林子雨编著《大数据基础编程、实验和案例教程（第2版）》(教材官网)教材中的命令行和代码，在纸质教材中的印刷效果不是很好，可能会影响读者对命令行和代码的理解，为了方便读者正确理解命令行和代码或者直接拷贝命令行和代码用于上机实验，这里提供全书配套的所有命令行和代码。
查看教材所有章节的代码
第7章 MapReduce基础编程
教材第124页
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public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
private static final IntWritable one = new IntWritable(1);
private Text word = new Text();
public TokenizerMapper() {
}
public void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while(itr.hasMoreTokens()) {
this.word.set(itr.nextToken());
context.write(this.word, one);
}
}
}
教材第125页
public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public IntSumReducer() {
}
public void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {
int sum = 0;
IntWritable val;
for(Iterator i$ = values.iterator(); i$.hasNext(); sum += val.get()) {
val = (IntWritable)i$.next();
}
this.result.set(sum);
context.write(key, this.result);
}
}
教材第125页
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = (new GenericOptionsParser(conf, args)).getRemainingArgs();
if(otherArgs.length < 2) {
System.err.println("Usage: wordcount <in> [<in>...] <out>");
System.exit(2);
}
Job job = Job.getInstance(conf, "word count"); //设置环境参数
job.setJarByClass(WordCount.class); //设置整个程序的类名
job.setMapperClass(WordCount.TokenizerMapper.class); //添加Mapper类
job.setReducerClass(WordCount.IntSumReducer.class); //添加Reducer类
job.setOutputKeyClass(Text.class); //设置输出类型
job.setOutputValueClass(IntWritable.class); //设置输出类型
for(int i = 0; i < otherArgs.length - 1; ++i) {
FileInputFormat.addInputPath(job, new Path(otherArgs[i])); //设置输入文件
}
FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));//设置输出文件
System.exit(job.waitForCompletion(true)?0:1);
}
教材第126页
import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;
import org.apache.hadoop.util.GenericOptionsParser;
public class WordCount {
public WordCount() {
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = (new GenericOptionsParser(conf, args)).getRemainingArgs();
if(otherArgs.length < 2) {
System.err.println("Usage: wordcount <in> [<in>...] <out>");
System.exit(2);
}
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(WordCount.TokenizerMapper.class);
job.setCombinerClass(WordCount.IntSumReducer.class);
job.setReducerClass(WordCount.IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
for(int i = 0; i < otherArgs.length - 1; ++i) {
FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
}
FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
System.exit(job.waitForCompletion(true)?0:1);
}
public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
private static final IntWritable one = new IntWritable(1);
private Text word = new Text();
public TokenizerMapper() {
}
public void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while(itr.hasMoreTokens()) {
this.word.set(itr.nextToken());
context.write(this.word, one);
}
}
}
public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public IntSumReducer() {
}
public void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {
int sum = 0;
IntWritable val;
for(Iterator i$ = values.iterator(); i$.hasNext(); sum += val.get()) {
val = (IntWritable)i$.next();
}
this.result.set(sum);
context.write(key, this.result);
}
}
}
教材第128页
cd /usr/local/hadoop
export CLASSPATH="/usr/local/hadoop/share/hadoop/common/hadoop-common-3.1.3.jar:/usr/local/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-client-core-3.1.3.jar:/usr/local/hadoop/share/hadoop/common/lib/commons-cli-1.2.jar:$CLASSPATH"
javac WordCount.java
jar -cvf WordCount.jar *.class
./bin/hadoop jar WordCount.jar WordCount input output
./bin/hadoop fs -cat output/*
教材第135页
cd /usr/local/hadoop/myapp
ls
教材第136页
cd /usr/local/hadoop
./sbin/start-dfs.sh
教材第137页
cd /usr/local/hadoop
./bin/hdfs dfs -rm -r input
./bin/hdfs dfs -rm -r output
cd /usr/local/hadoop
./bin/hdfs dfs -mkdir input
cd /usr/local/hadoop
./bin/hdfs dfs -put ./wordfile1.txt input
./bin/hdfs dfs -put ./wordfile2.txt input
cd /usr/local/hadoop
./bin/hdfs dfs -rm -r /user/hadoop/output
cd /usr/local/hadoop
./bin/hadoop jar ./myapp/WordCount.jar input output
教材第138页
cd /usr/local/hadoop
./bin/hdfs dfs -cat output/*