GitHub user viirya opened a pull request:
https://github.com/apache/spark/pull/17532
[SPARK-20214][ML] Make sure converted csc matrix has sorted indices
## What changes were proposed in this pull request?
`_convert_to_vector` converts a scipy sparse matrix to csc matrix for
initializing `SparseVector`. However, it doesn't guarantee the converted csc
matrix has sorted indices and so a failure happens when you do something like
that:
from scipy.sparse import lil_matrix
lil = lil_matrix((4, 1))
lil[1, 0] = 1
lil[3, 0] = 2
_convert_to_vector(lil.todok())
File "/home/jenkins/workspace/python/pyspark/mllib/linalg/__init__.py",
line 78, in _convert_to_vector
return SparseVector(l.shape[0], csc.indices, csc.data)
File "/home/jenkins/workspace/python/pyspark/mllib/linalg/__init__.py",
line 556, in __init__
% (self.indices[i], self.indices[i + 1]))
TypeError: Indices 3 and 1 are not strictly increasing
A simple test can confirm that `dok_matrix.tocsc()` won't guarantee sorted
indices:
>>> from scipy.sparse import lil_matrix
>>> lil = lil_matrix((4, 1))
>>> lil[1, 0] = 1
>>> lil[3, 0] = 2
>>> dok = lil.todok()
>>> csc = dok.tocsc()
>>> csc.has_sorted_indices
0
>>> csc.indices
array([3, 1], dtype=int32)
I checked the source codes of scipy. The only way to guarantee it is
`csc_matrix.tocsr()` and `csr_matrix.tocsc()`.
## How was this patch tested?
Existing tests.
Please review http://spark.apache.org/contributing.html before opening a
pull request.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/viirya/spark-1 make-sure-sorted-indices
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17532.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17532
----
commit f88eb6b65005c367660d8aabfcd7d9b63ab6b121
Author: Liang-Chi Hsieh <[email protected]>
Date: 2017-04-05T03:22:43Z
Make sure converted csc matrix has sorted indices.
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