我试图在第7章中运行hello world示例。我在eclipse中创建了以下内容,然后将其打包到jar中: -
package com.mycode.mahout
import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;
import org.apache.mahout.clustering.WeightedVectorWritable;
import org.apache.mahout.clustering.kmeans.Cluster;
import org.apache.mahout.clustering.kmeans.KMeansDriver;
import org.apache.mahout.common.distance.EuclideanDistanceMeasure;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
public class SimpleKMeansClustering {
public static final double[][] points = { {1, 1}, {2, 1}, {1, 2},
{2, 2}, {3, 3}, {8, 8},
{9, 8}, {8, 9}, {9, 9}};
public static void writePointsToFile(List<Vector> points,
String fileName,
FileSystem fs,
Configuration conf) throws IOException {
Path path = new Path(fileName);
SequenceFile.Writer writer = new SequenceFile.Writer(fs, conf,
path, LongWritable.class, VectorWritable.class);
long recNum = 0;
VectorWritable vec = new VectorWritable();
for (Vector point : points) {
vec.set(point);
writer.append(new LongWritable(recNum++), vec);
}
writer.close();
}
public static List<Vector> getPoints(double[][] raw) {
List<Vector> points = new ArrayList<Vector>();
for (int i = 0; i < raw.length; i++) {
double[] fr = raw[i];
Vector vec = new RandomAccessSparseVector(fr.length);
vec.assign(fr);
points.add(vec);
}
return points;
}
public static void main(String args[]) throws Exception {
int k = 2;
List<Vector> vectors = getPoints(points);
File testData = new File("testdata");
if (!testData.exists()) {
testData.mkdir();
}
testData = new File("testdata/points");
if (!testData.exists()) {
testData.mkdir();
}
Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(conf);
writePointsToFile(vectors, "testdata/points/file1", fs, conf);
Path path = new Path("testdata/clusters/part-00000");
SequenceFile.Writer writer = new SequenceFile.Writer(fs, conf,
path, Text.class, Cluster.class);
for (int i = 0; i < k; i++) {
Vector vec = vectors.get(i);
Cluster cluster = new Cluster(vec, i, new EuclideanDistanceMeasure());
writer.append(new Text(cluster.getIdentifier()), cluster);
}
writer.close();
KMeansDriver.run(conf, new Path("testdata/points"), new Path("testdata/clusters"),
new Path("output"), new EuclideanDistanceMeasure(), 0.001, 10,
true, false);
SequenceFile.Reader reader = new SequenceFile.Reader(fs,
new Path("output/" + Cluster.CLUSTERED_POINTS_DIR
+ "/part-m-00000"), conf);
IntWritable key = new IntWritable();
WeightedVectorWritable value = new WeightedVectorWritable();
while (reader.next(key, value)) {
System.out.println(value.toString() + " belongs to cluster "
+ key.toString());
}
reader.close();
}
}
我把它打包成myjob.jar
现在我该如何在群集上执行此操作?
我试过以下: -
hadoop jar myjob.jar com.mycode.mahout.SimpleKMeansClustering
java -jar myjob.jar
java -cp myjob.jar
我得到了以下错误: -
[root@node1 tmp]# hadoop jar mahoutfirst.jar com.mahout.emc.SimpleKMeansClustering
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/mahout/math/Vector`
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:270)
at org.apache.hadoop.util.RunJar.main(RunJar.java:201)
Caused by: java.lang.ClassNotFoundException: org.apache.mahout.math.Vector
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
... 3 more
请告知使用mahout运行代码的正确方法是什么。
答案 0 :(得分:3)
即使这已经很晚了但是我遇到了类似的问题并且以下方法对我有用,因为我不想使用maven:
1)转到你的mahout安装目录&amp;寻找* job.jar作为
ls /usr/lib/mahout/
conf lib mahout-core-0.5-cdh3u3-job.jar mahout-examples-0.5-cdh3u3-job.jar mahout-taste-webapp-0.5-cdh3u3.war
2)将mahout-examples-0.5-cdh3u3-job.jar复制到代码所在的目录
3)使用&#34; job&#34; JAR文件由Mahout提供。它打包了所有依赖项。您还需要将类添加到其中。当您使用hadoop和mahout库编译您的类时,您已准备好.class文件。
4)将您的类文件添加到目录中的作业jar mahout-core-0.5-cdh3u3-job.jar:
jar uf mahout-core-0.5-cdh3u3-job.jar SimpleKMeansClustering.class
4)使用你的代码运行hadoop jar:
hadoop jar mahout-core-0.5-cdh3u3-job.jar SimpleKMeansClustering
5)在map-reduce作业结束时,您可以看到:
1.0: [1.000, 1.000] belongs to cluster 0
1.0: [2.000, 1.000] belongs to cluster 0
1.0: [1.000, 2.000] belongs to cluster 0
1.0: [2.000, 2.000] belongs to cluster 0
1.0: [3.000, 3.000] belongs to cluster 0
1.0: [8.000, 8.000] belongs to cluster 1
1.0: [9.000, 8.000] belongs to cluster 1
1.0: [8.000, 9.000] belongs to cluster 1
1.0: [9.000, 9.000] belongs to cluster 1
答案 1 :(得分:0)
看看上面发现的非类定义异常,似乎你可能需要在你的Hadoop作业中包含Mahout相关的jar(mahout-core.jar,我猜)。
要将jar传递给整个集群中的映射器,您可能需要使用DistributedCache或-libjar
Hadoop选项。后者的想法是explained here。