MapReduce编程开发之求平均成绩

2023-10-09 08:59

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

Java AOP面向切面编程的概念和实现方式

《JavaAOP面向切面编程的概念和实现方式》AOP是面向切面编程,通过动态代理将横切关注点(如日志、事务)与核心业务逻辑分离,提升代码复用性和可维护性,本文给大家介绍JavaAOP面向切面编程的概... 目录一、AOP 是什么?二、AOP 的核心概念与实现方式核心概念实现方式三、Spring AOP 的关

一文详解Python如何开发游戏

《一文详解Python如何开发游戏》Python是一种非常流行的编程语言,也可以用来开发游戏模组,:本文主要介绍Python如何开发游戏的相关资料,文中通过代码介绍的非常详细,需要的朋友可以参考下... 目录一、python简介二、Python 开发 2D 游戏的优劣势优势缺点三、Python 开发 3D

基于Python开发Windows自动更新控制工具

《基于Python开发Windows自动更新控制工具》在当今数字化时代,操作系统更新已成为计算机维护的重要组成部分,本文介绍一款基于Python和PyQt5的Windows自动更新控制工具,有需要的可... 目录设计原理与技术实现系统架构概述数学建模工具界面完整代码实现技术深度分析多层级控制理论服务层控制注

Java中的分布式系统开发基于 Zookeeper 与 Dubbo 的应用案例解析

《Java中的分布式系统开发基于Zookeeper与Dubbo的应用案例解析》本文将通过实际案例,带你走进基于Zookeeper与Dubbo的分布式系统开发,本文通过实例代码给大家介绍的非常详... 目录Java 中的分布式系统开发基于 Zookeeper 与 Dubbo 的应用案例一、分布式系统中的挑战二

基于Go语言开发一个 IP 归属地查询接口工具

《基于Go语言开发一个IP归属地查询接口工具》在日常开发中,IP地址归属地查询是一个常见需求,本文将带大家使用Go语言快速开发一个IP归属地查询接口服务,有需要的小伙伴可以了解下... 目录功能目标技术栈项目结构核心代码(main.go)使用方法扩展功能总结在日常开发中,IP 地址归属地查询是一个常见需求:

基于 Cursor 开发 Spring Boot 项目详细攻略

《基于Cursor开发SpringBoot项目详细攻略》Cursor是集成GPT4、Claude3.5等LLM的VSCode类AI编程工具,支持SpringBoot项目开发全流程,涵盖环境配... 目录cursor是什么?基于 Cursor 开发 Spring Boot 项目完整指南1. 环境准备2. 创建

MySQL的JDBC编程详解

《MySQL的JDBC编程详解》:本文主要介绍MySQL的JDBC编程,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... 目录前言一、前置知识1. 引入依赖2. 认识 url二、JDBC 操作流程1. JDBC 的写操作2. JDBC 的读操作总结前言本文介绍了mysq

SpringBoot 多环境开发实战(从配置、管理与控制)

《SpringBoot多环境开发实战(从配置、管理与控制)》本文详解SpringBoot多环境配置,涵盖单文件YAML、多文件模式、MavenProfile分组及激活策略,通过优先级控制灵活切换环境... 目录一、多环境开发基础(单文件 YAML 版)(一)配置原理与优势(二)实操示例二、多环境开发多文件版

使用docker搭建嵌入式Linux开发环境

《使用docker搭建嵌入式Linux开发环境》本文主要介绍了使用docker搭建嵌入式Linux开发环境,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面... 目录1、前言2、安装docker3、编写容器管理脚本4、创建容器1、前言在日常开发全志、rk等不同

Python实战之SEO优化自动化工具开发指南

《Python实战之SEO优化自动化工具开发指南》在数字化营销时代,搜索引擎优化(SEO)已成为网站获取流量的重要手段,本文将带您使用Python开发一套完整的SEO自动化工具,需要的可以了解下... 目录前言项目概述技术栈选择核心模块实现1. 关键词研究模块2. 网站技术seo检测模块3. 内容优化分析模