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https://issues.apache.org/jira/browse/SPARK-17950?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-17950:
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Labels: bulk-closed (was: )
> Match SparseVector behavior with DenseVector
> --------------------------------------------
>
> Key: SPARK-17950
> URL: https://issues.apache.org/jira/browse/SPARK-17950
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib, PySpark
> Affects Versions: 2.0.1
> Reporter: AbderRahman Sobh
> Priority: Minor
> Labels: bulk-closed
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> What changes were proposed in this pull request?
> Simply added the __getattr__ to SparseVector that DenseVector has, but calls
> to a SciPy sparse representation instead of storing a vector all the time in
> self.array
> This allows for use of functions on the values of an entire SparseVector in
> the same direct way that users interact with DenseVectors.
> i.e. you can simply call SparseVector.mean() to average the values in the
> entire vector.
> Note: The functions do have a slight bit of variance due to calling SciPy and
> not NumPy. However, the majority of useful functions (sums, means, max, etc.)
> are available to both packages anyways.
> How was this patch tested?
> Manual testing on local machine.
> Passed ./python/run-tests
> No UI changes.
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