Spark SQL中 RDD 转换到 DataFrame

1.people.txt
soyo8, 35
小周, 30
小华, 19
soyo,88
2.
/**
  * Created by soyo on 17-10-10.
  * 利用反射机制推断RDD模式
  */
import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
import org.apache.spark.sql.{Encoder, SparkSession}
import org.apache.spark.sql.SparkSession
case class  Person(name:String,age:Int)
object RDD_To_DataFrame {
  val spark=SparkSession.builder().getOrCreate()
  import spark.implicits._    //支持把一个RDD隐式转换为一个DataFrame

  def main(args: Array[String]): Unit = {
    val df =spark.sparkContext.textFile("file:///home/soyo/桌面/spark编程测试数据/people.txt")
      .map(_.split(",")).map(x=>Person(x(0),x(1).trim.toInt)).toDF()

      df.createOrReplaceTempView("people")   //定制people表
     val personDF=spark.sql("select * from people where age >=30")
    personDF.map(x=>"姓名="+x(0)+","+"年龄="+x(1)).show()
     //转换为表的形式
    personDF.select(personDF("name").as("姓名"),personDF("age").as("年龄")).show()
    personDF.rdd.saveAsTextFile("file:///home/soyo/桌面/spark编程测试数据/新数据.txt")
  }

}
结果：
+--------------+
|         value|
+--------------+
|姓名=soyo8,年龄=35|
|   姓名=小周,年龄=30|
| 姓名=soyo,年龄=88|
+--------------+

+-----+---+
|   姓名| 年龄|
+-----+---+
|soyo8| 35|
|   小周| 30|
| soyo| 88|
+-----+---+