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https://issues.apache.org/jira/browse/SPARK-10127?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14705524#comment-14705524
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Joseph K. Bradley commented on SPARK-10127:
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There have been a number of discussions about whether we should develop a fully
local linear algebra library. It will be important to follow a consistent API
which has a global design, rather than built up incrementally. There is
already a design doc: [SPARK-6442], and further additions should probably be
discussed on that JIRA.
Could you please close your PR for now, pending discussion on that JIRA? For
now, users can use existing libraries such as Breeze. Thanks!
> Add numpy-like indexing interface for DenceMatrix
> -------------------------------------------------
>
> Key: SPARK-10127
> URL: https://issues.apache.org/jira/browse/SPARK-10127
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.4.1
> Reporter: Hiroshi Takahashi
>
> Currently, we don't have good interface to access sub-matrix.
> It's inconvenience to prototype manipulate matrix via spark-shell for the
> reason.
> My suggestion is to add operator "!" as operator of accessing sub-matrix
> instead of numpy's ().
> for example:
> {code}
> scala> import org.apache.spark.mllib.linalg.DenseMatrix
> import org.apache.spark.mllib.linalg.DenseMatrix
> scala> val dm = new DenseMatrix(3, 3, Array(1.0, 4.0, 7.0, 2.0, 5.0, 8.0,
> 3.0, 6.0, 9.0))
> dm: org.apache.spark.mllib.linalg.DenseMatrix =
> 1.0 2.0 3.0
> 4.0 5.0 6.0
> 7.0 8.0 9.0
> // get row
> scala> dm!(1)
> res0: org.apache.spark.mllib.linalg.DenseMatrix = 4.0 5.0 6.0
> // get (i, j)
> scala> dm!(1, 2)
> res1: Double = 6.0
> // get colmun
> scala> dm!((), 1)
> res2: org.apache.spark.mllib.linalg.DenseMatrix =
> 2.0
> 5.0
> 8.0
> // get columns between i and j-1
> scala> dm!((), (1, 3))
> res3: org.apache.spark.mllib.linalg.DenseMatrix =
> 2.0 3.0
> 5.0 6.0
> 8.0 9.0
> // get rows between i and j-1
> scala> dm!((1, 3))
> res4: org.apache.spark.mllib.linalg.DenseMatrix =
> 4.0 5.0 6.0
> 7.0 8.0 9.0
> // get sub-matrix between (i1, j1-1) and (i2, j2-1)
> scala> dm!((1, 3), (1, 3))
> res5: org.apache.spark.mllib.linalg.DenseMatrix =
> 5.0 6.0
> 8.0 9.0
> {code}
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