如何沿着矩阵Spark Scala的行找到最大值的索引? [英] How can I find the index of the maximum values along rows of matrix Spark Scala?

问题描述

我有一个问题，想找到沿着矩阵行的最大值的索引.如何在Spark Scala中做到这一点?此功能类似于Python中numpy中的argmax.

I have a question about finding index of the maximum values along rows of matrix. How can I do this in Spark Scala? This function would be like argmax in numpy in Python.

推荐答案

矩阵的类型是什么?如果它是RowMatrix，则可以使用rows访问其行向量的RDD.

What's the type of your matrix ? If it's a RowMatrix, you can access the RDD of its row vectors using rows.

然后，如果我理解正确，那么找到此RDD[Vector]的每个向量的最大值就很简单.因此，您可以myMatrix.rows.map{_.toArray.max}.

Then it's a simple matter of finding the maximum of each vector of this RDD[Vector], if I understand correctly. You can therefore myMatrix.rows.map{_.toArray.max}.

如果有DenseMatrix，则可以将其转换为Array，在此阶段，您将在

If you have a DenseMatrix you can convert it to an Array, at which stage you'll have a list of elements in row-major form. You can also access the number of columns of your matrix with numCols, and then use the collections method grouped to obtain rows.

myMatrix.toArray.grouped(myMatrix.numCols).map{_.max}

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