地图缩小 - 按天/小时/分钟分割和写入HDFS

Question

我输入文件如下

输入文件

**Regid   Epoch Timestamp**  
f77xvP  1509073785106 
2YXsF7r 1509073795109
GUf98M1 1509073805109 
JNFXto1 1509073815110 

这就是我要做的事情，从HDFS读取上面的输入文件，并通过按日期/时间/小时/分钟进行分区，用单独的文件写入HDFS。

我对此进行了研究可以使用Hive完成，但是可以使用分区/ Reducer。可以帮助我以实现这个目的的方式帮助我

package com.main;

    import java.io.IOException;
    import java.text.DateFormat;
    import java.text.SimpleDateFormat;
    import java.util.Date;
    import java.util.Properties;

    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.LongWritable;
    import org.apache.hadoop.io.NullWritable;
    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.input.TextInputFormat;
    import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
    import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
    import org.json.JSONObject;



    public class JsonMain {

        public static Properties props;

        public static class Mapperclass extends Mapper<LongWritable, Text, Text, Text>{
            DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
            public void map(LongWritable mkey, Text mvalue, Context context) throws IOException, InterruptedException{
                try{
                    JSONObject obj = new JSONObject(mvalue.toString());
                    String regId = (String)obj.get("regId");
                    String time = (String)obj.get("time");
                    Date date = new Date(Long.parseLong(time));         
    //              long epoch = System.currentTimeMillis();
    //              System.out.println(epoch);
    //              Date date = new Date(epoch);
                    String datestring = dateFormat.format(date); 
                    context.write(new Text(regId), new Text(time + " " + datestring ));
                }
                catch (Exception e) {
                    e.printStackTrace();
                }

            }
        }



        public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
            // TODO Auto-generated method stub

            //  props = new Properties();
            //FileInputStream propFile = new FileInputStream(args[0].trim());
            //props.load(propFile);

            Configuration conf = new Configuration();
            Job job = Job.getInstance(conf, "Map Reduce");

            job.setJarByClass(JsonMain.class);
            job.setMapperClass(Mapperclass.class);      
            job.setNumReduceTasks(0);

            job.setMapOutputKeyClass(Text.class);
            job.setMapOutputValueClass(Text.class);

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


            job.setInputFormatClass(TextInputFormat.class);
            job.setOutputFormatClass(TextOutputFormat.class);



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

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

    }

上面的代码用HDFS写如下。

Ef77xvP 1509073785106 2017-10-26 20:09:45
2YXsF7r 1509073795109 2017-10-26 20:09:55
GUf98M1 1509073805109 2017-10-26 20:10:05
JNFXto1 1509073815110 2017-10-26 20:10:15
bkFbEK3 1509073825110 2017-10-26 20:10:25
LDze9od 1509073835110 2017-10-26 20:10:35
y0Zs8gF 1509073845111 2017-10-26 20:10:45