我发现调试和测试MapReduce项目很有挑战性。

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.log4j.Logger;
import org.json.simple.JSONArray;
import org.json.simple.JSONObject;
import org.json.simple.parser.JSONParser;
import org.json.simple.parser.ParseException;

import writables.Friend;
import writables.FriendArray;
import writables.FriendPair;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.StringTokenizer;

public class FacebookFriendsMapper extends Mapper<LongWritable, Text, FriendPair, FriendArray> {

    @Override
    public void map(LongWritable key, Text value, Context context)
            throws IOException, InterruptedException {

        Logger log = Logger.getLogger(FacebookFriendsMapper.class);

        StringTokenizer st = new StringTokenizer(value.toString(), "\t");
        String person = st.nextToken();
        String friends = st.nextToken();

        Friend f1 = populateFriend(person);
        List<Friend> friendList = populateFriendList(friends);
        Friend[] friendArray = Arrays.copyOf(friendList.toArray(), friendList.toArray().length, Friend[].class);
        FriendArray farray = new FriendArray(Friend.class, friendArray);

        for(Friend f2 : friendList) {
            FriendPair fpair = new FriendPair(f1, f2);
            context.write(fpair, farray);
            log.info(fpair+"......"+ farray);
        }

    }

    private Friend populateFriend(String friendJson) {

        JSONParser parser = new JSONParser();
        Friend friend = null;
        try {

            Object obj = (Object)parser.parse(friendJson);
            JSONObject jsonObject = (JSONObject) obj;

            Long lid = (long)jsonObject.get("id");
            IntWritable id = new IntWritable(lid.intValue());
            Text name = new Text((String)jsonObject.get("name"));
            Text hometown = new Text((String)jsonObject.get("hometown"));
            friend = new Friend(id, name, hometown);
        } catch (ParseException e) {
            e.printStackTrace();
        }

        return friend;
    }

    private List<Friend> populateFriendList(String friendsJson) {

        List<Friend> friendList = new ArrayList<Friend>();

        try {
            JSONParser parser = new JSONParser();
            Object obj = (Object)parser.parse(friendsJson.toString());
            JSONArray jsonarray = (JSONArray) obj;

            for(Object jobj : jsonarray) {
                JSONObject entry = (JSONObject)jobj;
                Long lid = (long)entry.get("id");
                IntWritable id = new IntWritable(lid.intValue());
                Text name = new Text((String)entry.get("name"));
                Text hometown = new Text((String)entry.get("hometown"));
                Friend friend = new Friend(id, name, hometown);
                friendList.add(friend);
            }
        } catch (ParseException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }

        return friendList;
    }

}

对于调试和测试，我通常会获取上面的脚本并将其放入另一个测试类的public static void main(String[] args)中，然后在Intellij IDEA的调试模式下运行，并从本地文件系统阅读样本数据，因此，我非常肯定Map器的逻辑是正确的。
关于Reducer脚本，我不确定Map器如何将其输出传递到Reducer的细节。我在研究期间检查了示例Reducer脚本，并得出了我的Reducer的初始版本，如下所示：

public class FacebookFriendsReducer extends 
    Reducer<FriendPair, FriendArray, FriendPair, FriendArray> {
    
    @Override
    public void reduce(FriendPair key, Iterable<FriendArray> values, Context context)
                    throws IOException, InterruptedException {
        
        }
}

这是我无法继续的地方，因为我无法模拟Map器如何将其输出传递到FacebookFriendsReducer和reduce方法。我目前的调试方法是在public static void main(String[] args)中编写reducer逻辑，然后在进程中以调试模式运行它，然后将其放入reducer类。
有人能告诉我如何将Map器的正确输出传递到Reduce中，以便我可以进一步处理逻辑吗？如果您有更好的替代方法，可以在打包成jar文件并将其发送到Hadoop集群之前，在本地窗口机器上调试和测试MapReduce，请告诉我。

编辑@OneCricketeer的答案：

您可以检查驱动程序（主类），如下所示：

public class FacebookFriendsDriver extends Configured implements Tool {

    @Override
    public int run(String[] args) throws Exception {

        String inputPath = "E:\\sampleInputPath\\inputFile";
        String outputPath = "E:\\sampleOutputPath\\outputFile";

//        if (args.length != 2) {
//            System.err.println("Usage: fberature <input path> <output path>");
//            System.exit(-1);
//        }

        //Job Setup
        Job fb = Job.getInstance(getConf(), "facebook-friends");

        fb.setJarByClass(FacebookFriendsDriver.class);

        //File Input and Output format
        FileInputFormat.addInputPath(fb, new Path(inputPath));
        FileOutputFormat.setOutputPath(fb, new Path(outputPath));

        fb.setInputFormatClass(TextInputFormat.class);
        fb.setOutputFormatClass(SequenceFileOutputFormat.class);

        //Mapper-Reducer-Combiner specifications
        fb.setMapperClass(FacebookFriendsMapper.class);
        fb.setReducerClass(FacebookFriendsReducer.class);

        fb.setMapOutputKeyClass(FriendPair.class);
        fb.setMapOutputValueClass(FriendArray.class);

        //Output key and value
        fb.setOutputKeyClass(FriendPair.class);
        fb.setOutputValueClass(FriendArray.class);

        //Submit job
        return fb.waitForCompletion(true) ? 0 : 1;

    }

    public static void main(String[] args) throws Exception {

        int exitCode = ToolRunner.run(new FacebookFriendsDriver(), args);
        System.exit(exitCode);
    }

}

上面的示例驱动程序类是我基于系统中现有的其他MapReduce作业创建的。但我无法使其在我的本地窗口计算机上工作，错误如下：

Connected to the target VM, address: '127.0.0.1:59143', transport: 'socket'
23/01/10 10:52:22 ERROR util.Shell: Failed to locate the winutils binary in the hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
    at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:324)
    at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:339)
    at org.apache.hadoop.util.Shell.<clinit>(Shell.java:332)
    at org.apache.hadoop.util.GenericOptionsParser.preProcessForWindows(GenericOptionsParser.java:431)
    at org.apache.hadoop.util.GenericOptionsParser.parseGeneralOptions(GenericOptionsParser.java:477)
    at org.apache.hadoop.util.GenericOptionsParser.<init>(GenericOptionsParser.java:171)
    at org.apache.hadoop.util.GenericOptionsParser.<init>(GenericOptionsParser.java:154)
    at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:64)
    at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:84)
    at FacebookFriendsDriver.main(FacebookFriendsDriver.java:60)
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/C:/Users/Holyken/.m2/repository/org/apache/hadoop/hadoop-auth/2.3.0-cdh5.1.0/hadoop-auth-2.3.0-cdh5.1.0.jar) to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
23/01/10 10:52:23 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
23/01/10 10:52:23 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
23/01/10 10:52:23 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
Exception in thread "main" java.lang.NullPointerException
    at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1090)
    at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1071)
    at org.apache.hadoop.util.Shell.runCommand(Shell.java:451)
    at org.apache.hadoop.util.Shell.run(Shell.java:424)
    at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:656)
    at org.apache.hadoop.util.Shell.execCommand(Shell.java:745)
    at org.apache.hadoop.util.Shell.execCommand(Shell.java:728)
    at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:633)
    at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:421)
    at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:281)
    at org.apache.hadoop.mapreduce.JobSubmissionFiles.getStagingDir(JobSubmissionFiles.java:126)
    at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:982)
    at org.apache.hadoop.mapred.JobClient$2.run(JobClient.java:976)
    at java.base/java.security.AccessController.doPrivileged(Native Method)
    at java.base/javax.security.auth.Subject.doAs(Subject.java:423)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1554)
    at org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:976)
    at org.apache.hadoop.mapreduce.Job.submit(Job.java:582)
    at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:612)
    at FacebookFriendsDriver.run(FacebookFriendsDriver.java:54)
    at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
    at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:84)
    at FacebookFriendsDriver.main(FacebookFriendsDriver.java:60)
Disconnected from the target VM, address: '127.0.0.1:59143', transport: 'socket'

您能否详细说明如何在本地文件系统上运行MapReduce作业？