toDF 的问题，值 toDF 不是 org.apache.spark.rdd.RDD 的成员

Question

我附加了错误“值 toDF 不是 org.apache.spark.rdd.RDD 的成员”的代码片段。我正在使用 Scala 2.11.8 和 spark 2.0.0。你能帮我解决 API toDF() 的这个问题吗？

import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.SQLContext
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Row, SparkSession}
import org.apache.spark.sql.functions._

object HHService {
    case class Services(
    uhid:String,
    locationid:String,
    doctorid:String,
    billdate:String,
    servicename:String,
    servicequantity:String,
    starttime:String,
    endtime:String,
    servicetype:String,
    servicecategory:String,
    deptname:String
    )

    def toService = (p: Seq[String]) => Services(p(0), p(1),p(2),p(3),p(4),p(5),p(6),p(7),p(8),p(9),p(10))

    def main(args: Array[String]){
        val warehouseLocation = "file:${system:user.dir}/spark-warehouse"
        val spark = SparkSession
            .builder
            .appName(getClass.getSimpleName)
            .config("spark.sql.warehouse.dir", warehouseLocation)
        .enableHiveSupport()
            .getOrCreate()
        val sc = spark.sparkContext 

        val sqlContext = spark.sqlContext;

        import spark.implicits._
        import sqlContext.implicits._

        val hospitalDataText = sc.textFile("D:/Books/bboks/spark/Intellipaat/Download/SparkHH/SparkHH/services.csv")
        val header = hospitalDataText.first()
        val hospitalData= hospitalDataText.filter(a => a!= header)
        //val HData = hospitalData.map(_.split(",")).map(p=>Services(p(0), p(1),p(2),p(3),p(4),p(5),p(6),p(7),p(8),p(9),p(10)))
        val HData = hospitalData.map(_.split(",")).map(toService(_))

        val hosService=HData.toDF()
    }

}

Answer 1

1] 需要获取 sqlContext 如下。

val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.implicits._

这解决了我的问题。前面的代码片段用于获取 sqlcontext。val sqlContext = spark.sqlContext（这种方式与 spark-shell 一起使用）

2] 案例类需要退出方法。大多数博客中也提到了这一点。