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[SPARK-20214][ML] Make sure converted csc matrix has sorted indices #17532

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[SPARK-20214][ML] Make sure converted csc matrix has sorted indices #17532

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10be94a
Make sure the converted csc matrix has sorted indices.
viirya Apr 5, 2017
2612d66
Add test. Call sort_indices().
viirya Apr 5, 2017
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4 changes: 3 additions & 1 deletion python/pyspark/ml/linalg/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,9 @@ def _convert_to_vector(l):
return DenseVector(l)
elif _have_scipy and scipy.sparse.issparse(l):
assert l.shape[1] == 1, "Expected column vector"
csc = l.tocsc()
# Make sure the converted csc_matrix has sorted indices.
csc = l.tocsr().tocsc()

@jkbradley jkbradley Apr 5, 2017

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I'd just call tocsc. You can then check the attribute has_sorted_indices and call sort_indices() if needed.

@viirya viirya Apr 5, 2017

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Thanks. Fixed.

assert csc.has_sorted_indices, "Converted CSC matrix should have sorted indices"
return SparseVector(l.shape[0], csc.indices, csc.data)
else:
raise TypeError("Cannot convert type %s into Vector" % type(l))
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4 changes: 3 additions & 1 deletion python/pyspark/mllib/linalg/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,9 @@ def _convert_to_vector(l):
return DenseVector(l)
elif _have_scipy and scipy.sparse.issparse(l):
assert l.shape[1] == 1, "Expected column vector"
csc = l.tocsc()
# Make sure the converted csc_matrix has sorted indices.
csc = l.tocsr().tocsc()
assert csc.has_sorted_indices, "Converted CSC matrix should have sorted indices"
return SparseVector(l.shape[0], csc.indices, csc.data)
else:
raise TypeError("Cannot convert type %s into Vector" % type(l))
Expand Down