【Hadoop】7.MapReduce框架原理-Shuffle机制-7.1Patition分区
什么是Shuffle
在Map方法之后，Reduce方法之前的数据处理过程称之为Shuffle
1. Partition分区
默认分区
官方默认的分区是哈希分区
@Public
@Stable
public class HashPartitioner<K2, V2> implements Partitioner<K2, V2> {
public HashPartitioner() {
}
public void configure(JobConf job) {
}
public int getPartition(K2 key, V2 value, int numReduceTasks) {
// key的hashcode值与Integer的最大值 在和reduceTask数量求余
return (key.hashCode() & Integer.MAX_VALUE) % numReduceTasks;
}
}
默认分区是根据key的hashCode值对ReduceTeasks的个数取模得到的。用户没法控制哪个key存储到哪个分区的
自定义分区
如果我们想要按照我们的要求输出文件，就需要我们的自定义Partitioner才可以。
步骤：
- 自定义类继承Partitioner，重写getPartition（）方法
- 在Job驱动中，设置自定义Partitioner
- 自定义Partition后，需要根据自定义Partitioner的逻辑设置相应的数量的Reducetask
示例
对以下数据分别根据a，b，c，d开头的分别放到一个文件，剩下的放到另一个文件。
呢么我们开始吧。
PatitionDriver 类
package com.xing.MapReduce.PatitionDemo;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
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;
import java.io.IOException;
public class PatitionDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
System.setProperty("hadoop.home.dir", "E:\\hadoop-2.7.1");
Configuration configuration = new Configuration();
FileSystem fs = FileSystem.get(configuration);
Job job = Job.getInstance(configuration);
job.setJobName("Patitioner");
job.setJarByClass(PatitionDriver.class);
job.setMapperClass(PatitionMapper.class);
job.setReducerClass(PatitionReduce.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
// 设置了自定义Partitioner 就必须设置好相应的ReduceTask
job.setPartitionerClass(PatitionCustom.class);
job.setNumReduceTasks(5);
Path inPath = new Path("E:\\hdfs\\data\\patition\\input\\demo.txt");
Path outPath = new Path("E:\\hdfs\\data\\patition\\output");
if (fs.exists(outPath)){
fs.delete(outPath,true );
}
FileInputFormat.setInputPaths(job,inPath);
FileOutputFormat.setOutputPath(job,outPath);
boolean b = job.waitForCompletion(true);
System.exit(b?0:-1);
}
}
PatitionMapper
最简单的分割加输出
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class PatitionMapper extends Mapper<LongWritable,Text,Text,Text> {
private Text k = new Text();
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String[] split = value.toString().split("\t");
k.set(split[0]);
context.write(k,value);
}
}
**PatitionReduce **
只有输出
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class PatitionReduce extends Reducer<Text,Text,Text,Text> {
@Override
protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
// 就只是简单的输出数据
for (Text value : values) {
context.write(key,value);
}
}
}
PatitionCustom
最重要的自定义Patitioner，自定义的Patitioner返回值一定是从0开始，逐一增加，不能说我返回的值为1,4,6,7这种。
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;
// Partitioner 这里是Map的输出
public class PatitionCustom extends Partitioner<Text,Text> {
/**
* 重写getPartition方法
* @param key
* @param value
* @param numPartitions
* @return
*/
public int getPartition(Text key, Text value, int numPartitions) {
System.out.println("###########我是自定义分区的key："+key+",value:"+value+",分区数目:"+numPartitions);
String keyString = key.toString();
if (keyString.startsWith("a")){
return 0;
}else if(keyString.startsWith("b")){
return 1;
}else if(keyString.startsWith("c")){
return 2;
}else if(keyString.startsWith("d")){
return 3;
}else {
return 4;
}
}
}
输出结果
"D:\Program Files\Java\jdk1.8.0_162\bin\java.exe" "-javaagent:D:\Program Files\JetBrains\IntelliJIDEA\lib\idea_rt.jar=50517:D:\Program Files\JetBrains\IntelliJIDEA\bin" -Dfile.encoding=UTF-8 -classpath "D:\Program Files\Java\jdk1.8.0_162\jre\lib\charsets.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\deploy.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\access-bridge-64.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\cldrdata.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\dnsns.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\jaccess.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\jfxrt.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\localedata.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\nashorn.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\sunec.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\sunjce_provider.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\sunmscapi.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\sunpkcs11.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\ext\zipfs.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\javaws.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\jce.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\jfr.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\jfxswt.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\jsse.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\management-agent.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\plugin.jar;D:\Program Files\Java\jdk1.8.0_162\jre\lib\resources.jar;D:\Program 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ministrator\.m2\repository\org\apache\hadoop\hadoop-yarn-client\2.7.1\hadoop-yarn-client-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-yarn-server-common\2.7.1\hadoop-yarn-server-common-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-shuffle\2.7.1\hadoop-mapreduce-client-shuffle-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-yarn-api\2.7.1\hadoop-yarn-api-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-core\2.7.1\hadoop-mapreduce-client-core-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-yarn-common\2.7.1\hadoop-yarn-common-2.7.1.jar;C:\Users\Administrator\.m2\repository\javax\xml\bind\jaxb-api\2.2.2\jaxb-api-2.2.2.jar;C:\Users\Administrator\.m2\repository\javax\xml\stream\stax-api\1.0-2\stax-api-1.0-2.jar;C:\Users\Administrator\.m2\repository\javax\activation\activation\1.1\activation-1.1.jar;C:\Users\Administrator\.m2\repository\javax\servlet\servlet-api\2.5\servlet-api-2.5.jar;C:\Users\Administrator\.m2\repository\com\sun\jersey\jersey-core\1.9\jersey-core-1.9.jar;C:\Users\Administrator\.m2\repository\com\sun\jersey\jersey-client\1.9\jersey-client-1.9.jar;C:\Users\Administrator\.m2\repository\org\codehaus\jackson\jackson-jaxrs\1.9.13\jackson-jaxrs-1.9.13.jar;C:\Users\Administrator\.m2\repository\org\codehaus\jackson\jackson-xc\1.9.13\jackson-xc-1.9.13.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-mapreduce-client-jobclient\2.7.1\hadoop-mapreduce-client-jobclient-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\apache\hadoop\hadoop-annotations\2.7.1\hadoop-annotations-2.7.1.jar;C:\Users\Administrator\.m2\repository\org\slf4j\slf4j-api\1.7.7\slf4j-api-1.7.7.jar;C:\Users\Administrator\.m2\repository\log4j\log4j\1.2.17\log4j-1.2.17.jar" com.xing.MapReduce.PatitionDemo.PatitionDriver
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
[INFO ] 2019-05-09 15:57:38,223 session.id is deprecated. Instead, use dfs.metrics.session-id
[INFO ] 2019-05-09 15:57:38,239 Initializing JVM Metrics with processName=JobTracker, sessionId=
[WARN ] 2019-05-09 15:57:39,003 Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
[WARN ] 2019-05-09 15:57:39,054 No job jar file set. User classes may not be found. See Job or Job#setJar(String).
[INFO ] 2019-05-09 15:57:39,067 Total input paths to process : 1
[INFO ] 2019-05-09 15:57:39,142 number of splits:1
[INFO ] 2019-05-09 15:57:39,258 Submitting tokens for job: job_local1859959178_0001
[INFO ] 2019-05-09 15:57:39,534 The url to track the job: http://localhost:8080/
[INFO ] 2019-05-09 15:57:39,534 Running job: job_local1859959178_0001
[INFO ] 2019-05-09 15:57:39,534 OutputCommitter set in config null
[INFO ] 2019-05-09 15:57:39,550 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:39,550 OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
[INFO ] 2019-05-09 15:57:39,628 Waiting for map tasks
[INFO ] 2019-05-09 15:57:39,628 Starting task: attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:39,659 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:39,674 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:39,737 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@1f41aa45
[INFO ] 2019-05-09 15:57:39,737 Processing split: file:/E:/hdfs/data/patition/input/demo.txt:0+228
[INFO ] 2019-05-09 15:57:39,799 (EQUATOR) 0 kvi 26214396(104857584)
[INFO ] 2019-05-09 15:57:39,799 mapreduce.task.io.sort.mb: 100
[INFO ] 2019-05-09 15:57:39,799 soft limit at 83886080
[INFO ] 2019-05-09 15:57:39,799 bufstart = 0; bufvoid = 104857600
[INFO ] 2019-05-09 15:57:39,799 kvstart = 26214396; length = 6553600
[INFO ] 2019-05-09 15:57:39,799 Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
###########我是自定义分区的key：apple,value:apple 没错我是苹果,分区数目:5
###########我是自定义分区的key：base,value:base 哈？你是谁？,分区数目:5
###########我是自定义分区的key：case,value:case 我也不知道,分区数目:5
###########我是自定义分区的key：airplane,value:airplane 我是飞机,分区数目:5
###########我是自定义分区的key：back,value:back 快后退,分区数目:5
###########我是自定义分区的key：duck,value:duck 啊啊啊,分区数目:5
###########我是自定义分区的key：disk,value:disk 拉拉阿拉,分区数目:5
###########我是自定义分区的key：fish,value:fish 我要吃鱼,分区数目:5
###########我是自定义分区的key：girlfriend,value:girlfriend 没错我缺个女朋友,分区数目:5
###########我是自定义分区的key：badboy,value:badboy 你是个坏男孩,分区数目:5
[INFO ] 2019-05-09 15:57:39,815
[INFO ] 2019-05-09 15:57:39,815 Starting flush of map output
[INFO ] 2019-05-09 15:57:39,815 Spilling map output
[INFO ] 2019-05-09 15:57:39,815 bufstart = 0; bufend = 283; bufvoid = 104857600
[INFO ] 2019-05-09 15:57:39,815 kvstart = 26214396(104857584); kvend = 26214360(104857440); length = 37/6553600
[INFO ] 2019-05-09 15:57:39,846 Finished spill 0
[INFO ] 2019-05-09 15:57:39,862 Task:attempt_local1859959178_0001_m_000000_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:39,877 map
[INFO ] 2019-05-09 15:57:39,877 Task 'attempt_local1859959178_0001_m_000000_0' done.
[INFO ] 2019-05-09 15:57:39,877 Finishing task: attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:39,877 map task executor complete.
[INFO ] 2019-05-09 15:57:39,877 Waiting for reduce tasks
[INFO ] 2019-05-09 15:57:39,877 Starting task: attempt_local1859959178_0001_r_000000_0
[INFO ] 2019-05-09 15:57:39,908 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:39,924 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:40,018 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@628cb174
[INFO ] 2019-05-09 15:57:40,033 Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@2308a302
[INFO ] 2019-05-09 15:57:40,049 MergerManager: memoryLimit=657666880, maxSingleShuffleLimit=164416720, mergeThreshold=434060160, ioSortFactor=10, memToMemMergeOutputsThreshold=10
[INFO ] 2019-05-09 15:57:40,111 attempt_local1859959178_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
[INFO ] 2019-05-09 15:57:40,158 localfetcher#1 about to shuffle output of map attempt_local1859959178_0001_m_000000_0 decomp: 68 len: 72 to MEMORY
[INFO ] 2019-05-09 15:57:40,174 Read 68 bytes from map-output for attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:40,189 closeInMemoryFile -> map-output of size: 68, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->68
[INFO ] 2019-05-09 15:57:40,189 EventFetcher is interrupted.. Returning
[INFO ] 2019-05-09 15:57:40,189 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,189 finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
[INFO ] 2019-05-09 15:57:40,220 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,220 Down to the last merge-pass, with 1 segments left of total size: 57 bytes
[INFO ] 2019-05-09 15:57:40,220 Merged 1 segments, 68 bytes to disk to satisfy reduce memory limit
[INFO ] 2019-05-09 15:57:40,220 Merging 1 files, 72 bytes from disk
[INFO ] 2019-05-09 15:57:40,220 Merging 0 segments, 0 bytes from memory into reduce
[INFO ] 2019-05-09 15:57:40,220 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,236 Down to the last merge-pass, with 1 segments left of total size: 57 bytes
[INFO ] 2019-05-09 15:57:40,236 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,252 mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
[INFO ] 2019-05-09 15:57:40,252 Task:attempt_local1859959178_0001_r_000000_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:40,267 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,267 Task attempt_local1859959178_0001_r_000000_0 is allowed to commit now
[INFO ] 2019-05-09 15:57:40,267 Saved output of task 'attempt_local1859959178_0001_r_000000_0' to file:/E:/hdfs/data/patition/output/_temporary/0/task_local1859959178_0001_r_000000
[INFO ] 2019-05-09 15:57:40,267 reduce > reduce
[INFO ] 2019-05-09 15:57:40,267 Task 'attempt_local1859959178_0001_r_000000_0' done.
[INFO ] 2019-05-09 15:57:40,267 Finishing task: attempt_local1859959178_0001_r_000000_0
[INFO ] 2019-05-09 15:57:40,267 Starting task: attempt_local1859959178_0001_r_000001_0
[INFO ] 2019-05-09 15:57:40,267 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:40,283 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:40,330 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@7e106404
[INFO ] 2019-05-09 15:57:40,330 Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@570b67ab
[INFO ] 2019-05-09 15:57:40,330 MergerManager: memoryLimit=657666880, maxSingleShuffleLimit=164416720, mergeThreshold=434060160, ioSortFactor=10, memToMemMergeOutputsThreshold=10
[INFO ] 2019-05-09 15:57:40,330 attempt_local1859959178_0001_r_000001_0 Thread started: EventFetcher for fetching Map Completion Events
[INFO ] 2019-05-09 15:57:40,330 localfetcher#2 about to shuffle output of map attempt_local1859959178_0001_m_000000_0 decomp: 90 len: 94 to MEMORY
[INFO ] 2019-05-09 15:57:40,330 Read 90 bytes from map-output for attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:40,330 closeInMemoryFile -> map-output of size: 90, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->90
[INFO ] 2019-05-09 15:57:40,330 EventFetcher is interrupted.. Returning
[INFO ] 2019-05-09 15:57:40,330 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,330 finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
[INFO ] 2019-05-09 15:57:40,345 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,345 Down to the last merge-pass, with 1 segments left of total size: 83 bytes
[INFO ] 2019-05-09 15:57:40,345 Merged 1 segments, 90 bytes to disk to satisfy reduce memory limit
[INFO ] 2019-05-09 15:57:40,361 Merging 1 files, 94 bytes from disk
[INFO ] 2019-05-09 15:57:40,361 Merging 0 segments, 0 bytes from memory into reduce
[INFO ] 2019-05-09 15:57:40,361 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,361 Down to the last merge-pass, with 1 segments left of total size: 83 bytes
[INFO ] 2019-05-09 15:57:40,361 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,361 Task:attempt_local1859959178_0001_r_000001_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:40,361 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,361 Task attempt_local1859959178_0001_r_000001_0 is allowed to commit now
[INFO ] 2019-05-09 15:57:40,376 Saved output of task 'attempt_local1859959178_0001_r_000001_0' to file:/E:/hdfs/data/patition/output/_temporary/0/task_local1859959178_0001_r_000001
[INFO ] 2019-05-09 15:57:40,376 reduce > reduce
[INFO ] 2019-05-09 15:57:40,376 Task 'attempt_local1859959178_0001_r_000001_0' done.
[INFO ] 2019-05-09 15:57:40,376 Finishing task: attempt_local1859959178_0001_r_000001_0
[INFO ] 2019-05-09 15:57:40,376 Starting task: attempt_local1859959178_0001_r_000002_0
[INFO ] 2019-05-09 15:57:40,376 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:40,376 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:40,439 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@8b6647c
[INFO ] 2019-05-09 15:57:40,439 Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@48c7cfe
[INFO ] 2019-05-09 15:57:40,439 MergerManager: memoryLimit=657666880, maxSingleShuffleLimit=164416720, mergeThreshold=434060160, ioSortFactor=10, memToMemMergeOutputsThreshold=10
[INFO ] 2019-05-09 15:57:40,439 attempt_local1859959178_0001_r_000002_0 Thread started: EventFetcher for fetching Map Completion Events
[INFO ] 2019-05-09 15:57:40,439 localfetcher#3 about to shuffle output of map attempt_local1859959178_0001_m_000000_0 decomp: 30 len: 34 to MEMORY
[INFO ] 2019-05-09 15:57:40,439 Read 30 bytes from map-output for attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:40,439 closeInMemoryFile -> map-output of size: 30, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->30
[INFO ] 2019-05-09 15:57:40,439 EventFetcher is interrupted.. Returning
[INFO ] 2019-05-09 15:57:40,439 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,439 finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
[INFO ] 2019-05-09 15:57:40,454 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,454 Down to the last merge-pass, with 1 segments left of total size: 23 bytes
[INFO ] 2019-05-09 15:57:40,470 Merged 1 segments, 30 bytes to disk to satisfy reduce memory limit
[INFO ] 2019-05-09 15:57:40,470 Merging 1 files, 34 bytes from disk
[INFO ] 2019-05-09 15:57:40,470 Merging 0 segments, 0 bytes from memory into reduce
[INFO ] 2019-05-09 15:57:40,470 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,470 Down to the last merge-pass, with 1 segments left of total size: 23 bytes
[INFO ] 2019-05-09 15:57:40,470 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,501 Task:attempt_local1859959178_0001_r_000002_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:40,501 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,501 Task attempt_local1859959178_0001_r_000002_0 is allowed to commit now
[INFO ] 2019-05-09 15:57:40,517 Saved output of task 'attempt_local1859959178_0001_r_000002_0' to file:/E:/hdfs/data/patition/output/_temporary/0/task_local1859959178_0001_r_000002
[INFO ] 2019-05-09 15:57:40,517 reduce > reduce
[INFO ] 2019-05-09 15:57:40,517 Task 'attempt_local1859959178_0001_r_000002_0' done.
[INFO ] 2019-05-09 15:57:40,517 Finishing task: attempt_local1859959178_0001_r_000002_0
[INFO ] 2019-05-09 15:57:40,517 Starting task: attempt_local1859959178_0001_r_000003_0
[INFO ] 2019-05-09 15:57:40,517 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:40,517 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:40,548 Job job_local1859959178_0001 running in uber mode : false
[INFO ] 2019-05-09 15:57:40,548 map 100% reduce 100%
[INFO ] 2019-05-09 15:57:40,579 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@35a9936c
[INFO ] 2019-05-09 15:57:40,579 Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@e079421
[INFO ] 2019-05-09 15:57:40,579 MergerManager: memoryLimit=657666880, maxSingleShuffleLimit=164416720, mergeThreshold=434060160, ioSortFactor=10, memToMemMergeOutputsThreshold=10
[INFO ] 2019-05-09 15:57:40,579 attempt_local1859959178_0001_r_000003_0 Thread started: EventFetcher for fetching Map Completion Events
[INFO ] 2019-05-09 15:57:40,579 localfetcher#4 about to shuffle output of map attempt_local1859959178_0001_m_000000_0 decomp: 49 len: 53 to MEMORY
[INFO ] 2019-05-09 15:57:40,579 Read 49 bytes from map-output for attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:40,579 closeInMemoryFile -> map-output of size: 49, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->49
[INFO ] 2019-05-09 15:57:40,579 EventFetcher is interrupted.. Returning
[INFO ] 2019-05-09 15:57:40,579 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,579 finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
[INFO ] 2019-05-09 15:57:40,595 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,595 Down to the last merge-pass, with 1 segments left of total size: 42 bytes
[INFO ] 2019-05-09 15:57:40,610 Merged 1 segments, 49 bytes to disk to satisfy reduce memory limit
[INFO ] 2019-05-09 15:57:40,610 Merging 1 files, 53 bytes from disk
[INFO ] 2019-05-09 15:57:40,610 Merging 0 segments, 0 bytes from memory into reduce
[INFO ] 2019-05-09 15:57:40,610 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,610 Down to the last merge-pass, with 1 segments left of total size: 42 bytes
[INFO ] 2019-05-09 15:57:40,610 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,626 Task:attempt_local1859959178_0001_r_000003_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:40,626 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,626 Task attempt_local1859959178_0001_r_000003_0 is allowed to commit now
[INFO ] 2019-05-09 15:57:40,642 Saved output of task 'attempt_local1859959178_0001_r_000003_0' to file:/E:/hdfs/data/patition/output/_temporary/0/task_local1859959178_0001_r_000003
[INFO ] 2019-05-09 15:57:40,642 reduce > reduce
[INFO ] 2019-05-09 15:57:40,642 Task 'attempt_local1859959178_0001_r_000003_0' done.
[INFO ] 2019-05-09 15:57:40,642 Finishing task: attempt_local1859959178_0001_r_000003_0
[INFO ] 2019-05-09 15:57:40,642 Starting task: attempt_local1859959178_0001_r_000004_0
[INFO ] 2019-05-09 15:57:40,642 File Output Committer Algorithm version is 1
[INFO ] 2019-05-09 15:57:40,642 ProcfsBasedProcessTree currently is supported only on Linux.
[INFO ] 2019-05-09 15:57:40,688 Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@54fd7bab
[INFO ] 2019-05-09 15:57:40,688 Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@6902049
[INFO ] 2019-05-09 15:57:40,688 MergerManager: memoryLimit=657666880, maxSingleShuffleLimit=164416720, mergeThreshold=434060160, ioSortFactor=10, memToMemMergeOutputsThreshold=10
[INFO ] 2019-05-09 15:57:40,688 attempt_local1859959178_0001_r_000004_0 Thread started: EventFetcher for fetching Map Completion Events
[INFO ] 2019-05-09 15:57:40,704 localfetcher#5 about to shuffle output of map attempt_local1859959178_0001_m_000000_0 decomp: 76 len: 80 to MEMORY
[INFO ] 2019-05-09 15:57:40,704 Read 76 bytes from map-output for attempt_local1859959178_0001_m_000000_0
[INFO ] 2019-05-09 15:57:40,704 closeInMemoryFile -> map-output of size: 76, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->76
[INFO ] 2019-05-09 15:57:40,704 EventFetcher is interrupted.. Returning
[INFO ] 2019-05-09 15:57:40,704 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,704 finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
[INFO ] 2019-05-09 15:57:40,720 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,720 Down to the last merge-pass, with 1 segments left of total size: 69 bytes
[INFO ] 2019-05-09 15:57:40,720 Merged 1 segments, 76 bytes to disk to satisfy reduce memory limit
[INFO ] 2019-05-09 15:57:40,720 Merging 1 files, 80 bytes from disk
[INFO ] 2019-05-09 15:57:40,720 Merging 0 segments, 0 bytes from memory into reduce
[INFO ] 2019-05-09 15:57:40,720 Merging 1 sorted segments
[INFO ] 2019-05-09 15:57:40,720 Down to the last merge-pass, with 1 segments left of total size: 69 bytes
[INFO ] 2019-05-09 15:57:40,720 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,751 Task:attempt_local1859959178_0001_r_000004_0 is done. And is in the process of committing
[INFO ] 2019-05-09 15:57:40,751 1 / 1 copied.
[INFO ] 2019-05-09 15:57:40,751 Task attempt_local1859959178_0001_r_000004_0 is allowed to commit now
[INFO ] 2019-05-09 15:57:40,766 Saved output of task 'attempt_local1859959178_0001_r_000004_0' to file:/E:/hdfs/data/patition/output/_temporary/0/task_local1859959178_0001_r_000004
[INFO ] 2019-05-09 15:57:40,766 reduce > reduce
[INFO ] 2019-05-09 15:57:40,766 Task 'attempt_local1859959178_0001_r_000004_0' done.
[INFO ] 2019-05-09 15:57:40,766 Finishing task: attempt_local1859959178_0001_r_000004_0
[INFO ] 2019-05-09 15:57:40,766 reduce task executor complete.
[INFO ] 2019-05-09 15:57:41,549 Job job_local1859959178_0001 completed successfully
[INFO ] 2019-05-09 15:57:41,580 Counters: 30
File System Counters
FILE: Number of bytes read=8840
FILE: Number of bytes written=1733562
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
Map-Reduce Framework
Map input records=10
Map output records=10
Map output bytes=283
Map output materialized bytes=333
Input split bytes=107
Combine input records=0
Combine output records=0
Reduce input groups=10
Reduce shuffle bytes=333
Reduce input records=10
Reduce output records=10
Spilled Records=20
Shuffled Maps =5
Failed Shuffles=0
Merged Map outputs=5
GC time elapsed (ms)=0
Total committed heap usage (bytes)=1321205760
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=228
File Output Format Counters
Bytes Written=343
Process finished with exit code 0
但是如果我们设置的ReduceTask不正好怎么办？
- 设置reduceTask为1
结果是只有一个文件。因为你只有一个reducetask，所有的分区只能都放到这个reduce里面去，所以只有一个文件
- 设置reduceTask为2
报异常了，这是因为你只有2个reduceTask，但是你有5个分区，它不知道到底该怎么放。所以会报错
- 设置reduceTask为6
你会发现有6个文件，但是第6个文件是空的，也即是说我有5个分区，你有6个reduceTask 那我就按照顺序放尽可以了，剩下一个就闲置在那里。
