編寫MapReduce程序的基本步驟如下：

1. 創建一個實現了Mapper接口的類，重寫map方法。map方法接收一個鍵值對作為輸入，將輸入數據處理并輸出為中間鍵值對。

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);
        }
    }
}

2. 創建一個實現了Reducer接口的類，重寫reduce方法。reduce方法接收中間鍵值對作為輸入，將輸入數據根據鍵匯總并輸出為最終結果鍵值對。

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);
    }
}

3. 創建一個配置對象，設置MapReduce作業的相關參數。

Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);

4. 指定輸入數據的路徑和輸出結果的路徑。

FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));

5. 設置Mapper和Reducer的類。

job.setMapperClass(MyMapper.class);
job.setCombinerClass(MyReducer.class);
job.setReducerClass(MyReducer.class);

6. 設置最終結果的鍵值對類型。

job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);

7. 提交MapReduce作業。

System.exit(job.waitForCompletion(true) ? 0 : 1);

以上就是編寫MapReduce程序的基本步驟。根據具體需求，可以對Mapper和Reducer的邏輯進行擴展和修改。