Github user gglanzani commented on the issue:
https://github.com/apache/spark/pull/15074
@HyukjinKwon So I think I will close this one. The issue is that there is
never a shorter path.
Take for example this code
```python
C = SparseMatrix(2, 2, [0, 0, 2], [1], [2], isTransposed=True)
print(C.toArray())
M = SparseMatrix(2, 2, [0, 0, 2], [1, 1], [2, 2], isTransposed=True)
print(M.toArray())
C == M
```
In the current implementation, the last statement is `True` (correctly),
even if `rowIndices` **and** `values` are different.
I might look in the future at how scipy is doing that. They do have some
extra machinery though, as they support a much wider spectrum of sparse
implementations.
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