大数据：Hadoop入门经典案例wordcount单词统计Java代码实现

痛定思痛。 2024-02-19 22:00 68阅读 0赞

## 大数据：Hadoop入门经典案例wordcount单词统计Java代码实现，Windows 10环境，IntelliJ IDEA集成开发环境。 ##

附1通过命令行形式实现大数据平台Hadoop下单词统计功能。现在通过自己编写Java代码实现。本例基于Hadoop 2.8.3，Windows 10（64位）。开发环境是Windows下的IntelliJ IDEA。

1，首先需要为IntelliJ IDEA增加maven依赖，在项目的pom.xml中添加以下Hadoop开发需要的依赖包，然后同步：

<dependencies>
    
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-common</artifactId>
                <version>2.8.3</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-client</artifactId>
                <version>2.8.3</version>
            </dependency>
    
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-hdfs</artifactId>
                <version>2.8.3</version>
            </dependency>
    
        </dependencies>

2，编写单词统计的Java代码。

主类WordCountMain.java：

import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    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;
    
    public class WordCountMain {
        public WordCountMain(String[] args) throws Exception {
            Configuration configuration = new Configuration();
    
            Job job = Job.getInstance(configuration, "word_count");
    
            job.setJarByClass(WordCountMain.class);
    
            job.setMapperClass(MyMapper.class);
            job.setReducerClass(MyReducer.class);
    
            job.setMapOutputKeyClass(Text.class);
            job.setOutputValueClass(LongWritable.class);
            job.setOutputKeyClass(Text.class);
    
            FileInputFormat.setInputPaths(job, new Path(args[0]));
            FileOutputFormat.setOutputPath(job, new Path(args[1]));
    
            System.out.println(job.waitForCompletion(true) ? "运行成功" : "运行失败");
        }
    
        public static void main(String[] args) {
            try {
                WordCountMain wordCountMain = new WordCountMain(args);
            } catch (Exception e) {
                e.printStackTrace();
            }
        }
    }

map类：

import org.apache.hadoop.io.LongWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Mapper;
    
    public  class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable> {
        @Override
        protected void map(LongWritable key, Text value, Context context) {
            String line = value.toString();
    
            String[] words = line.split(" ");
    
            for (String word : words) {
                // 将单词作为key，将次数1作为value。
                try {
                    context.write(new Text(word), new LongWritable(1));
                } catch (Exception e) {
                    e.printStackTrace();
                }
            }
        }
    }

reducer类：

import org.apache.hadoop.io.LongWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Reducer;
    
    public class MyReducer extends Reducer<Text, LongWritable, Text, LongWritable> {
        @Override
        protected void reduce(Text key, Iterable<LongWritable> values, Context context) {
            int count = 0;
    
            for (LongWritable value : values) {
                count += value.get();
            }
    
            try {
                context.write(key, new LongWritable(count));
            } catch (Exception e) {
                e.printStackTrace();
            }
        }
    }

3，在IntelliJ IDEA中直接导出可运行的Java的jar包（具体方法见文章 [https://zhangphil.blog.csdn.net/article/details/99434450][https_zhangphil.blog.csdn.net_article_details_99434450]），注意，在Hadoop2.8.3，Windows 10,64位环境下，编译出的jar包里面有两个文件夹：META-INF和license，如果直接运行将导致失败。需要用解压缩工具打开这个jar包，删掉META-INF和license这两个文件夹，如图：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly96aGFuZ3BoaWwuYmxvZy5jc2RuLm5ldA_size_16_color_FFFFFF_t_70][]

如果不删除这两个文件夹，在jar包运行时候，会抛出错误导致运行失败。

4，通过start-all命令，启动Hadoop，如附录1中那样。只不过这次使用的jar包不是Hadoop示例代码中的jar包，而是我自己编写的Java代码：

hadoop jar E:/code/IdeaProjects/bigdata/out/artifacts/bigdata_jar/bigdata_jar.jar  WordCountMain /test_dir/myfile  /test_dir/result

bigdata\_jar.jar包就是上面Java代码在第三步IntelliJ IDEA中生成的jar包。

运行后输出的结果和附1相同。

附：

1、命令行方式使用Hadoop自带的word count单词统计jar包统计字符单词数

[https://zhangphil.blog.csdn.net/article/details/98982399][https_zhangphil.blog.csdn.net_article_details_98982399]

[https_zhangphil.blog.csdn.net_article_details_99434450]: https://zhangphil.blog.csdn.net/article/details/99434450
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly96aGFuZ3BoaWwuYmxvZy5jc2RuLm5ldA_size_16_color_FFFFFF_t_70]: https://image.dandelioncloud.cn/pgy_files/images/2024/01/29/03feb55cb0b645879be9e1e67297679b.png
[https_zhangphil.blog.csdn.net_article_details_98982399]: https://zhangphil.blog.csdn.net/article/details/98982399