Win7上eclipse无插件提交Hadoop2.2分布式作业

qindongliang1922

浏览: 2198306 次
性别:
来自: 北京

最近访客更多访客>>

北风norther

godandghost

youhere

tanss

博主相关

博客

微博

相册

留言

关于我

博客专栏

: 证道Lucene4
浏览量：117953

: 证道Hadoop
浏览量：126340

: 证道shell编程
浏览量：60304

: ELK修真
浏览量：71649

文章分类

社区版块

存档分类

博客分类：

Hadoop

hadoop eclipse linux mapreduce java

一直以来，都以为，想在Win上提交hadoop集群的作业，必须得在eclipse上安装hadoop-eclipse-plugin插件才可以提交，但最近与同事交流，发现其实，不一定必须安装hadoop的eclipse插件，才能提交。今天试了一把，发现果然可以不用安装插件也可以正确提交作业到集群上，故在此总结一下。

既然，无须安装hadoop的eclipse插件，就能提交hadoop作业，那为毛，还出现了这个插件呢？其实安装插件除了能直接提交作业外，还有一个比较方便的功能，就是能直接在eclipse上对HDFS上的文件，进行删除，上传，新建目录等，这一点是不安装插件做不到的，当然，如果你不需要这些操作，那么就无所谓了，仅仅提交个作业而已。

下面说下，如何在eclipse上使用无插件提交hadoop作业，（在hadoop集群的8088界面上可以看到提交的作业信息是否成功）。

序号	操作	说明
1	eclipse IDE	散仙在这里是4.2版本的eclipse
2	hadoop2.2的64位完整包	散仙在这里放在D盘根目录下
3	修改源码org/apache/hadoop/mapred/YARNRunner.java，改变linux与windows的路径不一致bug	散仙已经修改好，文末散仙会上传这个修改好的类
4	把linux集群上的配置文件，core-site.xml，hdfs-site.xml,mapred.site.xml和yarn-site.xml文件，放在src根目录下，另外在D盘hadoop的/etc/hadoop目录下，覆盖一下	注意一致
5	编写wordcount的MR例子，开始测试	入门测试
6	高富帅工程师一名	主角
7	配置hadoop的win上的环境变量HADOOP_HOME	只配置这一个即可

上面的操作都完成后，就可以进行测试了,散仙在这里的WordCount源码如下：

package com.mywordcount;

 

 
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FilenameFilter;
import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;

/***
 * 
 * Hadoop2.2.0  无插件提交集群作业
 * 
 * @author qindongliang
 * 
 *         hadoop技术交流群： 376932160
 * 
 * 
 * */
public class MyWordCount2 {

	/**
	 * Mapper
	 * 
	 * **/
	private static class WMapper extends
			Mapper<LongWritable, Text, Text, IntWritable> {

		private IntWritable count = new IntWritable(1);
		private Text text = new Text();

		@Override
		protected void map(LongWritable key, Text value, Context context)
				throws IOException, InterruptedException {
			String values[] = value.toString().split("#");
			// System.out.println(values[0]+"========"+values[1]);
			count.set(Integer.parseInt(values[1]));
			text.set(values[0]);
			context.write(text, count);

		}

	}

	/**
	 * Reducer
	 * 
	 * **/
	private static class WReducer extends
			Reducer<Text, IntWritable, Text, Text> {

		private Text t = new Text();

		@Override
		protected void reduce(Text key, Iterable<IntWritable> value,
				Context context) throws IOException, InterruptedException {
			int count = 0;
			for (IntWritable i : value) {
				count += i.get();
			}
			t.set(count + "");
			context.write(key, t);

		}

	}

	public static void printEnv(Job job) {
		Configuration conf = job.getConfiguration();
		System.out.println("###########################################");
		System.out.println("fs.defaultFS:" + conf.get("fs.defaultFS"));
		System.out.println("mapred.job.tracker:"
				+ conf.get("mapred.job.tracker"));
		System.out.println("mapreduce.framework.name" + ":"
				+ conf.get("mapreduce.framework.name"));
		System.out.println("yarn.nodemanager.aux-services" + ":"
				+ conf.get("yarn.nodemanager.aux-services"));
		System.out.println("yarn.resourcemanager.address" + ":"
				+ conf.get("yarn.resourcemanager.address"));
		System.out.println("yarn.resourcemanager.scheduler.address" + ":"
				+ conf.get("yarn.resourcemanager.scheduler.address"));
		System.out.println("yarn.resourcemanager.resource-tracker.address"
				+ ":"
				+ conf.get("yarn.resourcemanager.resource-tracker.address"));
		System.out.println("yarn.application.classpath" + ":"
				+ conf.get("yarn.application.classpath"));
		System.out.println("zkhost:" + conf.get("zkhost"));
		System.out.println("namespace:" + conf.get("namespace"));
		System.out.println("project:" + conf.get("project"));
		System.out.println("collection:" + conf.get("collection"));
		System.out.println("shard:" + conf.get("shard"));
		System.out.println("###########################################");
	}
	 /**
	  * 载入hadoop的配置文件
	  * 兼容hadoop1.x和hadoop2.x
	  * 
	  * */
	public static void getConf(final Configuration conf) throws FileNotFoundException{
		String HADOOP_CONF_DIR = System.getenv().get("HADOOP_CONF_DIR");
		String HADOOP_HOME = System.getenv().get("HADOOP_HOME");
		System.out.println("HADOOP_HOME:" + HADOOP_HOME);
		System.out.println("HADOOP_CONF_DIR:" + HADOOP_CONF_DIR);//此处兼容hadoop1.x
		
		//此处兼容hadoop2.x
		if (HADOOP_CONF_DIR == null || HADOOP_CONF_DIR.isEmpty()) {
			HADOOP_CONF_DIR = HADOOP_HOME + "/etc/hadoop";
		}

		//得到hadoop的conf目录的路径加载文件
		File file = new File(HADOOP_CONF_DIR);
		FilenameFilter filter = new FilenameFilter() {

			@Override
			public boolean accept(File dir, String name) {
				return name.endsWith("xml");
			}
		};
		
		
		//获取hadoop的仅仅xml结尾的文件列表
		String[] list = file.list(filter);
		for (String fn : list) {
			System.out.println("Loading Configuration: " + HADOOP_CONF_DIR
					+ "/" + fn);
			//循环加载xml文件
			conf.addResource(new FileInputStream(HADOOP_CONF_DIR + "/" + fn));
		}

		 
		
		//yarn的classpath路径，如果为空则加载拼接yarn的路径
		if (conf.get("yarn.application.classpath", "").isEmpty()) {
			StringBuilder sb = new StringBuilder();
			sb.append(System.getenv("CLASSPATH")).append(":");
			sb.append(HADOOP_HOME).append("/share/hadoop/common/lib/*")
					.append(":");
			sb.append(HADOOP_HOME).append("/share/hadoop/common/*").append(":");
			sb.append(HADOOP_HOME).append("/share/hadoop/hdfs/*").append(":");
			sb.append(HADOOP_HOME).append("/share/hadoop/mapreduce/*")
					.append(":");
			sb.append(HADOOP_HOME).append("/share/hadoop/yarn/*").append(":");
			sb.append(HADOOP_HOME).append("/lib/*").append(":");
			conf.set("yarn.application.classpath", sb.toString());
		}
		
		
		
		
		
		
	}
	
 

	public static void main(String[] args) throws Exception { {
			 
			Configuration conf = new Configuration();
			conf.set("mapreduce.job.jar", "myjob.jar");//此处代码，一定放在Job任务前面，否则会报类找不到的异常
			Job job = Job.getInstance(conf, "345");	 
			getConf(conf);
			job.setJarByClass(MyWordCount2.class);

			job.setMapperClass(WMapper.class);
			job.setReducerClass(WReducer.class);
			job.setInputFormatClass(TextInputFormat.class);
			job.setOutputFormatClass(TextOutputFormat.class);

			job.setMapOutputKeyClass(Text.class);
			job.setMapOutputValueClass(IntWritable.class);
			job.setOutputKeyClass(Text.class);
			job.setOutputValueClass(Text.class);

			String path = "/qin/output";
			FileSystem fs = FileSystem.get(conf);
			Path p = new Path(path);
			if (fs.exists(p)) {
				fs.delete(p, true);
				System.out.println("输出路径存在，已删除！");
			}
			FileInputFormat.setInputPaths(job, "/qin/input");
			FileOutputFormat.setOutputPath(job, p);
			printEnv(job);
			System.exit(job.waitForCompletion(true) ? 0 : 1); 
		 
	}

	}
}

项目结构目录，截图如下：

运行信息如下：

HADOOP_HOME:D:\hadoop-2.2.0
HADOOP_CONF_DIR:null
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/capacity-scheduler.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/core-site.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/hadoop-policy.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/hdfs-site.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/httpfs-site.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/mapred-site.xml
Loading Configuration: D:\hadoop-2.2.0/etc/hadoop/yarn-site.xml
2014-06-25 20:40:08,419 WARN  [main] conf.Configuration (Configuration.java:loadProperty(2172)) - java.io.FileInputStream@3ba08dab:an attempt to override final parameter: mapreduce.jobtracker.address;  Ignoring.
输出路径存在，已删除！
###########################################
fs.defaultFS:hdfs://h1:9000
2014-06-25 20:40:08,897 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address
mapred.job.tracker:h1:8021
mapreduce.framework.name:yarn
yarn.nodemanager.aux-services:mapreduce_shuffle
yarn.resourcemanager.address:h1:8032
yarn.resourcemanager.scheduler.address:h1:8030
yarn.resourcemanager.resource-tracker.address:h1:8031
yarn.application.classpath:$HADOOP_CONF_DIR,$HADOOP_COMMON_HOME/share/hadoop/common/*,$HADOOP_COMMON_HOME/share/hadoop/common/lib/*,$HADOOP_HDFS_HOME/share/hadoop/hdfs/*,$HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*,$HADOOP_YARN_HOME/share/hadoop/yarn/*,$HADOOP_YARN_HOME/share/hadoop/yarn/lib/*
zkhost:null
namespace:null
project:null
collection:null
shard:null
###########################################
2014-06-25 20:40:08,972 INFO  [main] client.RMProxy (RMProxy.java:createRMProxy(56)) - Connecting to ResourceManager at h1/192.168.46.32:8032
2014-06-25 20:40:09,153 WARN  [main] mapreduce.JobSubmitter (JobSubmitter.java:copyAndConfigureFiles(149)) - Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
2014-06-25 20:40:09,331 INFO  [main] input.FileInputFormat (FileInputFormat.java:listStatus(287)) - Total input paths to process : 1
2014-06-25 20:40:09,402 INFO  [main] mapreduce.JobSubmitter (JobSubmitter.java:submitJobInternal(394)) - number of splits:1
2014-06-25 20:40:09,412 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - user.name is deprecated. Instead, use mapreduce.job.user.name
2014-06-25 20:40:09,412 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.jar is deprecated. Instead, use mapreduce.job.jar
2014-06-25 20:40:09,413 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
2014-06-25 20:40:09,413 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.mapoutput.value.class is deprecated. Instead, use mapreduce.map.output.value.class
2014-06-25 20:40:09,413 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
2014-06-25 20:40:09,414 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.job.name is deprecated. Instead, use mapreduce.job.name
2014-06-25 20:40:09,414 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class
2014-06-25 20:40:09,414 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
2014-06-25 20:40:09,414 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
2014-06-25 20:40:09,414 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
2014-06-25 20:40:09,415 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
2014-06-25 20:40:09,416 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
2014-06-25 20:40:09,416 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
2014-06-25 20:40:09,416 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.mapoutput.key.class is deprecated. Instead, use mapreduce.map.output.key.class
2014-06-25 20:40:09,416 INFO  [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) - mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
2014-06-25 20:40:09,502 INFO  [main] mapreduce.JobSubmitter (JobSubmitter.java:printTokens(477)) - Submitting tokens for job: job_1403723552088_0016
2014-06-25 20:40:09,651 INFO  [main] impl.YarnClientImpl (YarnClientImpl.java:submitApplication(174)) - Submitted application application_1403723552088_0016 to ResourceManager at h1/192.168.46.32:8032
2014-06-25 20:40:09,683 INFO  [main] mapreduce.Job (Job.java:submit(1272)) - The url to track the job: http://h1:8088/proxy/application_1403723552088_0016/
2014-06-25 20:40:09,683 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1317)) - Running job: job_1403723552088_0016
2014-06-25 20:40:17,070 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1338)) - Job job_1403723552088_0016 running in uber mode : false
2014-06-25 20:40:17,072 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) -  map 0% reduce 0%
2014-06-25 20:40:23,232 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) -  map 100% reduce 0%
2014-06-25 20:40:30,273 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) -  map 100% reduce 100%
2014-06-25 20:40:30,289 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1356)) - Job job_1403723552088_0016 completed successfully
2014-06-25 20:40:30,403 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1363)) - Counters: 43
	File System Counters
		FILE: Number of bytes read=58
		FILE: Number of bytes written=160123
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=136
		HDFS: Number of bytes written=27
		HDFS: Number of read operations=6
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=2
	Job Counters 
		Launched map tasks=1
		Launched reduce tasks=1
		Data-local map tasks=1
		Total time spent by all maps in occupied slots (ms)=4398
		Total time spent by all reduces in occupied slots (ms)=4263
	Map-Reduce Framework
		Map input records=4
		Map output records=4
		Map output bytes=44
		Map output materialized bytes=58
		Input split bytes=98
		Combine input records=0
		Combine output records=0
		Reduce input groups=3
		Reduce shuffle bytes=58
		Reduce input records=4
		Reduce output records=3
		Spilled Records=8
		Shuffled Maps =1
		Failed Shuffles=0
		Merged Map outputs=1
		GC time elapsed (ms)=94
		CPU time spent (ms)=980
		Physical memory (bytes) snapshot=310431744
		Virtual memory (bytes) snapshot=1681850368
		Total committed heap usage (bytes)=136450048
	Shuffle Errors
		BAD_ID=0
		CONNECTION=0
		IO_ERROR=0
		WRONG_LENGTH=0
		WRONG_MAP=0
		WRONG_REDUCE=0
	File Input Format Counters 
		Bytes Read=38
	File Output Format Counters 
		Bytes Written=27

至此，我们已经可以成功的在无插件的环境里提交hadoop任务了，如果提交过程中，出现权限异常，可以在eclipse的run环境里配置，linux上安装hadoop的用户名即可，截图如下：