[GitHub] [arrow] mrkn commented on a change in pull request #7477: ARROW-4221: [C++][Python] Add canonical flag in COO sparse index

[GitBox <gi...@apache.org>]

mrkn commented on a change in pull request #7477:
URL: https://github.com/apache/arrow/pull/7477#discussion_r443922882



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File path: python/pyarrow/tensor.pxi
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@@ -199,7 +202,13 @@ shape: {0.shape}""".format(self)
             for x in dim_names:
                 c_dim_names.push_back(tobytes(x))
 
-        coords = np.vstack([obj.row, obj.col]).T
+        row = obj.row
+        col = obj.col
+        if obj.has_canonical_format:
+            order = np.lexsort((col, row))  # row-major order

Review comment:
       SciPy's coo_matrix employs column-major order, but our SparseCOOIndex employs row-major order.
   This is the reason why we need to sort the index here.
   
   The reason why our SparseCOOIndex should employ row-major order is that TensorFlow's SparseTensor employs row-major order.  Converting from SciPy's coo_matrrix needs to copy the index matrix even if we employ column-major order, but converting from TensorFlow's SparseTensor does not need to copy the index matrix if we employ row-major order.




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