scala - unsupportedOperationException 使用 Joda 时间将字符串转换为 DateTime 时出错

Question

我正在使用 joda.time.Datetime 库将字符串转换为日期时间字段，但它会抛出不受支持的异常这是主类代码:

//create new var with input data without header
var inputDataWithoutHeader: RDD[String] = dropHeader(inputFile)
var inputDF1 = inputDataWithoutHeader.map(_.split(",")).map{p =>
val dateYMD: DateTime = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss").parseDateTime(p(8))
testData(dateYMD)}.toDF().show()

p(8) 是在类 testData 中定义的数据类型日期时间的列，该列的 CSV 数据的值类似于 2013-02-17 00:00:00

这是 testData 类:

case class testData(StartDate: DateTime) { }

这是我得到的错误:

线程“主”中的异常

java.lang.UnsupportedOperationException: Schema for type org.joda.time.DateTime is not supported
    at org.apache.spark.sql.catalyst.ScalaReflection$class.schemaFor(ScalaReflection.scala:153)
    at org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:29)
    at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$schemaFor$1.apply(ScalaReflection.scala:128)
    at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$schemaFor$1.apply(ScalaReflection.scala:126)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.AbstractTraversable.map(Traversable.scala:105)
    at org.apache.spark.sql.catalyst.ScalaReflection$class.schemaFor(ScalaReflection.scala:126)
    at org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:29)
    at org.apache.spark.sql.catalyst.ScalaReflection$class.schemaFor(ScalaReflection.scala:64)
    at org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:29)
    at org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:361)
    at org.apache.spark.sql.SQLImplicits.rddToDataFrameHolder(SQLImplicits.scala:47)
    at com.projs.poc.spark.ml.ProcessCSV$delayedInit$body.apply(ProcessCSV.scala:37)

Answer 1

1. 正如您在 the official documentation 中所读到的那样Spark SQL 中的日期使用 java.sql.Timestamp 表示。如果你想使用 Joda 时间，你必须将输出转换为正确的类型

2. SparkSQL 可以使用类型转换轻松处理标准日期格式:

   sc.parallelize(Seq(Tuple1("2016-01-11 00:01:02")))
     .toDF("dt")
     .select($"dt".cast("timestamp"))