scala - 显式转换读取 .csv 与案例类 Spark 2.1.0

Question

我有以下案例类:

case class OrderDetails(OrderID : String, ProductID : String, UnitPrice : Double,
                    Qty : Int, Discount : Double)

我正在尝试阅读此 csv:https://github.com/xsankar/fdps-v3/blob/master/data/NW-Order-Details.csv

这是我的代码:

val spark = SparkSession.builder.master(sparkMaster).appName(sparkAppName).getOrCreate()
import spark.implicits._
val orderDetails = spark.read.option("header","true").csv( inputFiles + "NW-Order-Details.csv").as[OrderDetails]

错误是:

 Exception in thread "main" org.apache.spark.sql.AnalysisException: 
 Cannot up cast `UnitPrice` from string to double as it may truncate
 The type path of the target object is:
  - field (class: "scala.Double", name: "UnitPrice")
  - root class: "es.own3dh2so4.OrderDetails"
 You can either add an explicit cast to the input data or choose a higher precision type of the field in the target object;

如果所有字段都是“ double ”值，为什么不能转换？我不明白什么？

Spark 2.1.0 版，Scala 2.11.7 版

Answer 1

您只需要明确地将您的字段转换为 Double :

val orderDetails = spark.read
   .option("header","true")
   .csv( inputFiles + "NW-Order-Details.csv")
   .withColumn("unitPrice", 'UnitPrice.cast(DoubleType))
   .as[OrderDetails]

附带说明一下，根据 Scala(和 Java)约定，您的 case 类构造函数参数应该是小驼峰式:

case class OrderDetails(orderID: String, 
                        productID: String, 
                        unitPrice: Double,
                        qty: Int, 
                        discount: Double)