The imports are from the mapreduce package. Also i use maven for
dependencies and the version of hadoop is 2.7.1
On 09/18/2016 09:11 PM, Dieter De Witte wrote:
Maybe also add the list of imports you are doing, they are different
between different versions of hadoop and mixing them might cause
counterintuitive behaviour...
Kind Regards,
Dieter De Witte
Big Data Scientist
iMinds - Data Science Lab <http://www.datasciencelab.ugent.be/>
Ghent University
2016-09-18 19:54 GMT+02:00 Denis Mone <monede...@gmail.com
<mailto:monede...@gmail.com>>:
Hello and thanks for your time.
What i mean is that i have setup breakpoints in my code in the
map and reduce functions
and the the breakpoint is not activated when the program
starts running (hence the title code does not enter class, which
is not that informative really).
As for the jobs, there is only one, that of kmeans algorithm and
is being executed correctly no exception thrown.
Here
<https://gist.github.com/Denis1990/9f42f73ae126ea47008ee907da64ac6a>
is the output of the job.
The driver class is this
<https://gist.github.com/Denis1990/2978c92567efa17060bb618f66d02ce0>
09/18/2016 02:27 AM, daemeon reiydelle wrote:
What do you mean by "does not enter ... class(es)"?
Does the log show that the scheduler ever accepts the job (You
may have to turn logging up)? Are "other" jobs that are submitted
to the same class under your user scheduled & executed? Wonder
about which scheduler? What is the definition for the scheduler
class? Is it getting to a container? Let's get a complete history
of the steps you are getting please?
***
.......**
Daemeon C.M. Reiydelle
USA (+1) 415.501.0198 <tel:%28%2B1%29%20415.501.0198>
London (+44) (0) 20 8144 9872
<tel:%28%2B44%29%20%280%29%2020%208144%209872>*/
/
On Sat, Sep 17, 2016 at 3:56 AM, Denis Mone <monede...@gmail.com
<mailto:monede...@gmail.com>> wrote:
Hello hadoop users.
I am trying to implement a mapreduce KMeans algorithm
using hadoop. The problem i have is that the code does not
enter the map and reduce class. I'm running the application
from Intellij Idea not using hadoop binary.
The rest of the email is a sample of my code. If someone can
see something that could help that would be greatly appreciated.
Thanks in advance.
Here is my driver code:
Job job = Job.getInstance(conf); job.setJobName("kmeans");
job.setJarByClass(KMeans.class); FileInputFormat.addInputPath(job, input);
FileOutputFormat.setOutputPath(job, output); job.setMapperClass(KMeansMapper.class);
job.setReducerClass(KMeansReducer.class);job.setMapOutputKeyClass(PointVector.class);
job.setMapOutputValueClass(PointVector.class); job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class); job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);job.waitForCompletion(true);
And below are my map and reduce classes:
public class KMeansMapperextends Mapper<LongWritable, Text, PointVector,
PointVector> {
private int clusters; private List<ImmutableTriple<Integer, String,
PointVector>>centers; @Override protected void setup(Context context)throws
IOException, InterruptedException {
System.out.println("Inside setup"); this.clusters =
Integer.valueOf(context.getConfiguration().get("clusters")); this.centers =new ArrayList<>();
BufferedReader br =new BufferedReader(new FileReader("/home/denis/centers")); for(int i =0; i <clusters;
i++) {
centers.add(DocumentRecordParser.parse(br.readLine())); }
br.close(); }
@Override public void map(LongWritable key, Text value, Context
context)throws IOException, InterruptedException {
PointVector line = DocumentRecordParser.returnPointVector(value.toString());
System.out.println("Inside map!"); double minDist = Double.MAX_VALUE; double
dist;PointVector index =null; EuclideanDistance ed =new EuclideanDistance(); for
(ImmutableTriple<Integer, String, PointVector> c :centers) {
dist = ed.compute(line.points(), c.right.points()); if (dist
< minDist) {
minDist = dist; index = c.right; }
}
context.write(index, line); }
}
public class KMeansReducerextends Reducer<PointVector, PointVector, Text,
Text> {
private double min_dist = Double.MAX_VALUE; @Override public void
reduce(PointVector center, Iterable<PointVector> points, Context context)throws
IOException, InterruptedException {
EuclideanDistance measure =new EuclideanDistance(); double
distance =0.0; int numOfPoints =0;double diff =0.0; PointVector newCenter
=null; double [] sums =new double[center.size()]; for (PointVector p : points) {
distance += measure.compute(center.points(), p.points()); if
(distance <min_dist) {
min_dist = distance; newCenter = p; }
numOfPoints++; sums = MathArrays.ebeAdd(p.points(), sums);}
for (int i =0; i < sums.length; i++) {
sums[i] = sums[i] / numOfPoints; }System.out.println("Old center " +
center +" new center: " + newCenter); context.write(new Text(newCenter.toString()), new
Text(new PointVector(sums).toString())); }
}
Last but not least my custom data structure class PointVector
public class PointVectorimplements WritableComparable<PointVector> {
/** * Keep the tfIdf values of the terms of a document */
private Vector<Double>data =new Vector<>(); public PointVector(double
[] values) {
this.data =new Vector<>(values.length);
this.data.addAll(Doubles.asList(values)); }
public PointVector(List<Double> values) {
this.data =new Vector<>(values.size());
this.data.addAll(values); }
public PointVector(String [] values) {
this.data =new Vector<>(values.length); for (String s: values)
{
this.data.add(Double.valueOf(s)); }
}
public PointVector() {
this.data =new Vector<>(); }
public double[]points() {
return Doubles.toArray(data); }
/** * Subtract the values of this vector from the PointVector
passed as argument * @param subtracted * @return */ public
PointVectorsub(PointVector subtracted) {
int N =this.data.size(); double [] vals =new double[N]; for (int
i =0; i < N; i++) {
vals[i] =this.data.get(i) - subtracted.get(i); }
return new PointVector(vals); }
public PointVectoradd(PointVector vec) {
int N =this.data.size(); double [] vals =new double[N]; for (int
i =0; i < N; i++) {
vals[i] =this.data.get(i) + vec.get(i); }
return new PointVector(vals); }
/** * Compute the dot product of this vector with the one
passed as argument * @param vector * @return */ public double
dotProduct(PointVector vector) {
int N =this.data.size(); double sum =0.0; for (int i =0; i <
N; i++) {
sum +=this.data.get(i) * vector.get(i); }
return sum; }
@Override public int compareTo(PointVector pointVector) {
return 0; }
@Override public void write(DataOutput dataOutput)throws
IOException {
dataOutput.writeInt(data.size()); for (double d :data) {
dataOutput.writeDouble(d); }
}
@Override public void readFields(DataInput dataInput)throws
IOException {
int s = dataInput.readInt(); // read the size of the vector }
public Doubleget(int i) {
return this.data.get(i); }
public int size() {
return this.data.size(); }
@Override public StringtoString() {
if (data.isEmpty()) {
return "[]"; }
StringBuilder sb =new StringBuilder(); sb.append("["); for
(double d :data) {
sb.append(d); sb.append(", "); }
final int pos = sb.lastIndexOf(","); sb.delete(pos, pos +1);
sb.append("]"); return sb.toString(); }
}
