大数据实验hadoop--通过编程实现词频统计并导出jar在终端运行

创建词文件夹

mkdir wordcount

进入文件夹
创建两个词文档

vim word1.txt
vim word2.txt

打开eclipse编写程序

1.导入需要的jar

导入此路径下所有jar（下同）

2.创建package

3.创建class

编写代码

代码如下：

package wordcount1;
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 WordCount1 {
    public WordCount1() {
    }
     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(WordCount1.class);
        job.setMapperClass(WordCount1.TokenizerMapper.class);
        job.setCombinerClass(WordCount1.IntSumReducer.class);
        job.setReducerClass(WordCount1.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() {
        }
        @SuppressWarnings("rawtypes")
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);
        }
    }
}

运行结果

导出jar

打开hadoop

运行hadoop

cd /usr/local/hadoop
./sbin/start-dfs.sh

在hdfs文件系统上创建input1文件夹

hdfs dfs -mkdir /user/hadoop/input1

将word1、word2上传到所创建的input1中

hdfs dfs -put ~/wordcount/word1.txt /user/hadoop/input1
hdfs dfs -put ~/wordcount/word2.txt /user/hadoop/input1

运行词频统计的jar

hadoop jar ~/wordcount/WordCount1.jar /user/hadoop/input1 /user/hadoop/output1

通过终端命令列出output1目录下的词频统计结果

hdfs dfs -cat /user/hadoop/output1/*

到此我们的目的得到实现，关闭hadoop

./sbin/stop-dfs.sh

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