' done.
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:40 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:40 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:40 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0008_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:40 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0008_r_000000_0 is allowed to commit now
2013-10-14 15:39:40 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0008_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-7
2013-10-14 15:39:40 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:40 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0008_r_000000_0' done.
2013-10-14 15:39:40 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:40 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0008
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=23968557
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=605943
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=25124624
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=150989
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1572732928
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:40 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:41 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:41 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:41 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0009
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:41 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:41 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:41 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:41 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:41 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0009_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:41 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0009_m_000000_0' done.
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:41 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:41 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:41 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:41 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0009_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:41 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0009_r_000000_0 is allowed to commit now
2013-10-14 15:39:41 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0009_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-8
2013-10-14 15:39:41 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:41 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0009_r_000000_0' done.
2013-10-14 15:39:42 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:42 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0009
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=27256775
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=673669
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=28569192
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=152767
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1772093440
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:42 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:42 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:42 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:42 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0010
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:42 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:42 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:42 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:42 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:42 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0010_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:42 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0010_m_000000_0' done.
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:42 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:42 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:42 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0010_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:42 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0010_r_000000_0 is allowed to commit now
2013-10-14 15:39:42 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0010_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-9
2013-10-14 15:39:42 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:42 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0010_r_000000_0' done.
2013-10-14 15:39:43 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:43 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0010
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=30544993
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=741007
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=32013760
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=154545
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1966735360
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:43 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:43 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:43 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:43 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0011
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:43 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: io.sort.mb = 100
2013-10-14 15:39:43 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: data buffer = 79691776/99614720
2013-10-14 15:39:43 org.apache.hadoop.mapred.MapTask$MapOutputBuffer 
信息: record buffer = 262144/327680
2013-10-14 15:39:43 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
信息: Starting flush of map output
2013-10-14 15:39:43 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
信息: Finished spill 0
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0011_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:43 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0011_m_000000_0' done.
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:43 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Merging 1 sorted segments
2013-10-14 15:39:43 org.apache.hadoop.mapred.Merger$MergeQueue merge
信息: Down to the last merge-pass, with 1 segments left of total size: 677 bytes
2013-10-14 15:39:43 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0011_r_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:43 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0011_r_000000_0 is allowed to commit now
2013-10-14 15:39:43 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0011_r_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-10
2013-10-14 15:39:43 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: reduce > reduce
2013-10-14 15:39:43 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0011_r_000000_0' done.
2013-10-14 15:39:44 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 100%
2013-10-14 15:39:44 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0011
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息: Counters: 19
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=695
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=33833211
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=808345
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=35458320
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=156323
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Map output materialized bytes=681
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Reduce shuffle bytes=0
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=6
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Map output bytes=666
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=2166095872
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Combine input records=0
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Reduce input records=3
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Reduce input groups=3
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Combine output records=0
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Reduce output records=3
2013-10-14 15:39:44 org.apache.hadoop.mapred.Counters log
信息:     Map output records=3
2013-10-14 15:39:44 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
2013-10-14 15:39:44 org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
信息: Total input paths to process : 1
2013-10-14 15:39:44 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Running job: job_local_0012
2013-10-14 15:39:44 org.apache.hadoop.mapred.Task initialize
信息:  Using ResourceCalculatorPlugin : null
2013-10-14 15:39:44 org.apache.hadoop.mapred.Task done
信息: Task:attempt_local_0012_m_000000_0 is done. And is in the process of commiting
2013-10-14 15:39:44 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:44 org.apache.hadoop.mapred.Task commit
信息: Task attempt_local_0012_m_000000_0 is allowed to commit now
2013-10-14 15:39:44 org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
信息: Saved output of task 'attempt_local_0012_m_000000_0' to hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusteredPoints
2013-10-14 15:39:44 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
信息: 
2013-10-14 15:39:44 org.apache.hadoop.mapred.Task sendDone
信息: Task 'attempt_local_0012_m_000000_0' done.
2013-10-14 15:39:45 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息:  map 100% reduce 0%
2013-10-14 15:39:45 org.apache.hadoop.mapred.JobClient monitorAndPrintJob
信息: Job complete: job_local_0012
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息: Counters: 11
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:   File Output Format Counters 
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Bytes Written=41520
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:   File Input Format Counters 
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Bytes Read=31390
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:   FileSystemCounters
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_READ=18560374
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_READ=437203
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     FILE_BYTES_WRITTEN=19450325
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     HDFS_BYTES_WRITTEN=120417
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:   Map-Reduce Framework
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Map input records=1000
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Spilled Records=0
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Total committed heap usage (bytes)=1083047936
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     SPLIT_RAW_BYTES=130
2013-10-14 15:39:45 org.apache.hadoop.mapred.Counters log
信息:     Map output records=1000
Dumping out clusters from clusters: hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-*-final and clusteredPoints: hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusteredPoints
CL-552{n=443 c=[1.631, -0.412] r=[1.563, 1.407]}
	Weight : [props - optional]:  Point:
	1.0: [-2.393, 3.347]
	1.0: [-4.364, 1.905]
	1.0: [-3.275, 0.023]
	1.0: [-2.479, 2.534]
	1.0: [-0.559, 1.223]
	...
	
CL-847{n=77 c=[-2.953, -0.971] r=[1.767, 2.189]}
	Weight : [props - optional]:  Point:
	1.0: [-0.883, -3.320]
	1.0: [-1.099, -6.063]
	1.0: [-0.004, -0.610]
	1.0: [-2.996, -3.610]
	1.0: [3.988, 1.008]
	...

CL-823{n=480 c=[0.219, 2.600] r=[1.479, 1.385]}
	Weight : [props - optional]:  Point:
	1.0: [2.670, 1.851]
	1.0: [2.177, 6.773]
	1.0: [5.537, 2.651]
	1.0: [5.663, 6.868]
	1.0: [5.117, 3.747]
	1.0: [1.912, 2.959]
	...

4). 聚类结果解读
我们可以把上面的日志分解析成3个部分解读

  • a. 初始化环境
  • b. 算法执行
  • c. 打印聚类结果

a. 初始化环境
出初HDFS的数据目录和工作目录,并上传数据文件。


Delete: hdfs://192.168.1.210:9000/user/hdfs/mix_data
Create: hdfs://192.168.1.210:9000/user/hdfs/mix_data
copy from: datafile/randomData.csv to hdfs://192.168.1.210:9000/user/hdfs/mix_data
ls: hdfs://192.168.1.210:9000/user/hdfs/mix_data
==========================================================
name: hdfs://192.168.1.210:9000/user/hdfs/mix_data/randomData.csv, folder: false, size: 36655

b. 算法执行
算法执行,有3个步骤。

  • 1):把原始数据randomData.csv,转成Mahout sequence files of VectorWritable。
  • 2):通过随机的方法,选中kmeans的3个中心,做为初始集群
  • 3):根据迭代次数的设置,执行MapReduce,进行计算

1):把原始数据randomData.csv,转成Mahout sequence files of VectorWritable。

程序源代码:


      InputDriver.runJob(new Path(inPath), new Path(seqFile), "org.apache.mahout.math.RandomAccessSparseVector");

日志输出:

Job complete: job_local_0001

2):通过随机的方法,选中kmeans的3个中心,做为初始集群

程序源代码:


        int k = 3;
        Path seqFilePath = new Path(seqFile);
        Path clustersSeeds = new Path(seeds);
        DistanceMeasure measure = new EuclideanDistanceMeasure();
        clustersSeeds = RandomSeedGenerator.buildRandom(conf, seqFilePath, clustersSeeds, k, measure);

日志输出:

Job complete: job_local_0002

3):根据迭代次数的设置,执行MapReduce,进行计算
程序源代码:


        KMeansDriver.run(conf, seqFilePath, clustersSeeds, new Path(outPath), measure, 0.01, 10, true, 0.01, false);

日志输出:


Job complete: job_local_0003
Job complete: job_local_0004
Job complete: job_local_0005
Job complete: job_local_0006
Job complete: job_local_0007
Job complete: job_local_0008
Job complete: job_local_0009
Job complete: job_local_0010
Job complete: job_local_0011
Job complete: job_local_0012

c. 打印聚类结果


Dumping out clusters from clusters: hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusters-*-final and clusteredPoints: hdfs://192.168.1.210:9000/user/hdfs/mix_data/result/clusteredPoints
CL-552{n=443 c=[1.631, -0.412] r=[1.563, 1.407]}
CL-847{n=77 c=[-2.953, -0.971] r=[1.767, 2.189]}
CL-823{n=480 c=[0.219, 2.600] r=[1.479, 1.385]}

运行结果:有3个中心。

  • Cluster1, 包括443个点,中心坐标[1.631, -0.412]
  • Cluster2, 包括77个点,中心坐标[-2.953, -0.971]
  • Cluster3, 包括480 个点,中心坐标[0.219, 2.600]

5). HDFS产生的目录


# 根目录
~ hadoop fs -ls /user/hdfs/mix_data
Found 4 items
-rw-r--r--   3 Administrator supergroup      36655 2013-10-04 15:31 /user/hdfs/mix_data/randomData.csv
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/seeds
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/seqfile

# 输出目录
~ hadoop fs -ls /user/hdfs/mix_data/result
Found 13 items
-rw-r--r--   3 Administrator supergroup        194 2013-10-04 15:31 /user/hdfs/mix_data/result/_policy
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusteredPoints
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-0
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-1
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-10-final
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-2
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-3
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-4
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-5
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-6
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-7
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-8
drwxr-xr-x   - Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/result/clusters-9

# 产生的随机中心种子目录
~ hadoop fs -ls /user/hdfs/mix_data/seeds
Found 1 items
-rw-r--r--   3 Administrator supergroup        599 2013-10-04 15:31 /user/hdfs/mix_data/seeds/part-randomSeed

# 输入文件换成Mahout格式文件的目录
~ hadoop fs -ls /user/hdfs/mix_data/seqfile
Found 2 items
-rw-r--r--   3 Administrator supergroup          0 2013-10-04 15:31 /user/hdfs/mix_data/seqfile/_SUCCESS
-rw-r--r--   3 Administrator supergroup      31390 2013-10-04 15:31 /user/hdfs/mix_data/seqfile/part-m-00000

4. 用R语言可视化结果

分别把聚类后的点,保存到不同的cluster*.csv文件,然后用R语言画图。


c1<-read.csv(file="cluster1.csv",sep=",",header=FALSE)
c2<-read.csv(file="cluster2.csv",sep=",",header=FALSE)
c3<-read.csv(file="cluster3.csv",sep=",",header=FALSE)
y<-rbind(c1,c2,c3)
cols<-c(rep(1,nrow(c1)),rep(2,nrow(c2)),rep(3,nrow(c3)))
plot(y, col=c("black","blue","green")[cols])
center<-matrix(c(1.631, -0.412,-2.953, -0.971,0.219, 2.600),ncol=2,byrow=TRUE)
points(center, col="violetred", pch = 19)

kmeans

从上图中,我们看到有 黑,蓝,绿,三种颜色的空心点,这些点就是原始数据。
3个紫色实点,是Mahout的kmeans后生成的3个中心。

对比文章中用R语言实现的kmeans的分类和中心,都不太一样。 用Maven构建Mahout项目

简单总结一下,在使用kmeans时,根据距离算法,阈值,出始中心,迭代次数的不同,kmeans计算的结果是不相同的。因此,用kmeans算法,我们一般只能得到一个模糊的分类标准,这个标准对于我们认识未知领域的数据集是很有帮助的。不能做为精确衡量数据的指标。

5. 模板项目上传github

https://github.com/bsspirit/maven_mahout_template/tree/mahout-0.8

大家可以下载这个项目,做为开发的起点。


~ git clone https://github.com/bsspirit/maven_mahout_template
~ git checkout mahout-0.8

这样,我们完成了Mahout的聚类算法Kmeans的分步式实现。接下来,我们会继续做关于Mahout中分类的实验!

转载请注明出处:
http://blog.fens.me/hadoop-mahout-kmeans/

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