如何使用 Java 在 Spark 中组合或合并两个稀疏向量？

Question

我使用了 Java 的 API，即 Apache-Spark 1.2.0，并创建了两个解析向量，如下所示。

Vector v1 = Vectors.sparse(3, new int[]{0, 2}, new double[]{1.0, 3.0});
Vector v2 = Vectors.sparse(2, new int[]{0, 1}, new double[]{4,5});

如何得到v1和v2组合而成的新向量v3，所以结果应该是：(5, [0,2,3,4],[1.0, 3.0, 4.0, 5.0])

Answer 1

我发现这个问题已经一年了，仍然悬而未决。这里我自己写了一个辅助函数解决了这个问题，如下。

public static SparseVector combineSparseVectors(SparseVector... svs) {
    int size = 0;
    int nonzeros = 0;
    for (SparseVector sv : svs) {
        size += sv.size();
        nonzeros += sv.indices().length;
    }

    if (nonzeros != 0) {
        int[] indices = new int[nonzeros];
        double[] values = new double[nonzeros];

        int pointer_D = 0;
        int totalPt_D = 0;
        int pointer_V = 0;
        for (SparseVector sv : svs) {
            int[] indicesSV = sv.indices();
            for (int i : indicesSV) {
                indices[pointer_D++] = i + totalPt_D;
            }
            totalPt_D += sv.size();

            double[] valuesSV = sv.values();
            for (double d : valuesSV) {
                values[pointer_V++] = d;
            }

        }
        return new SparseVector(size, indices, values);
    } else {
        System.out.println("all zeroes");
        return null;
    }

}

Answer 2

根据 HappyCoding 的回答，我只想使用 pyspark 和 numpy

在 Python 3.x 中贡献我的代码

import numpy as np
from pyspark.mllib.linalg import SparseVector


def concat_sparse_vectors(sparse_vectors):
    """
    Input:
        sparse_vectors (list): A list containing sparse vectors
    Output:
        A concatenated sparse vector
    """
    size = 0
    nonzeros = 0

    for vector in sparse_vectors:
        size += vector.size
        nonzeros += len(vector.indices)

    if nonzeros != 0:
        indices = np.zeros(nonzeros)
        values = np.zeros(nonzeros)

        pointer_D = 0 # A pointer pointing to the index where a non-zero value occupied in the 'values' array
        total_point_D = 0 # A displacement value for 'pointer_D' in the concatenated array which is 'values' in the code
        pointer_V = 0 # A pointer pointing to a value in the 'values' array in the code

        for vector in sparse_vectors:
            vector_indices = vector.indices
            for i in vector_indices:
                indices[pointer_D] = i + total_point_D
                pointer_D += 1

            total_point_D += vector.size

            vector_values = vector.values
            for value in vector_values:
                values[pointer_V] = value
                pointer_V += 1

        return SparseVector(size, indices, values)

    else:
        print('All zeros')

如何使用 Java 在 Spark 中组合或合并两个稀疏向量？

How to combine or merge two sparse vectors in Spark using Java?

java

sparse-matrix

apache-spark

apache-spark-mllib