not possible, but you can add your own object in your project to the
spark's package that would give you access to private methods
package org.apache.spark.sql
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.execution.LogicalRDD
import org.apache.spark.sql.types.StructType
object DataFrameUtil {
/**
* Creates a DataFrame out of RDD[InternalRow] that you can get
using `df.queryExection.toRdd`
*/
def createFromInternalRows(sparkSession: SparkSession, schema:
StructType, rdd: RDD[InternalRow]): DataFrame = {
val logicalPlan = LogicalRDD(schema.toAttributes, rdd)(sparkSession)
Dataset.ofRows(sparkSession, logicalPlan)
}
}