Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/7972#discussion_r36363088
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
---
@@ -766,6 +767,28 @@ class SparseVector(
maxIdx
}
}
+
+ /**
+ * Create a slice of this vector based on the given indices.
+ * @param selectedIndices Sorted list of indices into the vector. This
does NOT do bound checking.
+ * @return New SparseVector with values in the order specified by the
given indices.
+ *
+ * NOTE: The API needs to be discussed before making this public.
+ */
+ private[spark] def slice(selectedIndices: Array[Int]): SparseVector = {
+ var currentIdx = 0
+ val (sliceInds, sliceVals) = selectedIndices.flatMap { origIdx =>
--- End diff --
Also leave a TODO to optimize the implementation. If we assume input
indices are ordered (or sort it), then this should be a merge intersection.
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