我在没有使用Tool的情况下编写了用于单机群集的mapreduce java代码,它可以在多节点集群上工作还是我必须进行更改? 以下代码将字符串标记为字符并计算每个文本文件的术语频率
public class tr
{
public static class Map extends MapReduceBase implements Mapper<LongWritable, Text,Text,IntWritable>
{
Text word=new Text();
IntWritable one=new IntWritable(1);
String imptoken;
public static List<String> stopwords=new ArrayList<String>();
public void map(LongWritable key,Text value,OutputCollector<Text,IntWritable> output,Reporter reporter) throws IOException
{
addwords();
String line=value.toString();
line=line.replaceAll("[^A-Za-z]"," ").toLowerCase();
StringTokenizer st=new StringTokenizer(line);
while(st.hasMoreTokens())
{
imptoken=st.nextToken();
if(stopwords.contains(imptoken))
{
}
else
{
word.set(imptoken);
output.collect(word, one);
}
}
}
public void addwords() throws IOException
{
FileSystem fs = FileSystem.get(new Configuration());
Path stop=new Path("/user/hduser/stopword.txt");
BufferedReader br=new BufferedReader(new InputStreamReader(fs.open(stop)));
String stopword=br.readLine();
while(stopword!=null)
{
stopwords.add(stopword);
stopword=br.readLine();
}
}
}
public static class Reduce extends MapReduceBase implements Reducer<Text,IntWritable, Text, IntWritable>
{
public void reduce(Text key,Iterator<IntWritable> value,OutputCollector<Text,IntWritable> output,Reporter reporter) throws IOException
{
int sum=0;
while(value.hasNext())
{
sum=sum+value.next().get();
}
/* Path paths=new Path("/user/hduser/input1/");
FileSystem fs=FileSystem.get(new Configuration());
FileStatus[] status = fs.listStatus(paths);
Path[] list = FileUtil.stat2Paths(status);
String keystr=key.toString();
for(Path file : list)
{
BufferedReader br=new BufferedReader(new InputStreamReader(fs.open(file)));
String word=br.readLine();
while(word!=null)
{
if(word.equals(keystr))
{
sum=0;
}
word=br.readLine();
}
}*/
output.collect(key, new IntWritable(sum));
}
}
public static void main(String args[]) throws IOException
{
FileSystem fs = FileSystem.get(new Configuration());
Path[] paths = new Path[args.length];
for (int i = 0; i < paths.length; i++)
{
paths[i] = new Path(args[i]);
}
FileStatus[] status = fs.listStatus(paths);
Path[] listedPaths = FileUtil.stat2Paths(status);
FSDataInputStream in = null;
for (Path p : listedPaths)
{
JobConf conf = new JobConf(tr.class);
conf.setJobName("tr");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Map.class);
conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
String name=p.getName();
String absolutepath=p.getParent().toString()+"/"+name;
FileInputFormat.setInputPaths(conf, new Path(absolutepath));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
Path local=new Path("/home/hduser/meproj/projectfiles/");
Path source=new Path(args[1]+"/"+"part-00000");
fs.copyToLocalFile(source, local);
File file=new File("/home/hduser/meproj/projectfiles/part-00000");
file.renameTo(new File("/home/hduser/meproj/projectfiles/"+name));
fs.delete(new Path(args[1]), true);
}
}
}
答案 0 :(得分:1)
当您使用Hadoop编写程序时,它将适用于所有群集设置,除非您专门做一些事情来破解它,例如在一台计算机上处理本地文件。
您正在以独立于设置的方式(您应该这样做)在Mapper和Reducer中完成工作,因此它应该可以在任何地方使用。
这与您的问题无关,但您不应该循环文件并在每条路径上运行独立的Jobs。真的,你应该在所有这些上运行一个Job。您可以将所有这些单独的路径放在同一文件夹中,并将该文件夹指定为输入。或者您可以在多个路径上运行hadoop(请参阅此answer)