java - Hadoop MapReduce : context. 写入更改值

Question

我是 Hadoop 的新手，正在编写 MapReduce 作业，我遇到了一个问题，它似乎是 reducers context.write 方法正在将正确的值更改为不正确的值。

MapReduce 作业应该做什么？

• 统计总字数(int wordCount)
• 计算不同单词的数量(int counter_dist)
• 统计以“z”或“Z”开头的单词数 (int counter_startZ)
• 统计出现次数少于4次的单词(int counter_less4)

所有这些都必须在单个 MapReduce 作业中完成。

正在分析的文本文件

Hello how zou zou zou zou how are you

正确输出:
wordCount = 9
counter_dist = 5
counter_startZ = 4
counter_less4 = 4

映射器类

public class WordCountMapper extends Mapper <Object, Text, Text, IntWritable> {

    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    @Override
    public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
        StringTokenizer itr = new StringTokenizer(value.toString());
        while (itr.hasMoreTokens()) {
            String hasKey = itr.nextToken();
            word.set(hasKey);
            context.write(word, one);
        }

    }
}

reducer 类
为了调试我的代码，我打印了很多语句来检查每个点的值。下面提供了标准输出代码。

public class WordCountReducer extends Reducer <Text, IntWritable, Text, IntWritable> {

    int wordCount = 0; // Total number of words
    int counter_dist = 0; // Number of distinct words in the corpus
    int counter_startZ = 0; // Number of words that start with letter Z
    int counter_less4 = 0; // Number of words that appear less than 4 

    @Override
    public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int repeatedWords = 0;
        System.out.println("###Reduce method starts");
        System.out.println("Values: wordCount:" + wordCount + " counter_dist:" + counter_dist + " counter_startZ:" + counter_startZ + " counter_less4:" + counter_less4 + " (start)");
        for (IntWritable val : values){
            System.out.println("Key: " + key.toString());
            repeatedWords++;
            wordCount += val.get();
            if(key.toString().startsWith("z") || key.toString().startsWith("Z")){
            counter_startZ++;
            }
            System.out.println("Values: wordCount:" + wordCount + " counter_dist:" + counter_dist + " counter_startZ:" + counter_startZ + " counter_less4:" + counter_less4 + " (end of loop)");
        }
        counter_dist++;

        if(repeatedWords < 4){
            counter_less4++;
        }

        System.out.println("Values: wordCount:" + wordCount + " counter_dist:" + counter_dist + " counter_startZ:" + counter_startZ + " counter_less4:" + counter_less4 + " repeatedWords:" + repeatedWords + " (end)");
        System.out.println("###Reduce method ends\n");
    }


    @Override
    public void cleanup(Context context) throws IOException, InterruptedException{
        System.out.println("###CLEANUP: wordCount: " + wordCount);
        System.out.println("###CLEANUP: counter_dist: " + counter_dist);
        System.out.println("###CLEANUP: counter_startZ: " + counter_startZ);
        System.out.println("###CLEANUP: counter_less4: " + counter_less4);

        context.write(new Text("Total words: "), new IntWritable(wordCount));
        context.write(new Text("Distinct words: "), new IntWritable(counter_dist));
        context.write(new Text("Starts with Z: "), new IntWritable(counter_startZ));
        context.write(new Text("Appears less than 4 times:"), new IntWritable(counter_less4));
    }


}

Stdout 日志，我正在使用它进行调试

###Reduce method starts
Values: wordCount:0 counter_dist:0 counter_startZ:0 counter_less4:0 (start)
Key: Hello
Values: wordCount:1 counter_dist:0 counter_startZ:0 counter_less4:0 (end of loop)
Values: wordCount:1 counter_dist:1 counter_startZ:0 counter_less4:1 repeatedWords:1 (end)
###Reduce method ends

###Reduce method starts
Values: wordCount:1 counter_dist:1 counter_startZ:0 counter_less4:1 (start)
Key: are
Values: wordCount:2 counter_dist:1 counter_startZ:0 counter_less4:1 (end of loop)
Values: wordCount:2 counter_dist:2 counter_startZ:0 counter_less4:2 repeatedWords:1 (end)
###Reduce method ends

###Reduce method starts
Values: wordCount:2 counter_dist:2 counter_startZ:0 counter_less4:2 (start)
Key: how
Values: wordCount:3 counter_dist:2 counter_startZ:0 counter_less4:2 (end of loop)
Key: how
Values: wordCount:4 counter_dist:2 counter_startZ:0 counter_less4:2 (end of loop)
Values: wordCount:4 counter_dist:3 counter_startZ:0 counter_less4:3 repeatedWords:2 (end)
###Reduce method ends

###Reduce method starts
Values: wordCount:4 counter_dist:3 counter_startZ:0 counter_less4:3 (start)
Key: you
Values: wordCount:5 counter_dist:3 counter_startZ:0 counter_less4:3 (end of loop)
Values: wordCount:5 counter_dist:4 counter_startZ:0 counter_less4:4 repeatedWords:1 (end)
###Reduce method ends

###Reduce method starts
Values: wordCount:5 counter_dist:4 counter_startZ:0 counter_less4:4 (start)
Key: zou
Values: wordCount:6 counter_dist:4 counter_startZ:1 counter_less4:4 (end of loop)
Key: zou
Values: wordCount:7 counter_dist:4 counter_startZ:2 counter_less4:4 (end of loop)
Key: zou
Values: wordCount:8 counter_dist:4 counter_startZ:3 counter_less4:4 (end of loop)
Key: zou
Values: wordCount:9 counter_dist:4 counter_startZ:4 counter_less4:4 (end of loop)
Values: wordCount:9 counter_dist:5 counter_startZ:4 counter_less4:4 repeatedWords:4 (end)
###Reduce method ends

###CLEANUP: wordCount: 9
###CLEANUP: counter_dist: 5
###CLEANUP: counter_startZ: 4
###CLEANUP: counter_less4: 4

从日志来看，所有值似乎都是正确的，并且一切正常。但是，当我打开 HDFS 中的输出目录并读取“part-r-00000”文件时，写入那里的 context.write 的输出完全不同。

Total words: 22
Distinct words: 4
Starts with Z: 0
Appears less than 4 times: 4

Answer 1

您绝不能依赖cleanup() 方法来处理关键的程序逻辑。 cleanup() 方法在每次删除 JVM 时都会被调用。因此，根据生成和终止的 JVM 数量(您无法预测)，您的逻辑会变得不稳定。

将初始化和写入上下文都移到reduce方法中。

即

int wordCount = 0; // Total number of words
int counter_dist = 0; // Number of distinct words in the corpus
int counter_startZ = 0; // Number of words that start with letter Z
int counter_less4 = 0; // Number of words that appear less than 4 

和

   context.write(new Text("Total words: "), new IntWritable(wordCount));
    context.write(new Text("Distinct words: "), new IntWritable(counter_dist));
    context.write(new Text("Starts with Z: "), new IntWritable(counter_startZ));
    context.write(new Text("Appears less than 4 times:"), new IntWritable(counter_less4));

---

编辑:根据 OP 评论，似乎整个逻辑都有缺陷。

下面是实现预期结果的代码。 请注意，我还没有实现setup() 或cleanup()；因为根本不需要。

使用计数器来计算您要查找的内容。 MapReduce 完成后，只需在驱动程序类中获取计数器即可。

例如字数和以“z”或“Z”开头的字可以在映射器中计算

public class WordCountMapper extends Mapper <Object, Text, Text, IntWritable> {

    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    @Override
    public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
        StringTokenizer itr = new StringTokenizer(value.toString());
        while (itr.hasMoreTokens()) {
            String hasKey = itr.nextToken();
            word.set(hasKey);
            context.getCounter("my_counters", "TOTAL_WORDS").increment(1);
            if(hasKey.toUpperCase().startsWith("Z")){
            context.getCounter("my_counters", "Z_WORDS").increment(1);
            }
            context.write(word, one);
        }
    }
}

reducer 计数器可以统计不同单词的数量 和单词出现次数少于 4 次。

public class WordCountReducer extends Reducer <Text, IntWritable, Text, IntWritable> {

    @Override
    public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int wordCount= 0;
        context.getCounter("my_counters", "DISTINCT_WORDS").increment(1);
        for (IntWritable val : values){
            wordCount += val.get();
        }
        if(wordCount < 4{
           context.getCounter("my_counters", "WORDS_LESS_THAN_4").increment(1);
        }
    }
}

在 Driver 类中获取计数器。以下代码位于您提交作业的行之后

CounterGroup group = job.getCounters().getGroup("my_counters");

for (Counter counter : group) {
   System.out.println(counter.getName() + "=" + counter.getValue());
}