Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/15730#discussion_r96038711
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala
---
@@ -459,14 +464,155 @@ class BlockMatrix @Since("1.3.0") (
*/
@Since("1.3.0")
def multiply(other: BlockMatrix): BlockMatrix = {
+ multiply(other, 1)
+ }
+
+ /**
+ * Left multiplies this [[BlockMatrix]] to `other`, another
[[BlockMatrix]]. This method add
--- End diff --
Ok, I feel this is very verbose in terms of documentation. Can we summarize
it somehow?
```scala
/**
* Left multiplies this [[BlockMatrix]] to `other`, another
[[BlockMatrix]]. The `colsPerBlock`
* of this matrix must equal the `rowsPerBlock` of `other`. If `other`
contains
* `SparseMatrix`, they will have to be converted to a `DenseMatrix`. The
output
* [[BlockMatrix]] will only consist of blocks of `DenseMatrix`. This may
cause
* some performance issues until support for multiplying two sparse
matrices is added.
* Blocks with duplicate indices will be added with each other.
*
* @param other Matrix `B` in `A * B = C`
* @param numMidDimSplits Number of splits to cut on the middle dimension
when doing multiplication.
For example, when multiplying a Matrix `A` of size `m x n` with Matrix `B`
of size `n x k`, this parameter
configures the parallelism to use when grouping the matrices. The
parallelism will increase from `m x k` to
`m x k x numMidDimSplits`, which in some cases also reduces total shuffled
data.
```
Wrote out a sketch, please put in proper format, i.e. omitted `*` on the
last lines
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