标签：rdd1 String val dataFrame rdd DataFrame Student
核心语句val rdd1 = dataFrame.rdd
package SparkSQL.DataFreamCreate.dataframetordd
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.types.{DataTypes, StructField, StructType}
import org.apache.spark.sql.{DataFrame, Row, SparkSession}
import scala.beans.BeanProperty
object dftordd1 {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("dataFrameCreate").setMaster("local[*]")
val sparkSession = SparkSession.builder().config(conf).getOrCreate()
val seq:Seq[Student] = Array(Student("zs",20,"男"),Student("ls",21,"女"),Student("ww",22,"男"))
val rdd:RDD[Student] = sparkSession.sparkContext.makeRDD(seq)
val dataFrame:DataFrame = sparkSession.createDataFrame(rdd,classOf[Student])
dataFrame.show()
val rdd1 = dataFrame.rdd
val rdd2: RDD[Row] = rdd1.map(row => {
Row(row.getAs[String]("name"), row.getAs[Int]("age") + 5, row.getAs[String]("sex"))
})
val structType = StructType(Array(
StructField("name", DataTypes.StringType),
StructField("age", DataTypes.IntegerType),
StructField("sex", DataTypes.StringType)
))
val frame: DataFrame = sparkSession.createDataFrame(rdd2, structType)
frame.show()
}
}
case class Student(@BeanProperty var name:String,@BeanProperty var age:Int,@BeanProperty var sex:String)
标签：rdd1,
String,
val,
dataFrame,
rdd,
DataFrame,
Student
From： https://www.cnblogs.com/jsqup/p/16638035.html