首先，我是Hadoop MapReduce的新手。我的化简器未运行，但显示作业已成功完成。以下是我的控制台输出：
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- 信息地图减少。作业：正在运行 作业：job_1418240815217_0015
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- 信息地图减少。作业：在优步模式下运行的作业job_1418240815217_0015：假
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- 信息地图减少。作业：映射 0% 减少 0%
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- 信息地图减少。作业：映射 100% 减少 0%
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- 信息地图减少。作业：作业job_1418240815217_0015成功完成
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- 信息地图减少。职位：计数器：30
主要类是：
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
@SuppressWarnings("deprecation")
Job job = new Job(conf,"NPhase2");
job.setJarByClass(NPhase2.class);
job.setMapOutputKeyClass(IntWritable.class);
job.setMapOutputValueClass(NPhase2Value.class);
job.setOutputKeyClass(NullWritable.class);
job.setOutputValueClass(Text.class);
job.setMapperClass(MapClass.class);
job.setReducerClass(Reduce.class);
int numberOfPartition = 0;
List<String> other_args = new ArrayList<String>();
for(int i = 0; i < args.length; ++i)
{
try {
if ("-m".equals(args[i])) {
//conf.setNumMapTasks(Integer.parseInt(args[++i]));
++i;
} else if ("-r".equals(args[i])) {
job.setNumReduceTasks(Integer.parseInt(args[++i]));
} else if ("-k".equals(args[i])) {
int knn = Integer.parseInt(args[++i]);
conf.setInt("knn", knn);
System.out.println(knn);
} else {
other_args.add(args[i]);
}
job.setNumReduceTasks(numberOfPartition * numberOfPartition);
//conf.setNumReduceTasks(1);
} catch (NumberFormatException except) {
System.out.println("ERROR: Integer expected instead of " + args[i]);
} catch (ArrayIndexOutOfBoundsException except) {
System.out.println("ERROR: Required parameter missing from " + args[i-1]);
}
}
// Make sure there are exactly 2 parameters left.
if (other_args.size() != 2) {
System.out.println("ERROR: Wrong number of parameters: " +
other_args.size() + " instead of 2.");
}
FileInputFormat.setInputPaths(job, other_args.get(0));
FileOutputFormat.setOutputPath(job, new Path(other_args.get(1)));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
我的映射器是：
公共静态类 MapClass 扩展映射器 {
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException
{
String line = value.toString();
String[] parts = line.split("\s+");
// key format <rid1>
IntWritable mapKey = new IntWritable(Integer.valueOf(parts[0]));
// value format <rid2, dist>
NPhase2Value np2v = new NPhase2Value(Integer.valueOf(parts[1]), Float.valueOf(parts[2]));
context.write(mapKey, np2v);
}
}
我的减速器类是：
public static class Reduce extends Reducer<IntWritable, NPhase2Value, NullWritable, Text>
{
int numberOfPartition;
int knn;
class Record
{
public int id2;
public float dist;
Record(int id2, float dist)
{
this.id2 = id2;
this.dist = dist;
}
public String toString()
{
return Integer.toString(id2) + " " + Float.toString(dist);
}
}
class RecordComparator implements Comparator<Record>
{
public int compare(Record o1, Record o2)
{
int ret = 0;
float dist = o1.dist - o2.dist;
if (Math.abs(dist) < 1E-6)
ret = o1.id2 - o2.id2;
else if (dist > 0)
ret = 1;
else
ret = -1;
return -ret;
}
}
public void setup(Context context)
{
Configuration conf = new Configuration();
conf = context.getConfiguration();
numberOfPartition = conf.getInt("numberOfPartition", 2);
knn = conf.getInt("knn", 3);
}
public void reduce(IntWritable key, Iterator<NPhase2Value> values, Context context) throws IOException, InterruptedException
{
//initialize the pq
RecordComparator rc = new RecordComparator();
PriorityQueue<Record> pq = new PriorityQueue<Record>(knn + 1, rc);
// For each record we have a reduce task
// value format <rid1, rid2, dist>
while (values.hasNext())
{
NPhase2Value np2v = values.next();
int id2 = np2v.getFirst().get();
float dist = np2v.getSecond().get();
Record record = new Record(id2, dist);
pq.add(record);
if (pq.size() > knn)
pq.poll();
}
while(pq.size() > 0)
{
context.write(NullWritable.get(), new Text(key.toString() + " " + pq.poll().toString()));
//break; // only ouput the first record
}
} // reduce
}
这是我的助手类：
公共类 NPhase2Value 实现 WritableComparable {
private IntWritable first;
private FloatWritable second;
public NPhase2Value() {
set(new IntWritable(), new FloatWritable());
}
public NPhase2Value(int first, float second) {
set(new IntWritable(first), new FloatWritable(second));
}
public void set(IntWritable first, FloatWritable second) {
this.first = first;
this.second = second;
}
public IntWritable getFirst() {
return first;
}
public FloatWritable getSecond() {
return second;
}
@Override
public void write(DataOutput out) throws IOException {
first.write(out);
second.write(out);
}
@Override
public void readFields(DataInput in) throws IOException {
first.readFields(in);
second.readFields(in);
}
@Override
public boolean equals(Object o) {
if (o instanceof NPhase2Value) {
NPhase2Value np2v = (NPhase2Value) o;
return first.equals(np2v.first) && second.equals(np2v.second);
}
return false;
}
@Override
public String toString() {
return first.toString() + " " + second.toString();
}
@Override
public int compareTo(NPhase2Value np2v) {
return 1;
}
}
我使用的命令行命令是：
hadoop jar knn.jar NPhase2 -m 1 -r 3 -k 4 phase1out phase2out
我正在努力找出错误，但仍然无法提出解决方案。请在这方面帮助我，因为我的日程安排很紧。
因为您已将化简器任务的数量设置为 0。看到这个：
int numberOfPartition = 0;
//.......
job.setNumReduceTasks(numberOfPartition * numberOfPartition);
我没有看到您在代码中的任何地方重置了numberOfPartition。我精简了您应该在解析 -r 选项的位置设置它，或者完全删除对 setNumReduceTasks 方法的调用，因为您在解析 -r 选项时已经设置了它。