Hadoop 打包和运行 MapReduce 程序

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主要内容:将 MapReduce 代码通过命令行打包成 jar 包,然后提交给 Hadoop 集群运行。示例的 WordCount.java、WordCount.txt 见最后面。

一、编译 Hadoop 的应用程序需要将所需的依赖包添加到 CLASSPATH,可以添加到 .bashrc 或者 /etc/profile。

# javac 编译相关包依赖
HADOOP_CLASSPATH=$($HADOOP_HOME/bin/hadoop classpath)
# 将 HADOOP_CLASSPATH 添加到 CLASSPATH
export CLASSPATH=.:$HADOOP_CLASSPATH:$CLASSPATH
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二、编译源代码

# 编译 没有设置 CLASSPATH 通过 -cp $($HADOOP_HOME/bin/hadoop classpath)
javac WordCount.java
# 打包
jar -cvf WordCount.jar  *.class
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三、提交到 Hadoop

# 上传 WordCount.txt 到 Hadoop
hdfs dfs -mkdir input
hdfs dfs -put WordCount.txt input
# 提交任务 jar 包、main 所在的类、输入文件夹、输出文件夹
hadoop jar WordCount.jar WordCount input output
# 查看运行结果
hdfs dfs -cat output/*
# 删除输出结果目录
hdfs dfs -rm -r output
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四、运行结果

and	1
bigdata	2
hadoop	2
hello	4
world	1
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附录:

WordCount.txt,单词使用空格分隔

hello world
hello hadoop
hello bigdata
hello hadoop  and bigdata
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WordCount.java

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.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;

public class WordCount {

    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
        private final static IntWritable ONE = new IntWritable(1);
        private final Text word = new Text();

        @Override
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                context.write(word, ONE);
            }
        }
    }

    public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
        private final IntWritable result = new IntWritable();

        @Override
        public void reduce(Text key, Iterable<IntWritable> values, Context context)
                throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "WordCount");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}
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