[jira] Updated: (HAMA-94) Implementation of cholesky decomposition

["Edward J. Yoon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HAMA-94?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Edward J. Yoon updated HAMA-94:
-------------------------------

        Fix Version/s:     (was: 0.2.0)
    Affects Version/s:     (was: 0.2.0)

change the effect version

> Implementation of cholesky decomposition
> ----------------------------------------
>
>                 Key: HAMA-94
>                 URL: https://issues.apache.org/jira/browse/HAMA-94
>             Project: Hama
>          Issue Type: New Feature
>          Components: examples
>            Reporter: Edward J. Yoon
>
> This is my old cholesky decomposition map/reduce code..
> ----
> /**
>  * Copyright 2007 The Apache Software Foundation
>  *
>  * Licensed to the Apache Software Foundation (ASF) under one
>  * or more contributor license agreements.  See the NOTICE file
>  * distributed with this work for additional information
>  * regarding copyright ownership.  The ASF licenses this file
>  * to you under the Apache License, Version 2.0 (the
>  * "License"); you may not use this file except in compliance
>  * with the License.  You may obtain a copy of the License at
>  *
>  *     http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.hama.algebra;
> import java.io.IOException;
> import org.apache.hadoop.hbase.HBaseConfiguration;
> import org.apache.hadoop.hbase.HStoreKey;
> import org.apache.hadoop.io.MapWritable;
> import org.apache.hadoop.io.Text;
> import org.apache.hadoop.mapred.JobConf;
> import org.apache.hadoop.mapred.OutputCollector;
> import org.apache.hadoop.mapred.Reporter;
> import org.apache.hama.FeatureVector;
> import org.apache.hama.Matrix;
> import org.apache.hama.TriangularMatrix;
> import org.apache.hama.mapred.MatrixMap;
> import org.apache.hama.mapred.MatrixOutputFormat;
> /**
>  * Cholesky Decomposition.
>  * <p>
>  * For a symmetric, positive definite matrix A, the Cholesky decomposition is an
>  * lower triangular matrix L so that A = L*L'.
>  * </p>
>  */
> public class CholeskyDecompositionMap extends MatrixMap<Text, MapWritable> {
>   protected Matrix matrix_a;
>   protected TriangularMatrix matrix_l;
>   public static final String MATRIX_A = "cholesky.decomposition.matrix.a";
>   public static final String MATRIX_L = "cholesky.decomposition.matrix.l";
>   public void configure(JobConf job) {
>     HBaseConfiguration conf = new HBaseConfiguration();
>     Text a_name = new Text(job.get(MATRIX_A, ""));
>     Text l_name = new Text(job.get(MATRIX_L, ""));
>     matrix_a = new Matrix(conf, a_name);
>     matrix_l = new TriangularMatrix(conf, l_name);
>   }
>   /**
>    * @param matrix_a
>    * @param matrix_l
>    * @param map
>    * @param jobConf
>    */
>   public static void initJob(String matrix_a, String matrix_l,
>       Class<CholeskyDecompositionMap> map, JobConf jobConf) {
>     initJob(matrix_a, map, jobConf);
>     jobConf.set(MatrixOutputFormat.OUTPUT, matrix_l);
>     jobConf.set(MATRIX_A, matrix_a);
>     jobConf.set(MATRIX_L, matrix_l);
>   }
>   @Override
>   public void map(HStoreKey key, MapWritable value,
>       OutputCollector<Text, MapWritable> output, Reporter reporter)
>       throws IOException {
>     int i = Integer.parseInt(String.valueOf(key.getRow()));
>     double[] ithRowOfL = new double[matrix_a.getRowDimension()];
>     double[] jthRowOfL = new double[matrix_a.getRowDimension()];
>     // Vector was added. I don't figure out the result. -- edward
>     FeatureVector iOfV = matrix_l.getRowVector(i);
>     for(int x = 0; x < iOfV.size(); x++) {
>       ithRowOfL[x] = iOfV.getDimAt(x);
>     }
>     for (int j = i; j < value.size(); j++) {
>       FeatureVector jOfV = matrix_l.getRowVector(i);
>       for(int x = 0; x < jOfV.size(); x++) {
>         jthRowOfL[x] = jOfV.getDimAt(x);
>       }
>       double sum = matrix_a.get(i, j);
>       for (int k = i - 1; k >= 0; k--) {
>         sum -= ithRowOfL[k] * jthRowOfL[k];
>       }
>       if (i == j) {
>         matrix_l.setToLower(j, i, Math.sqrt(sum));
>       } else {
>         double c = matrix_l.get(i, i);
>         matrix_l.setToLower(j, i, (sum / c));
>       }
>     }
>   }
> }

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