What is the type of unlabeledTest? SQL should be using the VectorUDT we've defined for Vectors <https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala#L183> so you should be able to just "import sqlContext.implicits._" and then call "rdd.toDf()" on your RDD to convert it into a dataframe.
On Fri, Sep 18, 2015 at 7:32 AM, Yasemin Kaya <godo...@gmail.com> wrote: > Hi, > > I am using *spark 1.5, ML Pipeline Decision Tree > <http://spark.apache.org/docs/latest/ml-decision-tree.html#output-columns>* > to get tree's probability. But I have to convert my data to Dataframe type. > While creating model there is no problem but when I am using model on my > data there is a problem about converting to data frame type. My data type > is *JavaPairRDD<String, Vector>* , when I am creating dataframe > > DataFrame production = sqlContext.createDataFrame( > unlabeledTest.values(), Vector.class); > > *Error says me: * > Exception in thread "main" java.lang.ClassCastException: > org.apache.spark.mllib.linalg.VectorUDT cannot be cast to > org.apache.spark.sql.types.StructType > > I know if I give LabeledPoint type, there will be no problem. But the data > have no label, I wanna predict the label because of this reason I use model > on it. > > Is there way to handle my problem? > Thanks. > > > Best, > yasemin > -- > hiç ender hiç >
