What's the best way to find the Nearest Neighbor row of a matrix with 10billion rows x 300 columns?

[Rex X]

Each row of the given matrix is Vector[Double]. Want to find out the
nearest neighbor row to each row using cosine similarity.

The problem here is the complexity: O( 10^20 )

We need to do *blocking*, and do the row-wise comparison within each block.
Any tips for best practice?

In Spark, we have RowMatrix.*ColumnSimilarity*, but I didn't find
*RowSimilarity* method.


Thank you.


Regards
Rex