首先按照网上林子雨老师的教程把MapReduce做好
然后再按照建民老师发的实验要求进行实验
实验要求:对如下信息进行统计并写入out
- 买家id 商品id 收藏日期
- 10181 1000481 2010-04-04 16:54:31
- 20001 1001597 2010-04-07 15:07:52
- 20001 1001560 2010-04-07 15:08:27
- 20042 1001368 2010-04-08 08:20:30
- 20067 1002061 2010-04-08 16:45:33
- 20056 1003289 2010-04-12 10:50:55
- 20056 1003290 2010-04-12 11:57:35
- 20056 1003292 2010-04-12 12:05:29
- 20054 1002420 2010-04-14 15:24:12
- 20055 1001679 2010-04-14 19:46:04
- 20054 1010675 2010-04-14 15:23:53
- 20054 1002429 2010-04-14 17:52:45
- 20076 1002427 2010-04-14 19:35:39
- 20054 1003326 2010-04-20 12:54:44
- 20056 1002420 2010-04-15 11:24:49
- 20064 1002422 2010-04-15 11:35:54
- 20056 1003066 2010-04-15 11:43:01
- 20056 1003055 2010-04-15 11:43:06
- 20056 1010183 2010-04-15 11:45:24
- 20056 1002422 2010-04-15 11:45:49
- 20056 1003100 2010-04-15 11:45:54
- 20056 1003094 2010-04-15 11:45:57
- 20056 1003064 2010-04-15 11:46:04
- 20056 1010178 2010-04-15 16:15:20
- 20076 1003101 2010-04-15 16:37:27
- 20076 1003103 2010-04-15 16:37:05
- 20076 1003100 2010-04-15 16:37:18
- 20076 1003066 2010-04-15 16:37:31
- 20054 1003103 2010-04-15 16:40:14
- 20054 1003100 2010-04-15 16:40:16
要求统计结果如下:
- 买家id 商品数量
- 10181 1
- 20001 2
- 20042 1
- 20054 6
- 20055 1
- 20056 12
- 20064 1
- 20067 1
- 20076 5
核心代码则是:
- package mapreduce;
- import java.io.IOException;
- import java.util.StringTokenizer;
- 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;
- public class WordCount {
- public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
- Job job = Job.getInstance();
- job.setJobName("WordCount");
- job.setJarByClass(WordCount.class);
- job.setMapperClass(doMapper.class);
- job.setReducerClass(doReducer.class);
- job.setOutputKeyClass(Text.class);
- job.setOutputValueClass(IntWritable.class);
- Path in = new Path("hdfs://localhost:9000/mymapreduce1/in/buyer_favorite1");
- Path out = new Path("hdfs://localhost:9000/mymapreduce1/out");
- FileInputFormat.addInputPath(job, in);
- FileOutputFormat.setOutputPath(job, out);
- System.exit(job.waitForCompletion(true) ? 0 : 1);
- }
- public static class doMapper extends Mapper<Object, Text, Text, IntWritable>{
- public static final IntWritable one = new IntWritable(1);
- public static Text word = new Text();
- @Override
- protected void map(Object key, Text value, Context context)
- throws IOException, InterruptedException {
- StringTokenizer tokenizer = new StringTokenizer(value.toString(), " ");
- word.set(tokenizer.nextToken());
- context.write(word, one);
- }
- }
- public static class doReducer extends Reducer<Text, IntWritable, Text, IntWritable>{
- private IntWritable result = new IntWritable();
- @Override
- protected void reduce(Text key, Iterable<IntWritable> values, Context context)
- throws IOException, InterruptedException {
- int sum = 0;
- for (IntWritable value : values) {
- sum += value.get();
- }
- result.set(sum);
- context.write(key, result);
- }
- }
- }
当按照这个写下来时,程序运行后写入out的是这个:
而这里面需要对在输出和计算上有一点点的修改,同时需要有空格。
修改之后的代码明天再更emm