编写MapReduce程序的基本步骤如下:
- 创建一个实现了Mapper接口的类,重写map方法。map方法接收一个键值对作为输入,将输入数据处理并输出为中间键值对。
public class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
- 创建一个实现了Reducer接口的类,重写reduce方法。reduce方法接收中间键值对作为输入,将输入数据根据键汇总并输出为最终结果键值对。
public class MyReducer 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);
}
}
- 创建一个配置对象,设置MapReduce作业的相关参数。
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
- 指定输入数据的路径和输出结果的路径。
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
- 设置Mapper和Reducer的类。
job.setMapperClass(MyMapper.class);
job.setCombinerClass(MyReducer.class);
job.setReducerClass(MyReducer.class);
- 设置最终结果的键值对类型。
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
- 提交MapReduce作业。
System.exit(job.waitForCompletion(true) ? 0 : 1);
以上就是编写MapReduce程序的基本步骤。根据具体需求,可以对Mapper和Reducer的逻辑进行扩展和修改。
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