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一、WordCount代码
(一)WordCount简介
1.wordcount.txt
(二)WordCount的java代码
1.WordCountMapper
2.WordCountReduce
3.WordCountDriver
(三)IDEA运行结果
(四)Hadoop运行wordcount
1.在HDFS上新建一个文件目录
2.新建一个文件#xff0c;并上传至该目录下…目录
一、WordCount代码
(一)WordCount简介
1.wordcount.txt
(二)WordCount的java代码
1.WordCountMapper
2.WordCountReduce
3.WordCountDriver
(三)IDEA运行结果
(四)Hadoop运行wordcount
1.在HDFS上新建一个文件目录
2.新建一个文件并上传至该目录下
3.执行wordcount命令
4.查看运行结果
5.第二次提交报错原因
6.进入NodeManager查看
7.启动历史服务器(如果已经启动可以忽略此步骤)
8.查看历史服务信息
三、执行本地代码
(一)项目代码
1.stuscore.csv
2.Student类
2.StudentMapper类
4.StudentReduce类
5.StudentDriver类
(二)java代码中指定路径
1.maven项目编译并打包
2.上传stuscore.csv到hdfs指定目录下
3.xftp上传target目录下的打包好的jar包上传到虚拟机
4.Hadoop运行hadoopstu-1.0-SNAPSHOT.jar
5.Hadoop运行结果
(三)java代码中不指定路径
1.StuudentDriver类
2.重新编译打包上传
3.HDFS命令执行该jar包
4.查看运行结果 一、WordCount代码
(一)WordCount简介
WordCount是大数据经典案例其逻辑就是有一个文本文件通过编写java代码与Hadoop核心组件的操作查询每个单词出现的频率。
1.wordcount.txt hello java
hello hadoop
hello java hadoop
java hadoop
java hadoop
hadoop java
hello java (二)WordCount的java代码
1.WordCountMapper
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;// MapperKEYIN, VALUEIN, KEYOUT, VALUEOUT
// 0,hello world,hello,1
public class WordCountMapper extends MapperLongWritable, Text,Text, IntWritable {Text text new Text();IntWritable intWritable new IntWritable();Overrideprotected void map(LongWritable key, Text value, MapperLongWritable, Text, Text, IntWritable.Context context) throws IOException, InterruptedException {System.out.println(WordCount stage Key:key Value:value);String[] words value.toString().split( );// hello world --[hello,world]for (String word :words) {text.set(word);intWritable.set(1);context.write(text,intWritable);// 输出键值对 hello,1world,1}}
}
2.WordCountReduce
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;// KEYIN, VALUEIN, KEYOUT, VALUEOUT
public class WordCountReduce extends ReducerText, IntWritable,Text, LongWritable {Overrideprotected void reduce(Text key, IterableIntWritable values, ReducerText, IntWritable, Text, LongWritable.Context context) throws IOException, InterruptedException {System.out.println(Reduce stage Key:key Values:values.toString());int count 0;for (IntWritable intWritable :values) {count intWritable.get();}
// LongWritable longWritable new LongWritable();
// longWritable.set(count);LongWritable longWritable new LongWritable(count);System.out.println(Key:key ResultValue:longWritable.get());context.write(key,longWritable);}
}
3.WordCountDriver
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
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 WordCountDriver {public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {Configuration configuration new Configuration();Job job Job.getInstance(configuration);job.setJarByClass(WordCountDriver.class);// 设置mapper类job.setMapperClass(WordCountMapper.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(IntWritable.class);// 设置reduce类job.setReducerClass(WordCountReduce.class);job.setOutputKeyClass(Text.class);job.setOutputValueClass(LongWritable.class);// 指定map输入的文件路径FileInputFormat.setInputPaths(job,new Path(D:\\javaseprojects\\hadoopstu\\input\\demo1\\wordcount.txt));// 指定reduce结果输出的文件路径Path path new Path(D:\\javaseprojects\\hadoopstu\\output);FileSystem fileSystem FileSystem.get(path.toUri(),configuration);if(fileSystem.exists(path)){fileSystem.delete(path,true);}FileOutputFormat.setOutputPath(job,path);job.waitForCompletion(true);
// job.setJobName();}
}(三)IDEA运行结果 (四)Hadoop运行wordcount
1.在HDFS上新建一个文件目录
[rootlxm147 ~]# hdfs dfs -mkdir /inputpath
2023-02-10 23:05:40,098 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[rootlxm147 ~]# hdfs dfs -ls /
2023-02-10 23:05:52,217 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 3 items
drwxr-xr-x - root supergroup 0 2023-02-08 08:06 /aa
drwxr-xr-x - root supergroup 0 2023-02-10 10:52 /bigdata
drwxr-xr-x - root supergroup 0 2023-02-10 23:05 /inputpath
2.新建一个文件并上传至该目录下
[rootlxm147 mapreduce]# vim ./test.csv
[rootlxm147 mapreduce]# hdfs dfs -put ./test.csv /inputpath 3.执行wordcount命令
[rootlxm147 mapreduce]# hadoop jar ./hadoop-mapreduce-examples-3.1.3.jar wordcount /inputpath /outputpath4.查看运行结果
(1)web端 (2)命令行
[rootlxm147 mapreduce]# hdfs dfs -cat /outputpath/part-r-00000
2023-02-10 23:26:06,276 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2023-02-10 23:26:07,793 INFO sasl.SaslDataTransferClient: SASL encryption trust check: localHostTrusted false, remoteHostTrusted false
hadoop 1
hello 2
java 2
javaweb 1
mybatis 2
spring 1
5.第二次提交报错原因
执行wordcount命令前删除/outpath目录下的文件再执行即可
6.进入NodeManager查看
http://lxm147:8088/cluster 7.启动历史服务器(如果已经启动可以忽略此步骤)
[rootlxm148 ~]# mr-jobhistory-daemon.sh start historyserver
WARNING: Use of this script to start the MR JobHistory daemon is deprecated.
WARNING: Attempting to execute replacement mapred --daemon start instead.
[rootlxm148 ~]# jps
4546 SecondaryNameNode
6370 JobHistoryServer
4164 NameNode
4804 ResourceManager
4937 NodeManager
6393 Jps
4302 DataNode8.查看历史服务信息
http://lxm147:19888/ 三、执行本地代码
(一)项目代码
1.stuscore.csv 1,zs,10,语文
2,ls,98,语文
3,ww,80,语文
1,zs,20,数学
2,ls,87,数学
3,ww,58,数学
1,zs,44,英语
2,ls,66,英语
3,ww,40,英语
1,zs,55,政治
2,ls,60,政治
3,ww,80,政治
1,zs,10,化学
2,ls,28,化学
3,ww,78,化学
1,zs,87,生物
2,ls,9,生物
3,ww,10,生物 2.Student类
import org.apache.hadoop.io.WritableComparable;import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;public class Student implements WritableComparableStudent {private long stuid;private String stuname;private int score;private String lession;Overridepublic int compareTo(Student o) {return this.score o.score ? 1 : 0;}Overridepublic void write(DataOutput dataOutput) throws IOException {dataOutput.writeLong(stuid);dataOutput.writeUTF(stuname);dataOutput.writeUTF(lession);dataOutput.writeInt(score);}Overridepublic void readFields(DataInput dataInput) throws IOException {this.stuid dataInput.readLong();this.stuname dataInput.readUTF();this.lession dataInput.readUTF();this.score dataInput.readInt();}Overridepublic String toString() {return Student{ stuid stuid , stuname stuname \ , score score , lession lession \ };}public long getStuid() {return stuid;}public void setStuid(long stuid) {this.stuid stuid;}public String getStuname() {return stuname;}public void setStuname(String stuname) {this.stuname stuname;}public int getScore() {return score;}public void setScore(int score) {this.score score;}public String getLession() {return lession;}public void setLession(String lession) {this.lession lession;}public Student(long stuid, String stuname, int score, String lession) {this.stuid stuid;this.stuname stuname;this.score score;this.lession lession;}public Student() {}
}2.StudentMapper类
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;// Kid,Vstudent
// Mapper进来的K,进来的V,出去的K,出去的V
public class StudentMapper extends MapperLongWritable, Text, LongWritable, Student {Overrideprotected void map(LongWritable key, Text value, MapperLongWritable, Text, LongWritable, Student.Context context) throws IOException, InterruptedException {System.out.println(key value.toString());String[] split value.toString().split(,);LongWritable stuidKey new LongWritable(Long.parseLong(split[2]));Student studentValue new Student(Long.parseLong(split[0]), split[1], Integer.parseInt(split[2]),split[3]);context.write(stuidKey,studentValue);}
}
4.StudentReduce类
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;public class StudentReduce extends ReducerLongWritable, Student, Student, NullWritable {Overrideprotected void reduce(LongWritable key, IterableStudent values, ReducerLongWritable, Student, Student, NullWritable.Context context) throws IOException,InterruptedException {Student stu new Student();// 相同key相加
// int sum 0;int max 0;String name ;String lession ;
// for (Student student:
// values) {
// sum student.getScore();
// name student.getStuname();
// }// 求每门科目的最高分for (Student student :values) {if(maxstudent.getScore()){max student.getScore();name student.getStuname();lession student.getLession();}}stu.setStuid(key.get());stu.setScore(max);stu.setStuname(name);stu.setLession(lession);System.out.println(stu.toString());context.write(stu,NullWritable.get());}
}5.StudentDriver类
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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 StudentDriver {public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {Configuration configuration new Configuration();Job job Job.getInstance(configuration);job.setJarByClass(StudentDriver.class);job.setMapperClass(StudentMapper.class);job.setMapOutputKeyClass(LongWritable.class);job.setMapOutputValueClass(Student.class);job.setReducerClass(StudentReduce.class);job.setOutputKeyClass(Student.class);job.setOutputValueClass(NullWritable.class);// 指定路径FileInputFormat.setInputPaths(job,new Path(hdfs://lxm147:9000/bigdata/in/demo2/stuscore.csv));Path path new Path(hdfs://lxm147:9000/bigdata/out2);// 不指定路径/* Path inpath new Path(args[0]);FileInputFormat.setInputPaths(job, inpath);Path path new Path(args[1]);*/FileSystem fs FileSystem.get(path.toUri(), configuration);if (fs.exists(path)) {fs.delete(path, true);}FileOutputFormat.setOutputPath(job, path);job.waitForCompletion(true);}
}
(二)java代码中指定路径
1.maven项目编译并打包
分别双击compile和package 2.上传stuscore.csv到hdfs指定目录下
hdfs dfs -put /opt/stuscore.csv /bigdata/in/demo2
3.xftp上传target目录下的打包好的jar包上传到虚拟机 4.Hadoop运行hadoopstu-1.0-SNAPSHOT.jar
[rootlxm147 opt]# hadoop jar ./hadoopstu-1.1.0-SNAPSHOT.jar nj.zb.kb21.demo2.StudentDriver /bigdata/in/demo2/stuscore.csv /bigdata/out25.Hadoop运行结果 (三)java代码中不指定路径
1.StuudentDriver类
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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 StudentDriver {public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {Configuration configuration new Configuration();Job job Job.getInstance(configuration);job.setJarByClass(StudentDriver.class);job.setMapperClass(StudentMapper.class);job.setMapOutputKeyClass(LongWritable.class);job.setMapOutputValueClass(Student.class);job.setReducerClass(StudentReduce.class);job.setOutputKeyClass(Student.class);job.setOutputValueClass(NullWritable.class);// 指定路径/*FileInputFormat.setInputPaths(job,new Path(hdfs://lxm147:9000/bigdata/in/demo2/stuscore.csv));Path path new Path(hdfs://lxm147:9000/bigdata/out2);*/// 不指定路径Path inpath new Path(args[0]);FileInputFormat.setInputPaths(job, inpath);Path path new Path(args[1]);FileSystem fs FileSystem.get(path.toUri(), configuration);if (fs.exists(path)) {fs.delete(path, true);}FileOutputFormat.setOutputPath(job, path);job.waitForCompletion(true);}
}
2.重新编译打包上传
为了方便区分这里修改版本号再重新编译打包 3.HDFS命令执行该jar包
[rootlxm147 opt]# hadoop jar ./hadoopstu-1.1.0-SNAPSHOT.jar nj.zb.kb21.demo2.StudentDriver /bigdata/in/demo2/stuscore.csv /bigdata/out4.查看运行结果
[rootlxm147 opt]# hdfs dfs -cat /bigdata/out/part-r-00000
Student{stuid1, stunamezs, score226}
Student{stuid2, stunamels, score348}
Student{stuid3, stunameww, score346}
