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eclipse中开发Hadoop2.x的Map/Reduce项目集锦

热度：108   发布时间：2016-04-23 00:35:02.0
eclipse中开发Hadoop2.x的Map/Reduce项目汇总
问题导读：
1.如何创建MR程序？
2.如何配置运行参数？
3.HADOOP_HOME为空会出现什么问题？
4.hadoop-common-2.2.0-bin-master/bin的作用是什么？
扩展：
4.winutils.exe是什么？







本文总结了两个例子，分别从不同角度。
一、eclipse中开发Hadoop2.x的Map/Reduce项目
本文演示如何在Eclipse中开发一个Map/Reduce项目：
1、环境说明
  • Hadoop2.2.0
  • Eclipse Juno SR2
  • Hadoop2.x-eclipse-plugin 插件的编译安装配置的过程参考：http://www.micmiu.com/bigdata/hadoop/hadoop2-x-eclipse-plugin-build-install/
2、新建MR工程
依次点击 File → New → Ohter…??选择 “Map/Reduce Project”，然后输入项目名称:micmiu_MRDemo，创建新项目:
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?

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3、创建Mapper和Reducer
依次点击 File → New → Ohter… 选择Mapper，自动继承Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>
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创建Reducer的过程同Mapper，具体的业务逻辑自己实现即可。
本文就以官方自带的WordCount为例进行测试：

?

  1. package com.micmiu.mr;
  2. /**
  3. * Licensed to the Apache Software Foundation (ASF) under one
  4. * or more contributor license agreements.??See the NOTICE file
  5. * distributed with this work for additional information
  6. * regarding copyright ownership.??The ASF licenses this file
  7. * to you under the Apache License, Version 2.0 (the
  8. * "License"); you may not use this file except in compliance
  9. * with the License.??You may obtain a copy of the License at
  10. *
  11. *? ???http://www.apache.org/licenses/LICENSE-2.0
  12. *
  13. * Unless required by applicable law or agreed to in writing, software
  14. * distributed under the License is distributed on an "AS IS" BASIS,
  15. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  16. * See the License for the specific language governing permissions and
  17. * limitations under the License.
  18. */
  19. import java.io.IOException;
  20. import java.util.StringTokenizer;
  21. import org.apache.hadoop.conf.Configuration;
  22. import org.apache.hadoop.fs.Path;
  23. import org.apache.hadoop.io.IntWritable;
  24. import org.apache.hadoop.io.Text;
  25. import org.apache.hadoop.mapreduce.Job;
  26. import org.apache.hadoop.mapreduce.Mapper;
  27. import org.apache.hadoop.mapreduce.Reducer;
  28. import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
  29. import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
  30. import org.apache.hadoop.util.GenericOptionsParser;
  31. public class WordCount {
  32. ??public static class TokenizerMapper?
  33. ? ?? ? extends Mapper<Object, Text, Text, IntWritable>{
  34. ? ? private final static IntWritable one = new IntWritable(1);
  35. ? ? private Text word = new Text();
  36. ? ? public void map(Object key, Text value, Context context
  37. ? ?? ?? ?? ?? ?? ???) throws IOException, InterruptedException {
  38. ? ?? ?StringTokenizer itr = new StringTokenizer(value.toString());
  39. ? ?? ?while (itr.hasMoreTokens()) {
  40. ? ?? ???word.set(itr.nextToken());
  41. ? ?? ???context.write(word, one);
  42. ? ?? ?}
  43. ? ? }
  44. ??}
  45. ??public static class IntSumReducer?
  46. ? ?? ? extends Reducer<Text,IntWritable,Text,IntWritable> {
  47. ? ? private IntWritable result = new IntWritable();
  48. ? ? public void reduce(Text key, Iterable<IntWritable> values,?
  49. ? ?? ?? ?? ?? ?? ?? ???Context context
  50. ? ?? ?? ?? ?? ?? ?? ???) throws IOException, InterruptedException {
  51. ? ?? ?int sum = 0;
  52. ? ?? ?for (IntWritable val : values) {
  53. ? ?? ???sum += val.get();
  54. ? ?? ?}
  55. ? ?? ?result.set(sum);
  56. ? ?? ?context.write(key, result);
  57. ? ? }
  58. ??}
  59. ??public static void main(String[] args) throws Exception {
  60. ? ? Configuration conf = new Configuration();
  61. ? ? String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
  62. ? ? if (otherArgs.length != 2) {
  63. ? ?? ?System.err.println("Usage: wordcount <in> <out>");
  64. ? ?? ?System.exit(2);
  65. ? ? }
  66. ? ? //conf.set("fs.defaultFS", "hdfs://192.168.6.77:9000");
  67. ? ? Job job = new Job(conf, "word count");
  68. ? ? job.setJarByClass(WordCount.class);
  69. ? ? job.setMapperClass(TokenizerMapper.class);
  70. ? ? job.setCombinerClass(IntSumReducer.class);
  71. ? ? job.setReducerClass(IntSumReducer.class);
  72. ? ? job.setOutputKeyClass(Text.class);
  73. ? ? job.setOutputValueClass(IntWritable.class);
  74. ? ? FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
  75. ? ? FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
  76. ? ? System.exit(job.waitForCompletion(true) ? 0 : 1);
  77. ??}
  78. }
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4、准备测试数据
micmiu-01.txt：

?

  1. Hi Michael welcome to Hadoop?
  2. more see micmiu.com
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micmiu-02.txt：

  1. Hi Michael welcome to BigData
  2. more see micmiu.com
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micmiu-03.txt：

  1. Hi Michael welcome to Spark?
  2. more see micmiu.com
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把 micmiu 打头的三个文件上传到hdfs：

  1. micmiu-mbp:Downloads micmiu$ hdfs dfs -copyFromLocal micmiu-*.txt /user/micmiu/test/input
  2. micmiu-mbp:Downloads micmiu$ hdfs dfs -ls /user/micmiu/test/input
  3. Found 3 items
  4. -rw-r--r--? ?1 micmiu supergroup? ?? ?? ?50 2014-04-15 14:53 /user/micmiu/test/input/micmiu-01.txt
  5. -rw-r--r--? ?1 micmiu supergroup? ?? ?? ?50 2014-04-15 14:53 /user/micmiu/test/input/micmiu-02.txt
  6. -rw-r--r--? ?1 micmiu supergroup? ?? ?? ?49 2014-04-15 14:53 /user/micmiu/test/input/micmiu-03.txt
  7. micmiu-mbp:Downloads micmiu$
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5、配置运行参数
Run As → Run Configurations… ，在Arguments中配置运行参数，例如程序的输入参数：
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6、运行
Run As -> Run on Hadoop ，执行完成后可以看到如下信息：
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到此Eclipse中调用Hadoop2x本地伪分布式模式执行MR演示成功。
ps：调用集群环境MR运行一直失败，暂时没有找到原因。


上面说了一个整体的过程，下面详细描述了遇到的问题

二、Win7 Eclipse调试Centos Hadoop2.2-Mapreduce

?

1.搭建了一套Centos5.3 + Hadoop2.2 + Hbase0.96.1.1的开发环境，Win7 Eclipse调试MapReduce成功。

2. Hadoop安装
MapReduce的配置可以参考http://blog.sina.com.cn/s/blog_546abd9f0101i8b8.html。
安装成功后，能顺利查看以下几个页面，就OK了。我的集群环境是200master，201-203slave。
dfs.http.address? ?192.168.1.200:50070
dfs.secondary.http.address??192.168.1.200:50090
dfs.datanode.http.address??192.168.1.201:50075
yarn.resourcemanager.webapp.address??192.168.1.200:50030
mapreduce.jobhistory.webapp.address 192.168.1.200:19888。这个好像访问不了。需要启动hadoop/sbin/mr-jobhistory-daemon.sh start historyserver才可以访问。
三. Hadoop2.x eclispe-plugin
需要注意一点的是，Hadoop installation directory里填写Win下的hadoop home地址，其目的在于创建MapReduce Project能从这个地方自动引入MapReduce需要的jar。
插件可以从下面下载：
Hadoop 2.2.0编译hadoop-eclipse-plugin插件
hadoop-eclipse-plugin-2.2.0.jar插件包分享
四. 各种问题
1.上面一步完成后，创建一个MapReduce Project，运行时发现出问题了。
  1. java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
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跟代码就去发现是HADOOP_HOME的问题。如果HADOOP_HOME为空，必然fullExeName为null\bin\winutils.exe。解决方法很简单啦，乖乖的配置环境变量吧，不想重启电脑可以在MapReduce程序里加上System.setProperty("hadoop.home.dir", "...");暂时缓缓。org.apache.hadoop.util.Shell.java
  1. ??public static final String getQualifiedBinPath(String executable)?
  2. ??throws IOException {
  3. ? ? // construct hadoop bin path to the specified executable
  4. ? ? String fullExeName = HADOOP_HOME_DIR + File.separator + "bin"?
  5. ? ?? ?+ File.separator + executable;
  6. ? ? File exeFile = new File(fullExeName);
  7. ? ? if (!exeFile.exists()) {
  8. ? ?? ?throw new IOException("Could not locate executable " + fullExeName
  9. ? ?? ???+ " in the Hadoop binaries.");
  10. ? ? }
  11. ? ? return exeFile.getCanonicalPath();
  12. ??}
  13. private static String HADOOP_HOME_DIR = checkHadoopHome();
  14. private static String checkHadoopHome() {
  15. ? ? // first check the Dflag hadoop.home.dir with JVM scope
  16. ? ? String home = System.getProperty("hadoop.home.dir");
  17. ? ? // fall back to the system/user-global env variable
  18. ? ? if (home == null) {
  19. ? ?? ?home = System.getenv("HADOOP_HOME");
  20. ? ? }
  21. ? ???...
  22. }
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2.这个时候得到完整的地址fullExeName，我机器上是D:\Hadoop\tar\hadoop-2.2.0\hadoop-2.2.0\bin\winutils.exe。继续执行代码又发现了错误
  1. Could not locate executable D:\Hadoop\tar\hadoop-2.2.0\hadoop-2.2.0\bin\winutils.exe in the Hadoop binaries.
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就去一看，没有winutils.exe这个东西。去https://github.com/srccodes/hadoop-common-2.2.0-bin下载一个，放就去即可。
3.继续出问题
  1. at org.apache.hadoop.util.Shell.execCommand(Shell.java:661)
  2. at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:639)
  3. at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:435)
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继续跟代码org.apache.hadoop.util.Shell.java
  1. ??public static String[] getSetPermissionCommand(String perm, boolean recursive,
  2. ? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ? String file) {
  3. ? ? String[] baseCmd = getSetPermissionCommand(perm, recursive);
  4. ? ? String[] cmdWithFile = Arrays.copyOf(baseCmd, baseCmd.length + 1);
  5. ? ? cmdWithFile[cmdWithFile.length - 1] = file;
  6. ? ? return cmdWithFile;
  7. ??}
  8. ??/** Return a command to set permission */
  9. ??public static String[] getSetPermissionCommand(String perm, boolean recursive) {
  10. ? ? if (recursive) {
  11. ? ?? ?return (WINDOWS) ? new String[] { WINUTILS, "chmod", "-R", perm }
  12. ? ?? ?? ?? ?? ?? ?? ?? ? : new String[] { "chmod", "-R", perm };
  13. ? ? } else {
  14. ? ?? ?return (WINDOWS) ? new String[] { WINUTILS, "chmod", perm }
  15. ? ?? ?? ?? ?? ?? ?? ???: new String[] { "chmod", perm };
  16. ? ? }
  17. ??}
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cmdWithFile数组的内容为{"D:\Hadoop\tar\hadoop-2.2.0\hadoop-2.2.0\bin\winutils.exe", "chmod", "755", "xxxfile"}，我把这个单独在cmd里执行了一下，发现
无法启动此程序，因为计算机中丢失 MSVCR100.dll??

那就下载一个呗http://files.cnblogs.com/sirkevin/msvcr100.rar，丢到C:\Windows\System32里面。再次cmd执行，又来了问题
应用程序无法正常启动(0xc000007b)


下载http://blog.csdn.net/vbcom/article/details/7245186?,DirectX_Repair来解决这个问题吧。记得修复完后要重启电脑。搞定后cmd试一下，很棒。
4.到了这里，已经看到曙光了，但问题又来了
  1. Exception in thread "main" java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
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代码就去
  1. ? ? /** Windows only method used to check if the current process has requested
  2. ? ???*??access rights on the given path. */
  3. ? ? private static native boolean access0(String path, int requestedAccess);
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显然缺少dll文件，还记得https://github.com/srccodes/hadoop-common-2.2.0-bin下载的东西吧，里面就有hadoop.dll，最好的方法就是用hadoop-common-2.2.0-bin-master/bin目录替换本地hadoop的bin目录，并在环境变量里配置PATH=HADOOP_HOME/bin，重启电脑。
5.终于看到了MapReduce的正确输出output99。
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五. 总结?
hadoop eclipse插件不是必须的，其作用在我看来就是如下三点(这个是一个错误的认识，具体请参考http://zy19982004.iteye.com/blog/2031172)。study-hadoop是一个普通project，直接运行(不通过Run on Hadoop这只大象)，一样可以调试到MapReduce。
对hadoop中的文件可视化。
创建MapReduce Project时帮你引入依赖的jar。
Configuration conf = new Configuration();时就已经包含了所有的配置信息。
还是自己下载hadoop2.2的源码编译好，应该是不会有任何问题的(没有亲测)。


六. 其它问题

1.还是

  1. Exception in thread "main" java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
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代码跟到org.apache.hadoop.util.NativeCodeLoader.java去看

  1. ??static {
  2. ? ? // Try to load native hadoop library and set fallback flag appropriately
  3. ? ? if(LOG.isDebugEnabled()) {
  4. ? ?? ?LOG.debug("Trying to load the custom-built native-hadoop library...");
  5. ? ? }
  6. ? ? try {
  7. ? ?? ?System.loadLibrary("hadoop");
  8. ? ?? ?LOG.debug("Loaded the native-hadoop library");
  9. ? ?? ?nativeCodeLoaded = true;
  10. ? ? } catch (Throwable t) {
  11. ? ?? ?// Ignore failure to load
  12. ? ?? ?if(LOG.isDebugEnabled()) {
  13. ? ?? ???LOG.debug("Failed to load native-hadoop with error: " + t);
  14. ? ?? ???LOG.debug("java.library.path=" +
  15. ? ?? ?? ?? ?System.getProperty("java.library.path"));
  16. ? ?? ?}
  17. ? ? }
  18. ? ??
  19. ? ? if (!nativeCodeLoaded) {
  20. ? ?? ?LOG.warn("Unable to load native-hadoop library for your platform... " +
  21. ? ?? ?? ?? ?? ?"using builtin-java classes where applicable");
  22. ? ? }
  23. ??}
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这里报错如下

  1. DEBUG org.apache.hadoop.util.NativeCodeLoader - Failed to load native-hadoop with error: java.lang.UnsatisfiedLinkError: HADOOP_HOME\bin\hadoop.dll: Can't load AMD 64-bit .dll on a IA 32-bit platform
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怀疑是32位jdk的问题，替换成64位后，没问题了

  1. 2014-03-11 19:43:08,805 DEBUG org.apache.hadoop.util.NativeCodeLoader - Trying to load the custom-built native-hadoop library...
  2. 2014-03-11 19:43:08,812 DEBUG org.apache.hadoop.util.NativeCodeLoader - Loaded the native-hadoop library
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这里也解决了一个常见的警告

  1. WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
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