val tempDict = sqlContext.sql("select words.pName_token,collect_set(words.pID) as docids
                               from words
                               group by words.pName_token").toDF()

val wordDocs = tempDict.filter(newDict("pName_token")===word)

val listDocs = wordDocs.map(t => t(1)).collect()

listDocs: Array

[Any] = Array(WrappedArray(123, 234, 205876618, 456))

import org.apache.spark.sql.Row
import org.apache.spark.sql.functions._
import scala.collection.mutable.WrappedArray

val data = Seq((Seq(1,2,3),Seq(4,5,6),Seq(7,8,9)))
val df = sqlContext.createDataFrame(data)
val first = df.first

// use a pattern match to deferral the type
val mapped = first.getAs[WrappedArray[Int]](0)

// now we can use it like normal collection
mapped.mkString("n")

// get rows where has array
val rows = df.collect.map {
    case Row(a: Seq[Any], b: Seq[Any], c: Seq[Any]) =>
        (a, b, c)
}
rows.mkString("n")