基于Hadoop的超市进货推荐系统设计与实现【springboot案例项目】

由于原始代码较为复杂且涉及到特定的数据处理和算法，我们无法提供一个完整的代码实例。但是，我们可以提供一个简化版本的核心函数，展示如何在Spring Boot应用程序中使用Hadoop进行基本的MapReduce任务。

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
 
@Service
public class HadoopMapReduceService {
 
    @Autowired
    private Configuration configuration;
 
    public void runMapReduceJob(String inputPath, String outputPath) throws Exception {
        Job job = Job.getInstance(configuration, "word count");
        job.setJarByClass(HadoopMapReduceService.class);
 
        job.setMapperClass(MyMapper.class);
        job.setReducerClass(MyReducer.class);
 
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
 
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
 
        FileInputFormat.addInputPath(job, new Path(inputPath));
        FileOutputFormat.setOutputPath(job, new Path(outputPath));
 
        boolean success = job.waitForCompletion(true);
        if (!success) {
            throw new Exception("Job did not successfully complete");
        }
    }
 
    public static class MyMapper 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) {
            String line = value.toString();
            String[] words = line.split("\\s+");
            for (String w : words) {
                word.set(w);
                try {
                    context.write(word, one);
                } catch (Exception e) {
                    e.printStackTrace();
                }
            }
        }
    }
 
    public static class MyReducer