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Posted to issues@spark.apache.org by "zhengruifeng (Jira)" <ji...@apache.org> on 2019/12/03 10:45:00 UTC

[jira] [Created] (SPARK-30109) PCA use BLAS.gemv with sparse vector

zhengruifeng created SPARK-30109:
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             Summary: PCA use BLAS.gemv with sparse vector
                 Key: SPARK-30109
                 URL: https://issues.apache.org/jira/browse/SPARK-30109
             Project: Spark
          Issue Type: Improvement
          Components: ML
    Affects Versions: 3.0.0
            Reporter: zhengruifeng


When PCA was first impled in [SPARK-5521|https://issues.apache.org/jira/browse/SPARK-5521], at that time Matrix.multiply(BLAS.gemv internally) did not support sparse vector. So it worked around it by applying a complex matrix multiplication.

Since [SPARK-7681|https://issues.apache.org/jira/browse/SPARK-7681], BLAS.gemv supported sparse vector. So we can directly use Matrix.multiply now.



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