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Posted to dev@mahout.apache.org by "Jake Mannix (JIRA)" <ji...@apache.org> on 2013/04/25 00:07:17 UTC
[jira] [Created] (MAHOUT-1197) AbstractVector#cross is only
appropriately efficient for dense vectors
Jake Mannix created MAHOUT-1197:
-----------------------------------
Summary: AbstractVector#cross is only appropriately efficient for dense vectors
Key: MAHOUT-1197
URL: https://issues.apache.org/jira/browse/MAHOUT-1197
Project: Mahout
Issue Type: Bug
Components: Math
Affects Versions: 0.6
Reporter: Jake Mannix
Fix For: 0.8
Nobody overrides this implementation:
[code]
@Override
public Matrix cross(Vector other) {
Matrix result = matrixLike(size, other.size());
for (int row = 0; row < size; row++) {
result.assignRow(row, other.times(getQuick(row)));
}
return result;
}
[code]
I think you can imagine what kind of performance this has on sparse vectors (k non-zeroes) with high cardinality (N) - scales as O(N^2) instead of O(k^2).
I think the right approach is to *not* implement this in AbstractVector at all, and force concrete implementations to properly implement it performantly.
Alternatively, killing this method entirely might be appropriate. If anyone was using it (and uses sparse vectors), they'd have complained about this by now.
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Re: [jira] [Created] (MAHOUT-1197) AbstractVector#cross is only
appropriately efficient for dense vectors
Posted by Robin Anil <ro...@gmail.com>.
I second. Kill everything thats not used. Dan's assign work will improve
the speed of assignRow. But I can imagine there are even more smarter way
to do this for sparse vectors
On Wed, Apr 24, 2013 at 5:07 PM, Jake Mannix (JIRA) <ji...@apache.org> wrote:
> Jake Mannix created MAHOUT-1197:
> -----------------------------------
>
> Summary: AbstractVector#cross is only appropriately efficient
> for dense vectors
> Key: MAHOUT-1197
> URL: https://issues.apache.org/jira/browse/MAHOUT-1197
> Project: Mahout
> Issue Type: Bug
> Components: Math
> Affects Versions: 0.6
> Reporter: Jake Mannix
> Fix For: 0.8
>
>
> Nobody overrides this implementation:
> [code]
> @Override
> public Matrix cross(Vector other) {
> Matrix result = matrixLike(size, other.size());
> for (int row = 0; row < size; row++) {
> result.assignRow(row, other.times(getQuick(row)));
> }
> return result;
> }
> [code]
>
> I think you can imagine what kind of performance this has on sparse
> vectors (k non-zeroes) with high cardinality (N) - scales as O(N^2) instead
> of O(k^2).
>
> I think the right approach is to *not* implement this in AbstractVector at
> all, and force concrete implementations to properly implement it
> performantly.
>
> Alternatively, killing this method entirely might be appropriate. If
> anyone was using it (and uses sparse vectors), they'd have complained about
> this by now.
>
> --
> This message is automatically generated by JIRA.
> If you think it was sent incorrectly, please contact your JIRA
> administrators
> For more information on JIRA, see: http://www.atlassian.com/software/jira
>