MapReduce编程系列 — 3：数据去重
1、项目名称：
2、程序代码：
package com.dedup; import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.apache.hadoop.util.GenericOptionsParser; public class Dedup {
//map将输入中的value复制到输出数据的key上，并直接输出，注意参数类型和个数
public static class Map extends Mapper<Object, Text, Text, Text>{
public static Text line = new Text();
//注意参数类型和个数
public void map(Object key , Text value , Context context) throws IOException,InterruptedException{
System.out.println("mapper.......");
System.out.println("key:"+key+" value:"+value);
line = value;
context.write(line, new Text(" "));
System.out.println("line:"+ line +" value"+ value +" context:" + context);
}
}
//reduce将输入中的key复制到输出数据的key上，并直接输出，注意参数类型和个数
public static class Reduce extends Reducer<Text, Text, Text, Text>{
//注意参数类型和个数
public void reduce(Text key , Iterable<Text> values, Context context)throws IOException,InterruptedException{
System.out.println("reducer.......");
System.out.println("key:"+key+" values:"+values);
context.write(key, new Text(" "));
System.out.println("key:"+key+" values"+values+" context:"+context);
}
} public static void main(String [] args)throws Exception{
Configuration conf = new Configuration();
String otherArgs[] = new GenericOptionsParser(conf,args).getRemainingArgs();
if(otherArgs.length!=2){
System.out.println("Usage:dedup <in> <out>");
System.exit(2);
}
Job job = new Job(conf,"Data Deduplication");
job.setJarByClass(Dedup.class); job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class); job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class); FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true)? 0 : 1 );
}
}
3、测试数据：
file1：
2006-6-9 a
2006-6-10 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-15 c
2006-6-11 c
2006-6-10 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-15 c
2006-6-11 c
file2：
2006-6-9 b
2006-6-10 a
2006-6-11 b
2006-6-12 d
2006-6-13 a
2006-6-14 c
2006-6-15 d
2006-6-11 c
2006-6-10 a
2006-6-11 b
2006-6-12 d
2006-6-13 a
2006-6-14 c
2006-6-15 d
2006-6-11 c
4、运行过程：
14/09/21 16:51:16 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/09/21 16:51:16 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
14/09/21 16:51:16 INFO input.FileInputFormat: Total input paths to process : 2
14/09/21 16:51:16 WARN snappy.LoadSnappy: Snappy native library not loaded
14/09/21 16:51:16 INFO mapred.JobClient: Running job: job_local_0001
14/09/21 16:51:16 INFO util.ProcessTree: setsid exited with exit code 0
14/09/21 16:51:16 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@2e9aa770
14/09/21 16:51:16 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:16 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:16 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 a
line:2006-6-9 a value2006-6-9 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:11 value:2006-6-10 b
line:2006-6-10 b value2006-6-10 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:23 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:59 value:2006-6-14 b
line:2006-6-14 b value2006-6-14 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:71 value:2006-6-15 c
line:2006-6-15 c value2006-6-15 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
14/09/21 16:51:16 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:16 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:16 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
14/09/21 16:51:17 INFO mapred.JobClient: map 0% reduce 0%
14/09/21 16:51:19 INFO mapred.LocalJobRunner:
14/09/21 16:51:19 INFO mapred.Task: Task 'attempt_local_0001_m_000000_0' done.
14/09/21 16:51:19 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3697e580
14/09/21 16:51:19 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:19 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:19 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 b
line:2006-6-9 b value2006-6-9 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:11 value:2006-6-10 a
line:2006-6-10 a value2006-6-10 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:23 value:2006-6-11 b
line:2006-6-11 b value2006-6-11 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:59 value:2006-6-14 c
line:2006-6-14 c value2006-6-14 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:71 value:2006-6-15 d
line:2006-6-15 d value2006-6-15 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
14/09/21 16:51:19 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:19 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:19 INFO mapred.Task: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
14/09/21 16:51:20 INFO mapred.JobClient: map 100% reduce 0%
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task 'attempt_local_0001_m_000001_0' done.
14/09/21 16:51:22 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3c844c07
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Merger: Merging 2 sorted segments
14/09/21 16:51:22 INFO mapred.Merger: Down to the last merge-pass, with 2 segments left of total size: 258 bytes
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
reducer.......
key:2006-6-10 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-10 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-12 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-12 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-13 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-13 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
14/09/21 16:51:22 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
14/09/21 16:51:22 INFO output.FileOutputCommitter: Saved output of task 'attempt_local_0001_r_000000_0' to hdfs://localhost:9000/user/hadoop/dedup_output
14/09/21 16:51:25 INFO mapred.LocalJobRunner: reduce > reduce
14/09/21 16:51:25 INFO mapred.Task: Task 'attempt_local_0001_r_000000_0' done.
14/09/21 16:51:26 INFO mapred.JobClient: map 100% reduce 100%
14/09/21 16:51:26 INFO mapred.JobClient: Job complete: job_local_0001
14/09/21 16:51:26 INFO mapred.JobClient: Counters: 22
14/09/21 16:51:26 INFO mapred.JobClient: Map-Reduce Framework
14/09/21 16:51:26 INFO mapred.JobClient: Spilled Records=32
14/09/21 16:51:26 INFO mapred.JobClient: Map output materialized bytes=266
14/09/21 16:51:26 INFO mapred.JobClient: Reduce input records=16
14/09/21 16:51:26 INFO mapred.JobClient: Virtual memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient: Map input records=16
14/09/21 16:51:26 INFO mapred.JobClient: SPLIT_RAW_BYTES=232
14/09/21 16:51:26 INFO mapred.JobClient: Map output bytes=222
14/09/21 16:51:26 INFO mapred.JobClient: Reduce shuffle bytes=0
14/09/21 16:51:26 INFO mapred.JobClient: Physical memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient: Reduce input groups=12
14/09/21 16:51:26 INFO mapred.JobClient: Combine output records=0
14/09/21 16:51:26 INFO mapred.JobClient: Reduce output records=12
14/09/21 16:51:26 INFO mapred.JobClient: Map output records=16
14/09/21 16:51:26 INFO mapred.JobClient: Combine input records=0
14/09/21 16:51:26 INFO mapred.JobClient: CPU time spent (ms)=0
14/09/21 16:51:26 INFO mapred.JobClient: Total committed heap usage (bytes)=813170688
14/09/21 16:51:26 INFO mapred.JobClient: File Input Format Counters
14/09/21 16:51:26 INFO mapred.JobClient: Bytes Read=190
14/09/21 16:51:26 INFO mapred.JobClient: FileSystemCounters
14/09/21 16:51:26 INFO mapred.JobClient: HDFS_BYTES_READ=475
14/09/21 16:51:26 INFO mapred.JobClient: FILE_BYTES_WRITTEN=122061
14/09/21 16:51:26 INFO mapred.JobClient: FILE_BYTES_READ=1665
14/09/21 16:51:26 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=166
14/09/21 16:51:26 INFO mapred.JobClient: File Output Format Counters
14/09/21 16:51:26 INFO mapred.JobClient: Bytes Written=166
14/09/21 16:51:16 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
14/09/21 16:51:16 INFO input.FileInputFormat: Total input paths to process : 2
14/09/21 16:51:16 WARN snappy.LoadSnappy: Snappy native library not loaded
14/09/21 16:51:16 INFO mapred.JobClient: Running job: job_local_0001
14/09/21 16:51:16 INFO util.ProcessTree: setsid exited with exit code 0
14/09/21 16:51:16 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@2e9aa770
14/09/21 16:51:16 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:16 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:16 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 a
line:2006-6-9 a value2006-6-9 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:11 value:2006-6-10 b
line:2006-6-10 b value2006-6-10 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:23 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:59 value:2006-6-14 b
line:2006-6-14 b value2006-6-14 b context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:71 value:2006-6-15 c
line:2006-6-15 c value2006-6-15 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@2d3b0087
14/09/21 16:51:16 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:16 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:16 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
14/09/21 16:51:17 INFO mapred.JobClient: map 0% reduce 0%
14/09/21 16:51:19 INFO mapred.LocalJobRunner:
14/09/21 16:51:19 INFO mapred.Task: Task 'attempt_local_0001_m_000000_0' done.
14/09/21 16:51:19 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3697e580
14/09/21 16:51:19 INFO mapred.MapTask: io.sort.mb = 100
14/09/21 16:51:19 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/21 16:51:19 INFO mapred.MapTask: record buffer = 262144/327680
mapper.......
key:0 value:2006-6-9 b
line:2006-6-9 b value2006-6-9 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:11 value:2006-6-10 a
line:2006-6-10 a value2006-6-10 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:23 value:2006-6-11 b
line:2006-6-11 b value2006-6-11 b context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:35 value:2006-6-12 d
line:2006-6-12 d value2006-6-12 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:47 value:2006-6-13 a
line:2006-6-13 a value2006-6-13 a context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:59 value:2006-6-14 c
line:2006-6-14 c value2006-6-14 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:71 value:2006-6-15 d
line:2006-6-15 d value2006-6-15 d context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
mapper.......
key:83 value:2006-6-11 c
line:2006-6-11 c value2006-6-11 c context:org.apache.hadoop.mapreduce.Mapper$Context@319af5dd
14/09/21 16:51:19 INFO mapred.MapTask: Starting flush of map output
14/09/21 16:51:19 INFO mapred.MapTask: Finished spill 0
14/09/21 16:51:19 INFO mapred.Task: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
14/09/21 16:51:20 INFO mapred.JobClient: map 100% reduce 0%
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task 'attempt_local_0001_m_000001_0' done.
14/09/21 16:51:22 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3c844c07
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Merger: Merging 2 sorted segments
14/09/21 16:51:22 INFO mapred.Merger: Down to the last merge-pass, with 2 segments left of total size: 258 bytes
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
reducer.......
key:2006-6-10 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-10 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-10 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-11 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-11 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-12 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-12 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-13 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-13 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-14 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-14 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 c values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 c valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-15 d values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-15 d valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 a values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 a valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
reducer.......
key:2006-6-9 b values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78
key:2006-6-9 b valuesorg.apache.hadoop.mapreduce.ReduceContext$ValueIterable@9c8fd78 context:org.apache.hadoop.mapreduce.Reducer$Context@52767ce8
14/09/21 16:51:22 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
14/09/21 16:51:22 INFO mapred.LocalJobRunner:
14/09/21 16:51:22 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
14/09/21 16:51:22 INFO output.FileOutputCommitter: Saved output of task 'attempt_local_0001_r_000000_0' to hdfs://localhost:9000/user/hadoop/dedup_output
14/09/21 16:51:25 INFO mapred.LocalJobRunner: reduce > reduce
14/09/21 16:51:25 INFO mapred.Task: Task 'attempt_local_0001_r_000000_0' done.
14/09/21 16:51:26 INFO mapred.JobClient: map 100% reduce 100%
14/09/21 16:51:26 INFO mapred.JobClient: Job complete: job_local_0001
14/09/21 16:51:26 INFO mapred.JobClient: Counters: 22
14/09/21 16:51:26 INFO mapred.JobClient: Map-Reduce Framework
14/09/21 16:51:26 INFO mapred.JobClient: Spilled Records=32
14/09/21 16:51:26 INFO mapred.JobClient: Map output materialized bytes=266
14/09/21 16:51:26 INFO mapred.JobClient: Reduce input records=16
14/09/21 16:51:26 INFO mapred.JobClient: Virtual memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient: Map input records=16
14/09/21 16:51:26 INFO mapred.JobClient: SPLIT_RAW_BYTES=232
14/09/21 16:51:26 INFO mapred.JobClient: Map output bytes=222
14/09/21 16:51:26 INFO mapred.JobClient: Reduce shuffle bytes=0
14/09/21 16:51:26 INFO mapred.JobClient: Physical memory (bytes) snapshot=0
14/09/21 16:51:26 INFO mapred.JobClient: Reduce input groups=12
14/09/21 16:51:26 INFO mapred.JobClient: Combine output records=0
14/09/21 16:51:26 INFO mapred.JobClient: Reduce output records=12
14/09/21 16:51:26 INFO mapred.JobClient: Map output records=16
14/09/21 16:51:26 INFO mapred.JobClient: Combine input records=0
14/09/21 16:51:26 INFO mapred.JobClient: CPU time spent (ms)=0
14/09/21 16:51:26 INFO mapred.JobClient: Total committed heap usage (bytes)=813170688
14/09/21 16:51:26 INFO mapred.JobClient: File Input Format Counters
14/09/21 16:51:26 INFO mapred.JobClient: Bytes Read=190
14/09/21 16:51:26 INFO mapred.JobClient: FileSystemCounters
14/09/21 16:51:26 INFO mapred.JobClient: HDFS_BYTES_READ=475
14/09/21 16:51:26 INFO mapred.JobClient: FILE_BYTES_WRITTEN=122061
14/09/21 16:51:26 INFO mapred.JobClient: FILE_BYTES_READ=1665
14/09/21 16:51:26 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=166
14/09/21 16:51:26 INFO mapred.JobClient: File Output Format Counters
14/09/21 16:51:26 INFO mapred.JobClient: Bytes Written=166
5、运行结果：
2006-6-10 a
2006-6-10 b
2006-6-11 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-14 c
2006-6-15 c
2006-6-15 d
2006-6-9 a
2006-6-9 b
2006-6-10 b
2006-6-11 b
2006-6-11 c
2006-6-12 d
2006-6-13 a
2006-6-14 b
2006-6-14 c
2006-6-15 c
2006-6-15 d
2006-6-9 a
2006-6-9 b
MapReduce编程系列 — 3：数据去重的更多相关文章
- [Python] 文科生零基础学编程系列三——数据运算符的基本类别
上一篇:[Python] 文科生零基础学编程系列二--数据类型.变量.常量的基础概念 下一篇: ※ 程序的执行过程,就是对数据进行运算的过程. 不同的数据类型,可以进行不同的运算, 按照数据运算类型的 ...
- 学习ASP.NET Core Blazor编程系列八——数据校验
学习ASP.NET Core Blazor编程系列一--综述 学习ASP.NET Core Blazor编程系列二--第一个Blazor应用程序(上) 学习ASP.NET Core Blazor编程系 ...
- 【原创】MapReduce编程系列之二元排序
普通排序实现 普通排序的实现利用了按姓名的排序,调用了默认的对key的HashPartition函数来实现数据的分组.partition操作之后写入磁盘时会对数据进行排序操作(对一个分区内的数据作排序 ...
- MapReduce编程系列 — 5：单表关联
1.项目名称: 2.项目数据: chile parentTom LucyTom JackJone LucyJone JackLucy MaryLucy Ben ...
- MapReduce编程系列 — 2：计算平均分
1.项目名称: 2.程序代码: package com.averagescorecount; import java.io.IOException; import java.util.Iterator ...
- 【原创】MapReduce编程系列之表连接
问题描述 需要连接的表如下:其中左边是child,右边是parent,我们要做的是找出grandchild和grandparent的对应关系,为此需要进行表的连接. Tom Lucy Tom Jim ...
- MapReduce编程系列 — 6：多表关联
1.项目名称: 2.程序代码: 版本一(详细版): package com.mtjoin; import java.io.IOException; import java.util.Iterator; ...
- MapReduce编程系列 — 4：排序
1.项目名称: 2.程序代码: package com.sort; import java.io.IOException; import org.apache.hadoop.conf.Configur ...
- MapReduce编程系列 — 1：计算单词
1.代码: package com.mrdemo; import java.io.IOException; import java.util.StringTokenizer; import org.a ...
随机推荐
- TweenMax动画库学习(五)
目录 TweenMax动画库学习(一) TweenMax动画库学习(二) TweenMax动画库学习(三) Tw ...
- NSS_02 日志配置
采用log4net,使用系统推荐的最新版本:log4net-1.2.11-bin-newkey.zip(网址:http://logging.apache.org/log4net/download_lo ...
- jQuery(function($){...})与(function($){...})(jQuery)知识点分享
写jQuery插件时一些经验分享一下. 一.推荐写法 jQuery(function($){ //coding }); 全写为 jQuery(document).ready(function($){ ...
- ubuntu安装QQ目前最完善的方法！（亲测，成功）
wine qq 2012 for linux Ubuntu 64位兼容(12月21日末日版) 由 smile » 2011-04-07 9:08 +-------------------------- ...
- 解决Execwb 导致 ado崩溃的问题。
http://qc.embarcadero.com/wc/qcmain.aspx?d=61255
- Python时间和日期学习
#coding=utf-8 __author__ = 'Administrator' #日期和时间模块学习 """ Python程序能用很多方式处理日期和时间,转换日期格 ...
- ARCGIS 10中添加excel点字段生产点shp文件的工具
菜单栏中——文件——添加数据——添加XY数据——选择excel。 选择x,y和投影（注意这里投影应该是原数据的本身投影，不能直接选择你要转换的投影）完成。
- Mysql数据库备份和还原常用的命令
Mysql数据库备份和还原常用的命令是进行Mysql数据库备份和还原的关键,没有命令,什么都无从做起,更谈不上什么备份还原,只有给系统这个命令,让它去执行,才能完成Mysql数据库备份和还原的操作,下 ...
- 【MongoDB】 安装为windows services
参考 http://stackoverflow.com/questions/2404742/how-to-install-mongodb-on-windows # mongodb.conf # da ...
- 防止IFRAME页被嵌套
防止IFRAME页被嵌套 //最大化窗口,防止窗口嵌套 if (parent.location != window.location){ parent.location = window.locati ...