MapReduce编程开发之求平均成绩

2023-10-09 08:59
文章标签 开发 编程 平均 成绩 mapreduce 之求

本文主要是介绍MapReduce编程开发之求平均成绩，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

    MapReduce计算平均成绩是一个常见的算法，本省思路很简单，就是将每个人的成绩汇总，然后做除法，在map阶段，是直接将姓名做key,分数作为value输出。在shuffle阶段，会将每个人的所有成绩做汇总，数据结构变为<name,<score1,score2...>>这样子，我们在reduce阶段就通过分数这个value-list来结算平均分。average = sum(score)/courseCount，即平均分等于分数总和除以课程数。

mapreduce代码：

package com.xxx.hadoop.mapred;
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
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;/*** 求平均成绩**/
public class AverageScoreApp {public static class Map extends Mapper<Object, Text, Text, IntWritable>{@Overrideprotected void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context)throws IOException, InterruptedException {//成绩的结构是:// 张三	80// 李四	82// 王五	86StringTokenizer tokenizer = new StringTokenizer(value.toString(), "\n");while(tokenizer.hasMoreElements()) {StringTokenizer lineTokenizer = new StringTokenizer(tokenizer.nextToken());String name = lineTokenizer.nextToken(); //姓名String score = lineTokenizer.nextToken();//成绩context.write(new Text(name), new IntWritable(Integer.parseInt(score)));}}}public static class Reduce extends Reducer<Text, IntWritable, Text, DoubleWritable>{@Overrideprotected void reduce(Text key, Iterable<IntWritable> values,Reducer<Text, IntWritable, Text, DoubleWritable>.Context context)throws IOException, InterruptedException {//reduce这里输入的数据结构是：// 张三 <80,85,90>// 李四 <82,88,94>// 王五 <86,80,92>int sum = 0;//所有课程成绩总分double average = 0;//平均成绩int courseNum = 0; //课程数目for(IntWritable score:values) {sum += score.get();courseNum++;}average = sum/courseNum;context.write(new Text(key), new DoubleWritable(average));}}public static void main(String[] args) throws Exception{String input="/user/root/averagescore/input",output="/user/root/averagescore/output";System.setProperty("HADOOP_USER_NAME", "root");Configuration conf = new Configuration();conf.set("fs.defaultFS", "hdfs://192.168.56.202:9000");Job job = Job.getInstance(conf);job.setJarByClass(AverageScoreApp.class);job.setMapperClass(Map.class);job.setReducerClass(Reduce.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(IntWritable.class);job.setOutputKeyClass(Text.class);job.setOutputValueClass(DoubleWritable.class);FileInputFormat.addInputPath(job, new Path(input));FileOutputFormat.setOutputPath(job, new Path(output));System.exit(job.waitForCompletion(true)?0:1);}}

准备学生成绩数据：

控制台打印信息：

2019-08-31 15:50:26 [INFO ]  [main]  [org.apache.hadoop.conf.Configuration.deprecation] session.id is deprecated. Instead, use dfs.metrics.session-id
2019-08-31 15:50:26 [INFO ]  [main]  [org.apache.hadoop.metrics.jvm.JvmMetrics] Initializing JVM Metrics with processName=JobTracker, sessionId=
2019-08-31 15:50:27 [WARN ]  [main]  [org.apache.hadoop.mapreduce.JobResourceUploader] Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
2019-08-31 15:50:27 [WARN ]  [main]  [org.apache.hadoop.mapreduce.JobResourceUploader] No job jar file set.  User classes may not be found. See Job or Job#setJar(String).
2019-08-31 15:50:27 [INFO ]  [main]  [org.apache.hadoop.mapreduce.lib.input.FileInputFormat] Total input paths to process : 3
2019-08-31 15:50:27 [INFO ]  [main]  [org.apache.hadoop.mapreduce.JobSubmitter] number of splits:3
2019-08-31 15:50:27 [INFO ]  [main]  [org.apache.hadoop.mapreduce.JobSubmitter] Submitting tokens for job: job_local83653871_0001
2019-08-31 15:50:27 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job] The url to track the job: http://localhost:8080/
2019-08-31 15:50:27 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job] Running job: job_local83653871_0001
2019-08-31 15:50:27 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] OutputCommitter set in config null
2019-08-31 15:50:27 [INFO ]  [Thread-3]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] File Output Committer Algorithm version is 1
2019-08-31 15:50:27 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
2019-08-31 15:50:27 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] Waiting for map tasks
2019-08-31 15:50:27 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Starting task: attempt_local83653871_0001_m_000000_0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] File Output Committer Algorithm version is 1
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] ProcfsBasedProcessTree currently is supported only on Linux.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task]  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@52fc070c
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Processing split: hdfs://192.168.56.202:9000/user/root/averagescore/input/math.txt:0+55
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] (EQUATOR) 0 kvi 26214396(104857584)
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] mapreduce.task.io.sort.mb: 100
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] soft limit at 83886080
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396; length = 6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] 
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Starting flush of map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Spilling map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufend = 58; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396(104857584); kvend = 26214380(104857520); length = 17/6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Finished spill 0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task:attempt_local83653871_0001_m_000000_0 is done. And is in the process of committing
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] map
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task 'attempt_local83653871_0001_m_000000_0' done.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Finishing task: attempt_local83653871_0001_m_000000_0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Starting task: attempt_local83653871_0001_m_000001_0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] File Output Committer Algorithm version is 1
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] ProcfsBasedProcessTree currently is supported only on Linux.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task]  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@3f0602b3
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Processing split: hdfs://192.168.56.202:9000/user/root/averagescore/input/chinese.txt:0+54
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] (EQUATOR) 0 kvi 26214396(104857584)
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] mapreduce.task.io.sort.mb: 100
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] soft limit at 83886080
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396; length = 6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] 
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Starting flush of map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Spilling map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufend = 58; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396(104857584); kvend = 26214380(104857520); length = 17/6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Finished spill 0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task:attempt_local83653871_0001_m_000001_0 is done. And is in the process of committing
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] map
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task 'attempt_local83653871_0001_m_000001_0' done.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Finishing task: attempt_local83653871_0001_m_000001_0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Starting task: attempt_local83653871_0001_m_000002_0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] File Output Committer Algorithm version is 1
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] ProcfsBasedProcessTree currently is supported only on Linux.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task]  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@47fe69f7
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Processing split: hdfs://192.168.56.202:9000/user/root/averagescore/input/english.txt:0+53
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] (EQUATOR) 0 kvi 26214396(104857584)
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] mapreduce.task.io.sort.mb: 100
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] soft limit at 83886080
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396; length = 6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] 
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Starting flush of map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Spilling map output
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] bufstart = 0; bufend = 58; bufvoid = 104857600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] kvstart = 26214396(104857584); kvend = 26214380(104857520); length = 17/6553600
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.MapTask] Finished spill 0
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task:attempt_local83653871_0001_m_000002_0 is done. And is in the process of committing
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] map
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.Task] Task 'attempt_local83653871_0001_m_000002_0' done.
2019-08-31 15:50:28 [INFO ]  [LocalJobRunner Map Task Executor #0]  [org.apache.hadoop.mapred.LocalJobRunner] Finishing task: attempt_local83653871_0001_m_000002_0
2019-08-31 15:50:28 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] map task executor complete.
2019-08-31 15:50:28 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] Waiting for reduce tasks
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] Starting task: attempt_local83653871_0001_r_000000_0
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] File Output Committer Algorithm version is 1
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.yarn.util.ProcfsBasedProcessTree] ProcfsBasedProcessTree currently is supported only on Linux.
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Task]  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@4309aafd
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.ReduceTask] Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@44113ec8
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] MergerManager: memoryLimit=1265788544, maxSingleShuffleLimit=316447136, mergeThreshold=835420480, ioSortFactor=10, memToMemMergeOutputsThreshold=10
2019-08-31 15:50:28 [INFO ]  [EventFetcher for fetching Map Completion Events]  [org.apache.hadoop.mapreduce.task.reduce.EventFetcher] attempt_local83653871_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.LocalFetcher] localfetcher#1 about to shuffle output of map attempt_local83653871_0001_m_000000_0 decomp: 70 len: 74 to MEMORY
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput] Read 70 bytes from map-output for attempt_local83653871_0001_m_000000_0
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] closeInMemoryFile -> map-output of size: 70, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->70
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.LocalFetcher] localfetcher#1 about to shuffle output of map attempt_local83653871_0001_m_000001_0 decomp: 70 len: 74 to MEMORY
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput] Read 70 bytes from map-output for attempt_local83653871_0001_m_000001_0
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] closeInMemoryFile -> map-output of size: 70, inMemoryMapOutputs.size() -> 2, commitMemory -> 70, usedMemory ->140
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.LocalFetcher] localfetcher#1 about to shuffle output of map attempt_local83653871_0001_m_000002_0 decomp: 70 len: 74 to MEMORY
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput] Read 70 bytes from map-output for attempt_local83653871_0001_m_000002_0
2019-08-31 15:50:28 [INFO ]  [localfetcher#1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] closeInMemoryFile -> map-output of size: 70, inMemoryMapOutputs.size() -> 3, commitMemory -> 140, usedMemory ->210
2019-08-31 15:50:28 [INFO ]  [EventFetcher for fetching Map Completion Events]  [org.apache.hadoop.mapreduce.task.reduce.EventFetcher] EventFetcher is interrupted.. Returning
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] 3 / 3 copied.
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] finalMerge called with 3 in-memory map-outputs and 0 on-disk map-outputs
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Merger] Merging 3 sorted segments
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Merger] Down to the last merge-pass, with 3 segments left of total size: 174 bytes
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] Merged 3 segments, 210 bytes to disk to satisfy reduce memory limit
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] Merging 1 files, 210 bytes from disk
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl] Merging 0 segments, 0 bytes from memory into reduce
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Merger] Merging 1 sorted segments
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Merger] Down to the last merge-pass, with 1 segments left of total size: 194 bytes
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] 3 / 3 copied.
2019-08-31 15:50:28 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job] Job job_local83653871_0001 running in uber mode : false
2019-08-31 15:50:28 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job]  map 100% reduce 0%
2019-08-31 15:50:28 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.conf.Configuration.deprecation] mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Task] Task:attempt_local83653871_0001_r_000000_0 is done. And is in the process of committing
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] 3 / 3 copied.
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Task] Task attempt_local83653871_0001_r_000000_0 is allowed to commit now
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter] Saved output of task 'attempt_local83653871_0001_r_000000_0' to hdfs://192.168.56.202:9000/user/root/averagescore/output/_temporary/0/task_local83653871_0001_r_000000
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] reduce > reduce
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.Task] Task 'attempt_local83653871_0001_r_000000_0' done.
2019-08-31 15:50:29 [INFO ]  [pool-6-thread-1]  [org.apache.hadoop.mapred.LocalJobRunner] Finishing task: attempt_local83653871_0001_r_000000_0
2019-08-31 15:50:29 [INFO ]  [Thread-3]  [org.apache.hadoop.mapred.LocalJobRunner] reduce task executor complete.
2019-08-31 15:50:29 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job]  map 100% reduce 100%
2019-08-31 15:50:29 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job] Job job_local83653871_0001 completed successfully
2019-08-31 15:50:29 [INFO ]  [main]  [org.apache.hadoop.mapreduce.Job] Counters: 35File System CountersFILE: Number of bytes read=4456FILE: Number of bytes written=1087800FILE: Number of read operations=0FILE: Number of large read operations=0FILE: Number of write operations=0HDFS: Number of bytes read=488HDFS: Number of bytes written=63HDFS: Number of read operations=33HDFS: Number of large read operations=0HDFS: Number of write operations=6Map-Reduce FrameworkMap input records=15Map output records=15Map output bytes=174Map output materialized bytes=222Input split bytes=393Combine input records=0Combine output records=0Reduce input groups=5Reduce shuffle bytes=222Reduce input records=15Reduce output records=5Spilled Records=30Shuffled Maps =3Failed Shuffles=0Merged Map outputs=3GC time elapsed (ms)=27Total committed heap usage (bytes)=1493172224Shuffle ErrorsBAD_ID=0CONNECTION=0IO_ERROR=0WRONG_LENGTH=0WRONG_MAP=0WRONG_REDUCE=0File Input Format Counters Bytes Read=162File Output Format Counters Bytes Written=63

运行完毕，查看结果：

 

这篇关于MapReduce编程开发之求平均成绩的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！


http://www.chinasem.cn/article/171731。

相关文章

Go语言开发实现查询IP信息的MCP服务器

Go语言开发实现查询IP信息的MCP服务器

《Go语言开发实现查询IP信息的MCP服务器》随着MCP的快速普及和广泛应用,MCP服务器也层出不穷,本文将详细介绍如何在Go语言中使用go-mcp库来开发一个查询IP信息的MCP... 目录前言mcp-ip-geo 服务器目录结构说明查询 IP 信息功能实现工具实现工具管理查询单个 IP 信息工具的实现服
阅读更多...
shell编程之函数与数组的使用详解

shell编程之函数与数组的使用详解

《shell编程之函数与数组的使用详解》：本文主要介绍shell编程之函数与数组的使用,具有很好的参考价值,希望对大家有所帮助,如有错误或未考虑完全的地方,望不吝赐教... 目录shell函数函数的用法俩个数求和系统资源监控并报警函数函数变量的作用范围函数的参数递归函数shell数组获取数组的长度读取某下的
阅读更多...
使用Python开发一个带EPUB转换功能的Markdown编辑器

使用Python开发一个带EPUB转换功能的Markdown编辑器

《使用Python开发一个带EPUB转换功能的Markdown编辑器》Markdown因其简单易用和强大的格式支持,成为了写作者、开发者及内容创作者的首选格式,本文将通过Python开发一个Markd... 目录应用概览代码结构与核心组件1. 初始化与布局 (__init__)2. 工具栏 (setup_t
阅读更多...
Spring Shell 命令行实现交互式Shell应用开发

Spring Shell 命令行实现交互式Shell应用开发

《SpringShell命令行实现交互式Shell应用开发》本文主要介绍了SpringShell命令行实现交互式Shell应用开发,能够帮助开发者快速构建功能丰富的命令行应用程序,具有一定的参考价... 目录引言一、Spring Shell概述二、创建命令类三、命令参数处理四、命令分组与帮助系统五、自定义S
阅读更多...
Python通过模块化开发优化代码的技巧分享

Python通过模块化开发优化代码的技巧分享

《Python通过模块化开发优化代码的技巧分享》模块化开发就是把代码拆成一个个“零件”,该封装封装,该拆分拆分,下面小编就来和大家简单聊聊python如何用模块化开发进行代码优化吧... 目录什么是模块化开发如何拆分代码改进版：拆分成模块让模块更强大：使用 __init__.py你一定会遇到的问题模www.
阅读更多...
Spring Security基于数据库的ABAC属性权限模型实战开发教程

Spring Security基于数据库的ABAC属性权限模型实战开发教程

《SpringSecurity基于数据库的ABAC属性权限模型实战开发教程》：本文主要介绍SpringSecurity基于数据库的ABAC属性权限模型实战开发教程,本文给大家介绍的非常详细,对大... 目录1. 前言2. 权限决策依据RBACABAC综合对比3. 数据库表结构说明4. 实战开始5. MyBA
阅读更多...
使用Python开发一个简单的本地图片服务器

使用Python开发一个简单的本地图片服务器

《使用Python开发一个简单的本地图片服务器》本文介绍了如何结合wxPython构建的图形用户界面GUI和Python内建的Web服务器功能,在本地网络中搭建一个私人的,即开即用的网页相册,文中的示... 目录项目目标核心技术栈代码深度解析完整代码工作流程主要功能与优势潜在改进与思考运行结果总结你是否曾经
阅读更多...
揭秘Python Socket网络编程的7种硬核用法

揭秘Python Socket网络编程的7种硬核用法

《揭秘PythonSocket网络编程的7种硬核用法》Socket不仅能做聊天室,还能干一大堆硬核操作,这篇文章就带大家看看Python网络编程的7种超实用玩法,感兴趣的小伙伴可以跟随小编一起... 目录1.端口扫描器：探测开放端口2.简易 HTTP 服务器：10 秒搭个网页3.局域网游戏：多人联机对战4.
阅读更多...
Spring Boot + MyBatis Plus 高效开发实战从入门到进阶优化(推荐)

Spring Boot + MyBatis Plus 高效开发实战从入门到进阶优化(推荐)

《SpringBoot+MyBatisPlus高效开发实战从入门到进阶优化(推荐)》本文将详细介绍SpringBoot+MyBatisPlus的完整开发流程,并深入剖析分页查询、批量操作、动... 目录Spring Boot + MyBATis Plus 高效开发实战：从入门到进阶优化1. MyBatis
阅读更多...
Java并发编程必备之Synchronized关键字深入解析

Java并发编程必备之Synchronized关键字深入解析

《Java并发编程必备之Synchronized关键字深入解析》本文我们深入探索了Java中的Synchronized关键字,包括其互斥性和可重入性的特性,文章详细介绍了Synchronized的三种... 目录一、前言二、Synchronized关键字2.1 Synchronized的特性1. 互斥2.
阅读更多...

Copyright China编程 23002807@qq.com

沪ICP备2023033072号-2