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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2019/07/25 13:01:00 UTC
[jira] [Updated] (SPARK-28421) SparseVector.apply performance
optimization
[ https://issues.apache.org/jira/browse/SPARK-28421?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-28421:
------------------------------
Affects Version/s: 2.4.3
Priority: Minor (was: Major)
Fix Version/s: 2.4.4
> SparseVector.apply performance optimization
> -------------------------------------------
>
> Key: SPARK-28421
> URL: https://issues.apache.org/jira/browse/SPARK-28421
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.0.0, 2.4.3
> Reporter: zhengruifeng
> Assignee: zhengruifeng
> Priority: Minor
> Fix For: 2.4.4, 3.0.0
>
>
> Current impl of SparseVector.apply is inefficient:
> on each call, breeze.linalg.SparseVector & breeze.collection.mutable.SparseArray are created internally, then binary-search is used to search the input position.
>
> This place should be optimized like .ml.SparseMatrix, which directly use binary search, without conversion to breeze.linalg.Matrix.
>
> I tested the performance and found that if we avoid the internal conversions, then a 2.5~5X speed up can be obtained.
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