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  • Hadoop学习笔记——WordCount

    1.在IDEA下新建工程,选择from Mevan

    GroupId:WordCount

    ArtifactId:com.hadoop.1st

    Project name:WordCount

    2.pom.xml文件

    <?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0"
             xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
             xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
        <modelVersion>4.0.0</modelVersion>
    
        <groupId>WordCount</groupId>
        <artifactId>com.hadoop.1st</artifactId>
        <version>1.0-SNAPSHOT</version>
    
        <repositories>
            <repository>
                <id>apache</id>
                <url>http://maven.apache.org</url>
            </repository>
        </repositories>
    
        <dependencies>
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-core</artifactId>
                <version>1.2.1</version>
            </dependency>
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-common</artifactId>
                <version>2.7.1</version>
            </dependency>
        </dependencies>
    
        <build>
            <plugins>
                <plugin>
                    <artifactId>maven-dependency-plugin</artifactId>
                    <configuration>
                        <excludeTransitive>false</excludeTransitive>
                        <stripVersion>true</stripVersion>
                        <outputDirectory>./lib</outputDirectory>
                    </configuration>
    
                </plugin>
            </plugins>
        </build>
    </project>
    

     3.main/java目录下新建WordCount.java文件

    import org.apache.hadoop.conf.Configuration;
    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.Mapper;
    import org.apache.hadoop.mapreduce.Reducer;
    import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
    import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
    import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
    import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
    
    import java.io.IOException;
    import java.util.StringTokenizer;
    
    
    /**
     * Created by common on 17-3-26.
     */
    public class WordCount {
        public static class WordCountMap extends
                Mapper<LongWritable, Text, Text, IntWritable> {
    
            private final IntWritable one = new IntWritable(1);
            private Text word = new Text();
    
            public void map(LongWritable key, Text value, Context context)
                    throws IOException, InterruptedException {
                String line = value.toString();
                StringTokenizer token = new StringTokenizer(line);
                while (token.hasMoreTokens()) {
                    word.set(token.nextToken());
                    context.write(word, one);
                }
            }
        }
    
        public static class WordCountReduce extends
                Reducer<Text, IntWritable, Text, IntWritable> {
    
            public void reduce(Text key, Iterable<IntWritable> values,
                               Context context) throws IOException, InterruptedException {
                int sum = 0;
                for (IntWritable val : values) {
                    sum += val.get();
                }
                context.write(key, new IntWritable(sum));
            }
        }
    
        public static void main(String[] args) throws Exception {
            Configuration conf = new Configuration();
            Job job = new Job(conf);
            job.setJarByClass(WordCount.class);
            job.setJobName("wordcount");
    
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(IntWritable.class);
    
            job.setMapperClass(WordCountMap.class);
            job.setReducerClass(WordCountReduce.class);
    
            job.setInputFormatClass(TextInputFormat.class);
            job.setOutputFormatClass(TextOutputFormat.class);
    
            FileInputFormat.addInputPath(job, new Path(args[0]));
            FileOutputFormat.setOutputPath(job, new Path(args[1]));
    
            job.waitForCompletion(true);
        }
    }
    

     4.在src同级目录下新建input目录,以及下面的test.segmented文件

    test.segmented文件内容

    aa
    bb
    cc
    dd
    aa
    cc
    ee
    ff
    ff
    gg
    hh
    aa
    

    4.在run configuration下设置运行方式为Application

    5.运行java文件,将会生成output目录,part-r-00000为运行的结果,下次运行必须删除output目录,否则会报错

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  • 原文地址:https://www.cnblogs.com/tonglin0325/p/6623566.html
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