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折腾了半天。终于编写成功了第一个自己的mapreduce程序,并通过打jar包的方式运行起来了。
运行环境:
windows 64bit
eclipse 64bit
jdk6.0 64bit
1、新建java project
2、导入jar包
新建一个user library 把hadoop文件夹里的hadoop-core和lib包里的所有包都导入进来,以免出错。
1、主要是计算单词的小程序,测试用
package com.hirra; 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; import org.apache.hadoop.util.GenericOptionsParser; public class WordCount { //嵌套类 Mapper //Mapper<keyin,valuein,keyout,valueout> public static class WordCountMapper extends Mapper<Object, Text, Text, IntWritable>{ private final static IntWritable one = new IntWritable(1); private Text word = new Text(); @Override protected 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);//Context机制 } } } //嵌套类Reducer //Reduce<keyin,valuein,keyout,valueout> //Reducer的valuein类型要和Mapper的va lueout类型一致,Reducer的valuein是Mapper的valueout经过shuffle之后的值 public static class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable>{ private IntWritable result = new IntWritable(); @Override protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; for(IntWritable i:values){ sum += i.get(); } result.set(sum); context.write(key,result);//Context机制 } } public static void main(String[] args) throws Exception{ Configuration conf = new Configuration();//获得Configuration配置 Configuration: core-default.xml, core-site.xml
//很关键
conf.set("mapred.job.tracker", "hadoopmaster:9001"); String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();//获得输入参数[hdfs://localhost:9000/user/dat/input, hdfs://localhost:9000/user/dat/output] if(otherArgs.length != 2){//判断输入参数个数,不为两个异常退出 System.err.println("Usage:wordcount <in> <out>"); System.exit(2); } ////设置Job属性 Job job = new Job(conf,"word count"); job.setJarByClass(WordCount.class); job.setMapperClass(WordCountMapper.class); job.setCombinerClass(WordCountReducer.class);//将结果进行局部合并 job.setReducerClass(WordCountReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); FileInputFormat.addInputPath(job, new Path(otherArgs[0]));//传入input path FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));//传入output path,输出路径应该为空,否则报错org.apache.hadoop.mapred.FileAlreadyExistsException。 System.exit(job.waitForCompletion(true)?0:1);//是否正常退出 } }
2、注意问题
有些jar包没导入会出现问题
三、生成jar包
1、eclipse自带功能export jar包
四、运行
1、ssh client工具导入至linux
2、hadoop运行,转到hadoop的bin目录下,执行下面指令:
./hadoop jar test.jar /README.txt /usr/dat/output
3、注意问题
output目录必须是之前不存在的路径。
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原文地址:http://www.cnblogs.com/longshiyVip/p/4805735.html