
Idea 开发Mapreduce遇到的问题,代码不能自动实现方法!搞了很久没搞出来,哪位大牛知道这个?
包跟库都导入了,别的项目都能运行,就maven项目开发mapreduce的时候,代码不能给补齐,不能自动实现方法跟抛异常!下面是截图:...
包跟库都导入了,别的项目都能运行,就maven项目开发mapreduce的时候,代码不能给补齐,不能自动实现方法跟抛异常!下面是截图:
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项目配置 File ---- Project Structure
1. SDK的配置
2. 加入Hadoop的jar包依赖
3.打包配置
4.开发map-reduce代码
<span style="font-size:18px;">import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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 Dedup {
//map将输入中的value复制到输出数据的key上,并直接输出
public static class Map extends Mapper<Object,Text,Text,Text>{
private static Text line=new Text();//每行数据
//实现map函数
public void map(Object key,Text value,Context context)
throws IOException,InterruptedException{
line=value;
context.write(line, new Text(""));
}
}
//reduce将输入中的key复制到输出数据的key上,并直接输出
public static class Reduce extends Reducer<Text,Text,Text,Text>{
//实现reduce函数
public void reduce(Text key,Iterable<Text> values,Context context)
throws IOException,InterruptedException{
context.write(key, new Text(""));
}
}
public static void main(String[] args) throws Exception{
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
Job job = new Job(conf, "Data Deduplication");
job.setJarByClass(Dedup.class);
//设置Map、Combine和Reduce处理类
job.setMapperClass(Map.class);
job.setCombinerClass(Reduce.class);
job.setReducerClass(Reduce.class);
//设置输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//设置输入和输出目录
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputForwww.cdxcxgs.com#tOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}</span>
5.配置编译器
1. SDK的配置
2. 加入Hadoop的jar包依赖
3.打包配置
4.开发map-reduce代码
<span style="font-size:18px;">import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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 Dedup {
//map将输入中的value复制到输出数据的key上,并直接输出
public static class Map extends Mapper<Object,Text,Text,Text>{
private static Text line=new Text();//每行数据
//实现map函数
public void map(Object key,Text value,Context context)
throws IOException,InterruptedException{
line=value;
context.write(line, new Text(""));
}
}
//reduce将输入中的key复制到输出数据的key上,并直接输出
public static class Reduce extends Reducer<Text,Text,Text,Text>{
//实现reduce函数
public void reduce(Text key,Iterable<Text> values,Context context)
throws IOException,InterruptedException{
context.write(key, new Text(""));
}
}
public static void main(String[] args) throws Exception{
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
Job job = new Job(conf, "Data Deduplication");
job.setJarByClass(Dedup.class);
//设置Map、Combine和Reduce处理类
job.setMapperClass(Map.class);
job.setCombinerClass(Reduce.class);
job.setReducerClass(Reduce.class);
//设置输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//设置输入和输出目录
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputForwww.cdxcxgs.com#tOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}</span>
5.配置编译器
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