使用idea开发第一个hadoop程序:WordCount
一,打开idea,建立maven程序
二,添加基础依赖(pom.xml)
maven依赖版本查询网址:
<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>2.7.2</version> </dependency> </dependencies>
三,编写主程序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 Text word = new Text(); 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 IntWritable result = new IntWritable(); 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, "word count"); 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); } }
四,在src同级增加input文件夹,并添加多个文件,文件名不限(本例中文件为:001,002,)
文件中内容:adu hello等随便一些单词
五,配置运行参数:
在idea菜单栏中选择Run->Edit Configurations,在弹出来的对话框中点击+,新建一个Application配置。配置Main class 为 WordCount(可以点击右边的...选择)
program arguments为: input/ output/
只修改main class和program arguments两个参数即可
六,点击run运行,会生成output文件夹,与input同级(包含四个文件)
结果保存在part-r-00000文件中
hadoop权威指南中数据集链接