本文整理汇总了Java中org.apache.spark.mllib.linalg.DenseVector.size方法的典型用法代码示例。如果您正苦于以下问题：Java DenseVector.size方法的具体用法？Java DenseVector.size怎么用？Java DenseVector.size使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.spark.mllib.linalg.DenseVector的用法示例。
在下文中一共展示了DenseVector.size方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: DGER_IRW
import org.apache.spark.mllib.linalg.DenseVector; //导入方法依赖的package包/类
private static IndexedRowMatrix DGER_IRW(IndexedRowMatrix A, double alpha, DenseVector x, DenseVector y, JavaSparkContext jsc) {
final Broadcast<Double> AlphaBC = jsc.broadcast(alpha);
final Broadcast<DenseVector> BCVector_X = jsc.broadcast(x);
final Broadcast<DenseVector> BCVector_Y = jsc.broadcast(y);
JavaRDD<IndexedRow> rows = A.rows().toJavaRDD();
JavaRDD<IndexedRow> resultRows = rows.map(new Function<IndexedRow, IndexedRow>() {
@Override
public IndexedRow call(IndexedRow indexedRow) throws Exception {
DenseVector Vector_X = BCVector_X.getValue();
DenseVector Vector_Y = BCVector_Y.getValue();
double alphaBCRec = AlphaBC.getValue().doubleValue();
DenseVector row = indexedRow.vector().toDense();
double[] resultArray = new double[row.size()];
long i = indexedRow.index();
for( int j = 0; j< Vector_Y.size(); j++) {
resultArray[j] = alphaBCRec * Vector_X.apply((int)i) * Vector_Y.apply(j) + row.apply(j);
}
DenseVector result = new DenseVector(resultArray);
return new IndexedRow(indexedRow.index(), result);
}
});
IndexedRowMatrix newMatrix = new IndexedRowMatrix(resultRows.rdd(), x.size(), y.size());
return newMatrix;
}
示例2: multiply
import org.apache.spark.mllib.linalg.DenseVector; //导入方法依赖的package包/类
public static double multiply(DenseVector v1, DenseVector v2) {
double result = 0;
for( int i = 0; i< v1.size(); i++){
result = result + v1.apply(i) * v2.apply(i);
}
return result;
}
示例3: vectorSumElements
import org.apache.spark.mllib.linalg.DenseVector; //导入方法依赖的package包/类
public static double vectorSumElements(DenseVector vector) {
double result = 0.0;
for(int i = 0; i< vector.size(); i++) {
result = result + vector.apply(i);
}
return result;
}
示例4: writeVectorToFileInHDFS
import org.apache.spark.mllib.linalg.DenseVector; //导入方法依赖的package包/类
public static void writeVectorToFileInHDFS(String file, DenseVector vector, Configuration conf){
try {
FileSystem fs = FileSystem.get(conf);
Path pt = new Path(file);
//FileSystem fileSystem = FileSystem.get(context.getConfiguration());
BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(fs.create(pt, true)));
bw.write("%%MatrixMarket matrix array real general");
bw.newLine();
bw.write(vector.size()+" 1");
bw.newLine();
for(int i = 0; i< vector.size(); i++) {
bw.write(String.valueOf(vector.apply(i)));
bw.newLine();
}
bw.close();
//fs.close();
} catch (IOException e) {
LOG.error("Error in " + IO.class.getName() + ": " + e.getMessage());
e.printStackTrace();
System.exit(1);
}
}