我遇到了一个MapReduce WordCount示例应用程序,我想编辑代码,以便它还输出在地图阶段调用Map方法的次数。我有两个文本文件,这是我用于应用程序的代码
public class WordCount
{
public static class TokenizerMapper
extends Mapper<Object, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(Object key, Text value, Context context
) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
context.write(word, one);
}
}
}
public static class IntSumReducer
extends Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable<IntWritable> values,
Context context
) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
Job job = new Job(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
这仅用于学习目的,所以我非常感谢您的帮助!
谢谢
答案 0 :(得分:2)
Hadoop已经计算了地图方法调用的数量。您可以在计数器部分的应用程序UI中查看它,也可以在完成后从作业中获取:
int code = job.waitForCompletion(true) ? 0 : 1;
String group = "Map-Reduce Framework";
String counter = "Map input records";
long val = job.getCounters().getGroup(group).findCounter(counter).getValue();
请记住,如果启用推测执行,此数字可能大于输入文件行数。