Example usage for org.apache.mahout.math.hadoop DistributedRowMatrix iterateAll

Introduction

In this page you can find the example usage for org.apache.mahout.math.hadoop DistributedRowMatrix iterateAll.

Prototype

@Override
    public Iterator<MatrixSlice> iterateAll() 

Source Link

Usage

From source file:com.twitter.algebra.AlgebraCommon.java

License:Apache License

/***
 * If the MapDir matrix is small, we can convert it to an in memory representation
 * and then run efficient centralized operations
 * //from w w  w  .j  a  v a 2  s  . com
 * @param origMtx in MapDir format (generated by MatrixOutputFormat)
 * @return a dense matrix including the data
 * @throws IOException 
 */
public static DenseMatrix toDenseMatrix(DistributedRowMatrix origMtx) throws IOException {
    MapDir mapDir = new MapDir(new Configuration(), origMtx.getRowPath());
    DenseMatrix mtx = new DenseMatrix(origMtx.numRows(), origMtx.numCols());
    Iterator<MatrixSlice> sliceIterator;
    try {
        sliceIterator = mapDir.iterateAll();
    } catch (Exception e) {
        log.info(e.toString());
        log.info("Input is not in matrix format, trying SequenceFileFormat instead ...");
        sliceIterator = origMtx.iterateAll();
    }
    while (sliceIterator.hasNext()) {
        MatrixSlice slice = sliceIterator.next();
        //      int r = slice.index();
        //      for (int c = 0; c < mtx.numCols(); c++) {
        //        mtx.set(r, c, slice.get(c));
        //      }
        mtx.viewRow(slice.index()).assign(slice.vector());
    }
    mapDir.close();
    return mtx;
}

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From source file:com.twitter.algebra.matrix.format.MapDir.java

License:Apache License

public static void testIterator(DistributedRowMatrix origMtx, Path inPath) throws IOException {
    Configuration conf = new Configuration();
    MapDir mapDir = new MapDir(conf, inPath);

    Iterator<MatrixSlice> sliceIterator = origMtx.iterateAll();
    while (sliceIterator.hasNext()) {
        MatrixSlice slice = sliceIterator.next();
        int index = slice.index();
        System.out.println("A[" + index + "] = " + slice.vector());

        IntWritable key = new IntWritable(index);
        VectorWritable vw = new VectorWritable();
        vw = mapDir.get(key, vw);/*from w w  w. jav a2 s .c o m*/
        System.out.println("B[" + index + "] = " + vw);
    }
    mapDir.close();
}

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From source file:org.qcri.pca.PCACommon.java

/***
 * If the matrix is small, we can convert it to an in memory representation
 * and then run efficient centralized operations
 * /*from w  w  w. j  av  a  2 s  .c om*/
 * @param origMtx
 * @return a dense matrix including the data
 */
static DenseMatrix toDenseMatrix(DistributedRowMatrix origMtx) {
    DenseMatrix mtx = new DenseMatrix(origMtx.numRows(), origMtx.numCols());
    Iterator<MatrixSlice> sliceIterator = origMtx.iterateAll();
    while (sliceIterator.hasNext()) {
        MatrixSlice slice = sliceIterator.next();
        mtx.viewRow(slice.index()).assign(slice.vector());
    }
    return mtx;
}

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