hadoop提交作业到云端问题解决

问题描述：

当按照Hadoop实战上讲述的用eclipse提交作业，其实作业是运行在eclipse虚拟的一个云环境中，而不是真正提交到Hadoop云端运行。在50030上也看不到job的运行记录，此时的代码如下：

package com.spork.hadoop.jobutil.test;

import java.io.File;
import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

import com.spork.hadoop.jobutil.EJob;

public class WordCountTest {

    public static class TokenizerMapper extends
            Mapper<Object, Text, Text, IntWritable> {

        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();

        public void map(Object key, Text value, Context context)
                throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                context.write(word, one);
            }
        }
    }

    public static class IntSumReducer extends
            Reducer<Text, IntWritable, Text, IntWritable> {
        private IntWritable result = new IntWritable();

        public void reduce(Text key, Iterable<IntWritable> values, Context context)
                throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception {
        
        
        Configuration conf = new Configuration();
        
        String[] inAndOut={"hdfs://localhost:9000/bin/in/1","hdfs://localhost:9000/out"};

        Job job = new Job(conf, "word count");

        job.setJarByClass(WordCountTest.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(inAndOut[0]));
        FileOutputFormat.setOutputPath(job, new Path(inAndOut[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

如果要将作业真正提交到云端，一种是用命令行打jar包，然后运行、提交作业，这方式比较笨，而程序员都是些懒人啊，能让机器做干嘛自己动手。具体实现可以参考这个博客：http://weixiaolu.iteye.com/blog/1402919

这里介绍一个更加智能的方式，其主要思路是将jar打包的工作放在了java代码中来完成。其中使用了一个工具类ejob.java。

示例代码如下：

package com.spork.hadoop.jobutil.test;

import java.io.File;
import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

import com.spork.hadoop.jobutil.EJob;

public class WordCountTest {

	public static class TokenizerMapper extends
			Mapper<Object, Text, Text, IntWritable> {

		private final static IntWritable one = new IntWritable(1);
		private Text word = new Text();

		public void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			StringTokenizer itr = new StringTokenizer(value.toString());
			while (itr.hasMoreTokens()) {
				word.set(itr.nextToken());
				context.write(word, one);
			}
		}
	}

	public static class IntSumReducer extends
			Reducer<Text, IntWritable, Text, IntWritable> {
		private IntWritable result = new IntWritable();

		public void reduce(Text key, Iterable<IntWritable> values, Context context)
				throws IOException, InterruptedException {
			int sum = 0;
			for (IntWritable val : values) {
				sum += val.get();
			}
			result.set(sum);
			context.write(key, result);
		}
	}

	public static void main(String[] args) throws Exception {
		// Add these statements. XXX
		File jarFile = EJob.createTempJar("bin");
		EJob.addClasspath("/usr/hadoop-1.2.1/conf");
		ClassLoader classLoader = EJob.getClassLoader();
		Thread.currentThread().setContextClassLoader(classLoader);
		
		Configuration conf = new Configuration();
		
		String[] inAndOut={"hdfs://localhost:9000/bin/in/1","hdfs://localhost:9000/out"};

		Job job = new Job(conf, "word count");
		// And add this statement. XXX
		((JobConf) job.getConfiguration()).setJar(jarFile.toString());

		job.setJarByClass(WordCountTest.class);
		job.setMapperClass(TokenizerMapper.class);
		job.setCombinerClass(IntSumReducer.class);
		job.setReducerClass(IntSumReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);
		FileInputFormat.addInputPath(job, new Path(inAndOut[0]));
		FileOutputFormat.setOutputPath(job, new Path(inAndOut[1]));
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}

 

ejob类的代码如下：

/**
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.spork.hadoop.jobutil;

import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.lang.reflect.Array;
import java.lang.reflect.InvocationTargetException;
import java.lang.reflect.Method;
import java.net.URL;
import java.net.URLClassLoader;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Enumeration;
import java.util.jar.JarEntry;
import java.util.jar.JarFile;
import java.util.jar.JarOutputStream;
import java.util.jar.Manifest;

public class EJob {

	private static ArrayList<URL> classPath = new ArrayList<URL>();

	/** Unpack a jar file into a directory. */
	public static void unJar(File jarFile, File toDir) throws IOException {
		JarFile jar = new JarFile(jarFile);
		try {
			Enumeration entries = jar.entries();
			while (entries.hasMoreElements()) {
				JarEntry entry = (JarEntry) entries.nextElement();
				if (!entry.isDirectory()) {
					InputStream in = jar.getInputStream(entry);
					try {
						File file = new File(toDir, entry.getName());
						if (!file.getParentFile().mkdirs()) {
							if (!file.getParentFile().isDirectory()) {
								throw new IOException("Mkdirs failed to create "
										+ file.getParentFile().toString());
							}
						}
						OutputStream out = new FileOutputStream(file);
						try {
							byte[] buffer = new byte[8192];
							int i;
							while ((i = in.read(buffer)) != -1) {
								out.write(buffer, 0, i);
							}
						} finally {
							out.close();
						}
					} finally {
						in.close();
					}
				}
			}
		} finally {
			jar.close();
		}
	}

	/**
	 * Run a Hadoop job jar. If the main class is not in the jar's manifest, then
	 * it must be provided on the command line.
	 */
	public static void runJar(String[] args) throws Throwable {
		String usage = "jarFile [mainClass] args...";

		if (args.length < 1) {
			System.err.println(usage);
			System.exit(-1);
		}

		int firstArg = 0;
		String fileName = args[firstArg++];
		File file = new File(fileName);
		String mainClassName = null;

		JarFile jarFile;
		try {
			jarFile = new JarFile(fileName);
		} catch (IOException io) {
			throw new IOException("Error opening job jar: " + fileName).initCause(io);
		}

		Manifest manifest = jarFile.getManifest();
		if (manifest != null) {
			mainClassName = manifest.getMainAttributes().getValue("Main-Class");
		}
		jarFile.close();

		if (mainClassName == null) {
			if (args.length < 2) {
				System.err.println(usage);
				System.exit(-1);
			}
			mainClassName = args[firstArg++];
		}
		mainClassName = mainClassName.replaceAll("/", ".");

		File tmpDir = new File(System.getProperty("java.io.tmpdir"));
		tmpDir.mkdirs();
		if (!tmpDir.isDirectory()) {
			System.err.println("Mkdirs failed to create " + tmpDir);
			System.exit(-1);
		}
		final File workDir = File.createTempFile("hadoop-unjar", "", tmpDir);
		workDir.delete();
		workDir.mkdirs();
		if (!workDir.isDirectory()) {
			System.err.println("Mkdirs failed to create " + workDir);
			System.exit(-1);
		}

		Runtime.getRuntime().addShutdownHook(new Thread() {
			public void run() {
				try {
					fullyDelete(workDir);
				} catch (IOException e) {
				}
			}
		});

		unJar(file, workDir);

		classPath.add(new File(workDir + "/").toURL());
		classPath.add(file.toURL());
		classPath.add(new File(workDir, "classes/").toURL());
		File[] libs = new File(workDir, "lib").listFiles();
		if (libs != null) {
			for (int i = 0; i < libs.length; i++) {
				classPath.add(libs[i].toURL());
			}
		}

		ClassLoader loader = new URLClassLoader(classPath.toArray(new URL[0]));

		Thread.currentThread().setContextClassLoader(loader);
		Class<?> mainClass = Class.forName(mainClassName, true, loader);
		Method main = mainClass.getMethod("main", new Class[] { Array.newInstance(
				String.class, 0).getClass() });
		String[] newArgs = Arrays.asList(args).subList(firstArg, args.length)
				.toArray(new String[0]);
		try {
			main.invoke(null, new Object[] { newArgs });
		} catch (InvocationTargetException e) {
			throw e.getTargetException();
		}
	}

	/**
	 * Delete a directory and all its contents. If we return false, the directory
	 * may be partially-deleted.
	 */
	public static boolean fullyDelete(File dir) throws IOException {
		File contents[] = dir.listFiles();
		if (contents != null) {
			for (int i = 0; i < contents.length; i++) {
				if (contents[i].isFile()) {
					if (!contents[i].delete()) {
						return false;
					}
				} else {
					// try deleting the directory
					// this might be a symlink
					boolean b = false;
					b = contents[i].delete();
					if (b) {
						// this was indeed a symlink or an empty directory
						continue;
					}
					// if not an empty directory or symlink let
					// fullydelete handle it.
					if (!fullyDelete(contents[i])) {
						return false;
					}
				}
			}
		}
		return dir.delete();
	}

	/**
	 * Add a directory or file to classpath.
	 * 
	 * @param component
	 */
	public static void addClasspath(String component) {
		if ((component != null) && (component.length() > 0)) {
			try {
				File f = new File(component);
				if (f.exists()) {
					URL key = f.getCanonicalFile().toURL();
					if (!classPath.contains(key)) {
						classPath.add(key);
					}
				}
			} catch (IOException e) {
			}
		}
	}

	/**
	 * Add default classpath listed in bin/hadoop bash.
	 * 
	 * @param hadoopHome
	 */
	public static void addDefaultClasspath(String hadoopHome) {
		// Classpath initially contains conf dir.
		addClasspath(hadoopHome + "/conf");

		// For developers, add Hadoop classes to classpath.
		addClasspath(hadoopHome + "/build/classes");
		if (new File(hadoopHome + "/build/webapps").exists()) {
			addClasspath(hadoopHome + "/build");
		}
		addClasspath(hadoopHome + "/build/test/classes");
		addClasspath(hadoopHome + "/build/tools");

		// For releases, add core hadoop jar & webapps to classpath.
		if (new File(hadoopHome + "/webapps").exists()) {
			addClasspath(hadoopHome);
		}
		addJarsInDir(hadoopHome);
		addJarsInDir(hadoopHome + "/build");

		// Add libs to classpath.
		addJarsInDir(hadoopHome + "/lib");
		addJarsInDir(hadoopHome + "/lib/jsp-2.1");
		addJarsInDir(hadoopHome + "/build/ivy/lib/Hadoop/common");
	}

	/**
	 * Add all jars in directory to classpath, sub-directory is excluded.
	 * 
	 * @param dirPath
	 */
	public static void addJarsInDir(String dirPath) {
		File dir = new File(dirPath);
		if (!dir.exists()) {
			return;
		}
		File[] files = dir.listFiles();
		if (files == null) {
			return;
		}
		for (int i = 0; i < files.length; i++) {
			if (files[i].isDirectory()) {
				continue;
			} else {
				addClasspath(files[i].getAbsolutePath());
			}
		}
	}

	/**
	 * Create a temp jar file in "java.io.tmpdir".
	 * 
	 * @param root
	 * @return
	 * @throws IOException
	 */
	public static File createTempJar(String root) throws IOException {
		if (!new File(root).exists()) {
			return null;
		}
		Manifest manifest = new Manifest();
		manifest.getMainAttributes().putValue("Manifest-Version", "1.0");
		final File jarFile = File.createTempFile("EJob-", ".jar", new File(System
				.getProperty("java.io.tmpdir")));

		Runtime.getRuntime().addShutdownHook(new Thread() {
			public void run() {
				jarFile.delete();
			}
		});

		JarOutputStream out = new JarOutputStream(new FileOutputStream(jarFile),
				manifest);
		createTempJarInner(out, new File(root), "");
		out.flush();
		out.close();
		return jarFile;
	}

	private static void createTempJarInner(JarOutputStream out, File f,
			String base) throws IOException {
		if (f.isDirectory()) {
			File[] fl = f.listFiles();
			if (base.length() > 0) {
				base = base + "/";
			}
			for (int i = 0; i < fl.length; i++) {
				createTempJarInner(out, fl[i], base + fl[i].getName());
			}
		} else {
			out.putNextEntry(new JarEntry(base));
			FileInputStream in = new FileInputStream(f);
			byte[] buffer = new byte[1024];
			int n = in.read(buffer);
			while (n != -1) {
				out.write(buffer, 0, n);
				n = in.read(buffer);
			}
			in.close();
		}
	}

	/**
	 * Return a classloader based on user-specified classpath and parent
	 * classloader.
	 * 
	 * @return
	 */
	public static ClassLoader getClassLoader() {
		ClassLoader parent = Thread.currentThread().getContextClassLoader();
		if (parent == null) {
			parent = EJob.class.getClassLoader();
		}
		if (parent == null) {
			parent = ClassLoader.getSystemClassLoader();
		}
		return new URLClassLoader(classPath.toArray(new URL[0]), parent);
	}

}

 

修改之后，50030就可以监测到job的运行状况了，而且看cpu的使用状态，各个cpu的占用率也上去了。

 

若想更加详细了解ejob的实现机理，可以参考下面的博客。

http://www.cnblogs.com/spork/archive/2010/04/21/1717592.html