我有一个如下格式的输入文件。
input.txt
1, 1 2
2, 1 3
3, 2 3
4, 1 4
上面的输入文件有一个键,它是行号和作为无向图的图边的值。例如,对于第一条记录,行号是1,边在1和2之间。在映射逻辑中,我必须找到哪个垂直线的阶数较低。我该怎么办?请帮助我,因为我是Hadoop地图减少的新手。
为了识别图中阶数最低的顶点,我们有两个实现两个作业。这被称为Hadoop MapReduce编程中的链接作业
作业1
作业一将计算每个顶点的度数。Reducer会将输出保存到HDFS文件夹中。
作业2
作业2将读取作业1的输出作为输入,并找到度数最低的顶点。
请在下面找到用JAVA编写的详细代码。程序的参数是输入文本文件和输出文件
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.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.output.FileOutputFormat;
public class LowestDegreeOfGraph {
public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
@Override
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
Text word = new Text();
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
public static class MapForFindingLowDegree extends Mapper<LongWritable, Text, Text, Text> {
@Override
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
Text word = new Text();
String[] line = value.toString().split("t");
context.write(new Text("vertexWithLowestDegree"), new Text(line[0]+","+line[1]));
}
}
public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {
@Override
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
context.write(key, new IntWritable(sum));
}
}
public static class ReduceForFindingLowDegree extends Reducer<Text, Text, Text, Text> {
@Override
public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
int flag = 0;
int vertex=0;
int degree=0;
for (Text value : values) {
String[] line=value.toString().split(",");
if(flag==0){
vertex=Integer.parseInt(line[0]);
degree=Integer.parseInt(line[1]);
flag=1;
}else if(degree>Integer.parseInt(line[1])){
vertex=Integer.parseInt(line[0]);
degree=Integer.parseInt(line[1]);
}
}
context.write(new Text("Vertex with the lowest degree "+vertex),new Text("Degree "+degree));
}
}
public static void main(String[] args) throws Exception {
Configuration conf=new Configuration();
conf.set("fs.default.name", "hdfs://localhost:8020");
Job job = new Job(conf);
job.setJarByClass(LowestDegreeOfGraph.class);
job.setJobName("For calculating the degree for every vertex");
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path("/opt/"));
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.waitForCompletion(true);
Job job2 = new Job(conf);
job2.setJarByClass(LowestDegreeOfGraph.class);
job2.setJobName("Identifying the Vertex with lowest degree");
FileInputFormat.addInputPath(job2, new Path("/opt/"));
FileOutputFormat.setOutputPath(job2, new Path((args[1])));
job2.setMapperClass(MapForFindingLowDegree.class);
job2.setReducerClass(ReduceForFindingLowDegree.class);
job2.setOutputKeyClass(Text.class);
job2.setOutputValueClass(Text.class);
job2.waitForCompletion(true);
}
}
arg[0]是输入文件。PFB样本输入文件。示例输入文件1 21 32 31 4
arg[1]是输出文件的位置。
请在运行作业时提供arg[0]和arg[1]。
/opt是用于存储临时数据的临时位置。