一、原理分析
Mapreduce的处理过程,由于Mapreduce会在Map~reduce中,将重复的Key合并在一起,所以Mapreduce很容易就去除重复的行。Map无须做任何处理,设置Map中写入context的东西为不作任何处理的行,也就是Map中最初处理的value即可,而Reduce同样无须做任何处理,写入输出文件的东西就是,最初得到的Key。
我原来以为是map阶段用了hashmap,根据hash值的唯一性。估计应该不是...
Map是输入文件有几行,就运行几次。
二、代码
2.1 Mapper
package algorithm; import java.io.IOException; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; public class DuplicateRemoveMapper extends Mapper<LongWritable, Text, Text, Text> { //输入文件是数字 不过可能也有字符等 所以用Text,不用LongWritable public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { context.write(value, new Text());//后面不能是null,否则,空指针 } }
2.2 Reducer
package algorithm; import java.io.IOException; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; public class DuplicateRemoveReducer extends Reducer<Text, Text, Text, Text> { public void reduce(Text key, Iterable<Text> value, Context context) throws IOException, InterruptedException { // process values context.write(key, null); //可以出处null } }
2.3 Main
package algorithm; 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.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class DuplicateMainMR { public static void main(String[] args) throws Exception{ // TODO Auto-generated method stub Configuration conf = new Configuration(); Job job = new Job(conf,"DuplicateRemove"); job.setJarByClass(DuplicateMainMR.class); job.setMapperClass(DuplicateRemoveMapper.class); job.setReducerClass(DuplicateRemoveReducer.class); job.setOutputKeyClass(Text.class); //输出是null,不过不能随意写 否则包类型不匹配 job.setOutputValueClass(Text.class); job.setNumReduceTasks(1); //hdfs上写错了文件名 DupblicateRemove 多了个b //hdfs不支持修改操作 FileInputFormat.addInputPath(job, new Path("hdfs://192.168.58.180:8020/ClassicalTest/DupblicateRemove/DuplicateRemove.txt")); FileOutputFormat.setOutputPath(job, new Path("hdfs://192.168.58.180:8020/ClassicalTest/DuplicateRemove/DuplicateRemoveOut")); System.exit(job.waitForCompletion(true) ? 0 : 1); } }
三、输出分析
3.1 输入与输出
没啥要对比的....不贴了
3.2 控制台
doop.mapreduce.Job.updateStatus(Job.java:323) INFO - Job job_local4032991_0001 completed successfully DEBUG - PrivilegedAction as:hxsyl (auth:SIMPLE) from:org.apache.hadoop.mapreduce.Job.getCounters(Job.java:765) INFO - Counters: 38 File System Counters FILE: Number of bytes read=560 FILE: Number of bytes written=501592 FILE: Number of read operations=0 FILE: Number of large read operations=0 FILE: Number of write operations=0 HDFS: Number of bytes read=48 HDFS: Number of bytes written=14 HDFS: Number of read operations=13 HDFS: Number of large read operations=0 HDFS: Number of write operations=4 Map-Reduce Framework Map input records=8 Map output records=8 Map output bytes=26 Map output materialized bytes=48 Input split bytes=142 Combine input records=0 Combine output records=0 Reduce input groups=6 Reduce shuffle bytes=48 Reduce input records=8 Reduce output records=6 Spilled Records=16 Shuffled Maps =1 Failed Shuffles=0 Merged Map outputs=1 GC time elapsed (ms)=4 CPU time spent (ms)=0 Physical memory (bytes) snapshot=0 Virtual memory (bytes) snapshot=0 Total committed heap usage (bytes)=457179136 Shuffle Errors BAD_ID=0 CONNECTION=0 IO_ERROR=0 WRONG_LENGTH=0 WRONG_MAP=0 WRONG_REDUCE=0 File Input Format Counters Bytes Read=24 File Output Format Counters Bytes Written=14 DEBUG - PrivilegedAction as:hxsyl (auth:SIMPLE) from:org.apache.hadoop.mapreduce.Job.updateStatus(Job.java:323) DEBUG - stopping client from cache: [email protected] DEBUG - removing client from cache: [email protected] DEBUG - stopping actual client because no more references remain: [email protected] DEBUG - Stopping client DEBUG - IPC Client (521081105) connection to /192.168.58.180:8020 from hxsyl: closed DEBUG - IPC Client (521081105) connection to /192.168.58.180:8020 from hxsyl: stopped, remaining connections 0
时间: 2024-10-07 06:27:11