[jira] [Issue Comment Deleted] (SPARK-14850) VectorUDT/MatrixUDT should take primitive arrays without boxing

["胡振宇 (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14850?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

胡振宇 updated SPARK-14850:
------------------------
    Comment: was deleted

(was: I try to run your code on spark1.6.1 but i found that "toDF" cannot be used in this example
Here are my code 
object Example{
def main (args:Array[String]){
  case class Test(num:Int,vector:Vector)
  val conf = new SparkConf.setAppname("Example")
  val sqlContext=new SQLContext(sc)
  import sqlContext.implicts._
  val temp=sqlContext.sparkContext.parallelize(0,until 1e4.toInt,1).map(i=>Test(i,Vectors.dense(Array.fill(1e6.toInt)(1.0)))).toDF() //at this step toDF can be used I do
 }
}



sc.parallelize(0 until 1e4.toInt, 1).map { i =>
  (i, Vectors.dense(Array.fill(1e6.toInt)(1.0)))
}.toDF.rdd.count()

I even use sparkcontext but toDF cannot be used too

Do you have a solution to run the example on spark1.6.1? Thank you 

} )

> VectorUDT/MatrixUDT should take primitive arrays without boxing
> ---------------------------------------------------------------
>
>                 Key: SPARK-14850
>                 URL: https://issues.apache.org/jira/browse/SPARK-14850
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, SQL
>    Affects Versions: 1.5.2, 1.6.1, 2.0.0
>            Reporter: Xiangrui Meng
>            Assignee: Wenchen Fan
>            Priority: Critical
>             Fix For: 2.0.0
>
>
> In SPARK-9390, we switched to use GenericArrayData to store indices and values in vector/matrix UDTs. However, GenericArrayData is not specialized for primitive types. This might hurt MLlib performance badly. We should consider either specialize GenericArrayData or use a different container.
> cc: [~cloud_fan] [~yhuai]



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