Win7上eclipse无插件提交Hadoop2.2分布式作业
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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1eclipse IDE散仙在这里是4.2版本的eclipse2hadoop2.2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:
项目结构目录,截图如下:
运行信息如下:
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:
注意,一定是安装hadoop的用户,写成其他的用户,可能会导致没有权限访问HDFS上的数据,从而使提交的作业运行失败。
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1eclipse IDE散仙在这里是4.2版本的eclipse2hadoop2.2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:
注意,一定是安装hadoop的用户,写成其他的用户,可能会导致没有权限访问HDFS上的数据,从而使提交的作业运行失败。
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