本文，简单介绍下，如何运行hadoop自带的mapreduce的那些例子。
本文针对的hadoop版本，是2.6.5版本，自带的例子包名为：hadoop-mapreduce-examples-2.6.5.jar；
位于/share/hadoop/mapreduce目录下。
简单来说，如果想要完成范例的运行，直接：
hadoop jar hadoop-mapreduce-examples-2.6.5.jar wordcount /input /output其中，hadoop命令配置了环境变量。
那么，这个执行具体是怎么实现的呢；或者说，如果我使用其他的名称，或者说WordCount首字母大写，因为解压缩该包能够看到WordCount.class文件的存在，能成功么？
答案是：不能。
为什么不能？
我们仔细分析下这个整体的运行过程，目标在于，我们能够实现在mapreduce-examples包内添加我们自己的类，而且能够实现自己的运行逻辑。
执行命令很简单，入口，看下hadoop的运行脚本：
elif [ "$COMMAND" = "jar" ] ; then
CLASS=org.apache.hadoop.util.RunJar很清楚，接下来需要注意的类，是RunJar类，而且指明了该类的位置，该命令，实际执行了RunJar中的main方法，我们看一下：
/**
* 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 main(String[] args) throws Throwable {
new RunJar().run(args);
}这里看的更清楚了，我们在运行其它程序的时候，或者说是自己随意打出来的一个包，我们可以在后面直接指定className，就可以成功运行出结果了，注意，这里需要的className必须是全名。
接下来，看看RunJar类中，run方法的内容：
public void run(String[] args) throws Throwable {
String usage = "RunJar 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);
if (!file.exists() || !file.isFile()) {
System.err.println("Not a valid JAR: " + file.getCanonicalPath());
System.exit(-1);
}
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"));
ensureDirectory(tmpDir);
final File workDir;
try {
workDir = File.createTempFile("hadoop-unjar", "", tmpDir);
} catch (IOException ioe) {
// If user has insufficient perms to write to tmpDir, default
// "Permission denied" message doesn't specify a filename.
System.err.println("Error creating temp dir in java.io.tmpdir "
+ tmpDir + " due to " + ioe.getMessage());
System.exit(-1);
return;
}
if (!workDir.delete()) {
System.err.println("Delete failed for " + workDir);
System.exit(-1);
}
ensureDirectory(workDir);
ShutdownHookManager.get().addShutdownHook(new Runnable() {
@Override
public void run() {
FileUtil.fullyDelete(workDir);
}
}, SHUTDOWN_HOOK_PRIORITY);
unJar(file, workDir);
ClassLoader loader = createClassLoader(file, workDir);
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();
}
}纵观全部的代码，很容易看懂，主要是解析我们的参数，然后将提交的包解压，其中需要注意这一句：
Manifest manifest = jarFile.getManifest();
if (manifest != null) {
mainClassName = manifest.getMainAttributes().getValue("Main-Class");
}跟上文对应，如果打包的文件中有这个ManiFest文件，且包含了Main-class的配置，那么，就会运行这个Main-class的main方法。
Class<?> mainClass = Class.forName(mainClassName, true, loader);
Method main = mainClass.getMethod("main", new Class[] { Array
.newInstance(String.class, 0).getClass() });最后的运行逻辑如下：
try {
main.invoke(null, new Object[] { newArgs });
} catch (InvocationTargetException e) {
throw e.getTargetException();
}可以看出，使用反射机制来运行，暂且不提，按照这一段的说法，运行的是MAINFEST内定义的Main-class，那么，我们看下，包里面是否有MAINFEST文件呢？
有的，对于2.6.5版本的hadoop来说，文件内容如下：
Manifest-Version: 1.0
Archiver-Version: Plexus Archiver
Created-By: Apache Maven
Built-By: YYZYHC
Build-Jdk: 1.8.0_131
Main-Class: org.apache.hadoop.examples.ExampleDriver非常清楚，接下来我们需要看一下，这个ExampleDriver是何方神圣：
public class ExampleDriver {
public static void main(String argv[]) {
int exitCode = -1;
ProgramDriver pgd = new ProgramDriver();
try {
pgd.addClass("wordcount", WordCount.class,
"A map/reduce program that counts the words in the input files.");
pgd.addClass(
"wordmean",
WordMean.class,
"A map/reduce program that counts the average length of the words in the input files.");
pgd.addClass(
"wordmedian",
WordMedian.class,
"A map/reduce program that counts the median length of the words in the input files.");
pgd.addClass(
"wordstandarddeviation",
WordStandardDeviation.class,
"A map/reduce program that counts the standard deviation of the length of the words in the input files.");
pgd.addClass(
"aggregatewordcount",
AggregateWordCount.class,
"An Aggregate based map/reduce program that counts the words in the input files.");
pgd.addClass(
"aggregatewordhist",
AggregateWordHistogram.class,
"An Aggregate based map/reduce program that computes the histogram of the words in the input files.");
pgd.addClass("grep", Grep.class,
"A map/reduce program that counts the matches of a regex in the input.");
pgd.addClass("randomwriter", RandomWriter.class,
"A map/reduce program that writes 10GB of random data per node.");
pgd.addClass("randomtextwriter", RandomTextWriter.class,
"A map/reduce program that writes 10GB of random textual data per node.");
pgd.addClass("sort", Sort.class,
"A map/reduce program that sorts the data written by the random writer.");
pgd.addClass("pi", QuasiMonteCarlo.class,
QuasiMonteCarlo.DESCRIPTION);
pgd.addClass("bbp", BaileyBorweinPlouffe.class,
BaileyBorweinPlouffe.DESCRIPTION);
pgd.addClass("distbbp", DistBbp.class, DistBbp.DESCRIPTION);
pgd.addClass("pentomino", DistributedPentomino.class,
"A map/reduce tile laying program to find solutions to pentomino problems.");
pgd.addClass("secondarysort", SecondarySort.class,
"An example defining a secondary sort to the reduce.");
pgd.addClass("sudoku", Sudoku.class, "A sudoku solver.");
pgd.addClass("join", Join.class,
"A job that effects a join over sorted, equally partitioned datasets");
pgd.addClass("multifilewc", MultiFileWordCount.class,
"A job that counts words from several files.");
pgd.addClass("dbcount", DBCountPageView.class,
"An example job that count the pageview counts from a database.");
pgd.addClass("teragen", TeraGen.class,
"Generate data for the terasort");
pgd.addClass("terasort", TeraSort.class, "Run the terasort");
pgd.addClass("teravalidate", TeraValidate.class,
"Checking results of terasort");
exitCode = pgd.run(argv);
} catch (Throwable e) {
e.printStackTrace();
}
System.exit(exitCode);
}
}这代码也很容易看懂，里面定义了一个ProgramDriver，这个类位于hadoop-common包下，具体内容不贴了，接下来介绍其中部分被ExampleDriver使用到的东西：
/**
* A description of a program based on its class and a human-readable
* description.
*/
Map<String, ProgramDescription> programs;
public ProgramDriver() {
programs = new TreeMap<String, ProgramDescription>();
}只有一个构造器，生成了一个TreeMap，key是String，value是ProgramDescription，其内没什么花样，主要是一个main的Method，一个String的description。
ExampleDriver中，ProgramDriver中添加了很多的class，最后执行了run方法，所以，接下来我们看下ProgramDriver中的run方法：
/**
* This is a driver for the example programs. It looks at the first command
* line argument and tries to find an example program with that name. If it
* is found, it calls the main method in that class with the rest of the
* command line arguments.
*
* @param args
* The argument from the user. args[0] is the command to run.
* @return -1 on error, 0 on success
* @throws NoSuchMethodException
* @throws SecurityException
* @throws IllegalAccessException
* @throws IllegalArgumentException
* @throws Throwable
* Anything thrown by the example program's main
*/
public int run(String[] args) throws Throwable {
// Make sure they gave us a program name.
if (args.length == 0) {
System.out.println("An example program must be given as the"
+ " first argument.");
printUsage(programs);
return -1;
}
// And that it is good.
ProgramDescription pgm = programs.get(args[0]);
if (pgm == null) {
System.out.println("Unknown program '" + args[0] + "' chosen.");
printUsage(programs);
return -1;
}
// Remove the leading argument and call main
String[] new_args = new String[args.length - 1];
for (int i = 1; i < args.length; ++i) {
new_args[i - 1] = args[i];
}
pgm.invoke(new_args);
return 0;
}这里，看的很清楚，先根据后续的参数，提取出对应的类，然后予以执行。
同样，我们定义的wordcount实质上就是上文中TreeMap的key，必须精确指定，才能让程序运行起来。
综上所述，运行Hadoop自带的MapReduce-examples的途径有以下几种：
- 修改打包的实现，删除MAINFEST中的Main-class，或者是修改Main-class的名称为自己想要的名称。
- 直接指定自己的className全名，简易便捷。
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