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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;// Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>
// <0,"hello world","hello",1>
public class WordCountMapper extends Mapper<LongWritable, Text,Text, IntWritable> {Text text = new Text();IntWritable intWritable = new IntWritable();@Overrideprotected void map(LongWritable key, Text value, Mapper<LongWritable, 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,1><world,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 Reducer<Text, IntWritable,Text, LongWritable> {@Overrideprotected void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, 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
[root@lxm147 ~]# 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
[root@lxm147 ~]# 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 /inputpath2.新建一个文件，并上传至该目录下
[root@lxm147 mapreduce]# vim ./test.csv
[root@lxm147 mapreduce]# hdfs dfs -put ./test.csv /inputpath
3.执行wordcount命令
[root@lxm147 mapreduce]# hadoop jar ./hadoop-mapreduce-examples-3.1.3.jar wordcount /inputpath /outputpath
4.查看运行结果
(1)web端
(2)命令行
[root@lxm147 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 15.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)
[root@lxm148 ~]# 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.
[root@lxm148 ~]# jps
4546 SecondaryNameNode
6370 JobHistoryServer
4164 NameNode
4804 ResourceManager
4937 NodeManager
6393 Jps
4302 DataNode
8.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 WritableComparable<Student> {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;// K=id,V=student
// Mapper<进来的K,进来的V,出去的K,出去的V>
public class StudentMapper extends Mapper<LongWritable, Text, LongWritable, Student> {@Overrideprotected void map(LongWritable key, Text value, Mapper<LongWritable, 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 Reducer<LongWritable, Student, Student, NullWritable> {@Overrideprotected void reduce(LongWritable key, Iterable<Student> values, Reducer<LongWritable, 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(max<=student.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/demo23.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
[root@lxm147 opt]# hadoop jar ./hadoopstu-1.1.0-SNAPSHOT.jar nj.zb.kb21.demo2.StudentDriver /bigdata/in/demo2/stuscore.csv /bigdata/out2
5.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
[root@lxm147 opt]# hadoop jar ./hadoopstu-1.1.0-SNAPSHOT.jar nj.zb.kb21.demo2.StudentDriver /bigdata/in/demo2/stuscore.csv /bigdata/out
4.查看运行结果
[root@lxm147 opt]# hdfs dfs -cat /bigdata/out/part-r-00000
Student{stuid=1, stuname='zs', score=226}
Student{stuid=2, stuname='ls', score=348}
Student{stuid=3, stuname='ww', score=346}