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https://issues.apache.org/jira/browse/SPARK-7194?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-7194.
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Resolution: Won't Fix
Just talked to [~juliet] and she says the {{toSparse}} method is a good fit for
her use case.
> Vectors factors method for sparse vectors should accept the output of
> zipWithIndex
> ----------------------------------------------------------------------------------
>
> Key: SPARK-7194
> URL: https://issues.apache.org/jira/browse/SPARK-7194
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.1
> Reporter: Juliet Hougland
> Priority: Minor
>
> Let's say we have an RDD of Array[Double] where zero values are explictly
> recorded. Ie (0.0, 0.0, 3.2, 0.0...) If we want to transform this into an RDD
> of sparse vectors, we currently have to:
> arr_doubles.map{ array =>
> val indexElem: Seq[(Int, Double)] = array.zipWithIndex.filter(tuple =>
> tuple._1 != 0.0).map(tuple => (tuple._2, tuple._1))
> Vectors.sparse(arrray.length, indexElem)
> }
> Notice that there is a map step at the end to switch the order of the index
> and the element value after .zipWithIndex. There should be a factory method
> on the Vectors class that allows you to avoid this flipping of tuple elements
> when using zipWithIndex.
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