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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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Apache Spark reassigned SPARK-7194:
-----------------------------------

    Assignee: Apache Spark

> 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
>            Reporter: Juliet Hougland
>            Assignee: Apache Spark
>
> 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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