[jira] [Created] (SPARK-2923) Implement some basic linalg operations in MLlib

["Xiangrui Meng (JIRA)" <ji...@apache.org>]

Xiangrui Meng created SPARK-2923:
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             Summary: Implement some basic linalg operations in MLlib
                 Key: SPARK-2923
                 URL: https://issues.apache.org/jira/browse/SPARK-2923
             Project: Spark
          Issue Type: Improvement
          Components: MLlib
            Reporter: Xiangrui Meng
            Assignee: Xiangrui Meng


We use breeze for linear algebra operations. Breeze operations are user-friendly but there are some concerns:

1. creating temp objects, e.g., `val z = a * x + b * y`
2. multi-method is not used in some operators, e.g., `axpy`. If we pass in SparseVector as a generic Vector, it will use activeIterator, which is slow
3. calling native BLAS if it is available, which might not be good for level-1 methods

Having some basic BLAS operations implemented in MLlib can help simplify the current implementation and improve some performance.



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