ARROW-4335: [C++] Better document sparse tensor support #3810
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cpp/src/arrow/sparse_tensor.h
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I put this class in internal namespace to remove it from documentation targets.
cpp/src/arrow/sparse_tensor.h
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| /// values in sparse tensor | ||
| /// \brief EXPERIMENTAL: The base class for the index of a sparse tensor | ||
| /// | ||
| /// SparseIndex are used to represent where is non-zero values in a |
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This is less clear than it could be, maybe rewrite as "SparseIndex describes where the non-zero elements are within a SparseTensor."
cpp/src/arrow/sparse_tensor.h
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| /// SparseIndex are used to represent where is non-zero values in a | ||
| /// SparseTensor. | ||
| /// | ||
| /// There are several ways of the index representation. The format_id is used |
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I think it'd be useful to note specifically that there is a single derived class for each possible value of format_id (SparseTensorFormat::COO -> SparseCOOIndex and SparseTensorFormat::CSR -> SparseCSRIndex)
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I tried to describe that you mentioned.
Could you please review it again?
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Thanks!
Also this sentence isn't quite grammatically correct. Could you use -ways of the index representation+ways to represent this?
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Thank you for your feedback. I fixed the incorrect representation.
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The Travis failure looks spurious to me |
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@kou Could you understand what is happened on CI here? |
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Umm. I didn't see this SEGV. |
Codecov Report
@@ Coverage Diff @@
## master #3810 +/- ##
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+ Coverage 67.76% 87.79% +20.02%
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Files 468 710 +242
Lines 58721 86896 +28175
Branches 1252 1252
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+ Hits 39793 76287 +36494
+ Misses 18811 10496 -8315
+ Partials 117 113 -4
Continue to review full report at Codecov.
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I've fixed the SEGV. |
I wrote descriptions for sparse tensor classes. Author: Kenta Murata <mrkn@mrkn.jp> Closes apache#3810 from mrkn/sparse_tensor_doc and squashes the following commits: 9c4fe14 <Kenta Murata> Fix incorrect English 522a982 <Kenta Murata> Modify comments following review comments 83cab03 <Kenta Murata> Put SparseIndexBase<> class in internal namespace 6cd13e2 <Kenta Murata> Write descriptions of sparse tensor
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I wrote descriptions for sparse tensor classes.