我创建了一个Dataframe作为 MyData1
然后我创建了一个列,这样新的Dataframe就遵循 MyData2
. 现在我想将新的dataframe作为数据集返回,但有以下错误:
[info] org.apache.spark.sql.AnalysisException: cannot resolve '`hashed`' given input columns: [id, description];
[info] at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
[info] at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$3.applyOrElse(CheckAnalysis.scala:110)
[info] at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$3.applyOrElse(CheckAnalysis.scala:107)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:278)
这是我的密码:
import org.apache.spark.sql.{DataFrame, Dataset}
case class MyData1(id: String, description: String)
case class MyData2(id: String, description: String, hashed: String)
object MyObject {
def read(arg1: String, arg2: String): Dataset[MyData2] {
var df: DataFrame = null
val obj1 = new Matcher("cbutrer383", "e8f8chsdfd")
val obj2 = new Matcher("cbutrer383", "g567g4rwew")
val obj3 = new Matcher("cbutrer383", "567yr45e45")
df = Seq(obj1, obj2, obj3).toDF("id", "description")
df.withColumn("hashed", lit("hash"))
val ds: Dataset[MyData2] = df.as[MyData2]
ds
}
}
我知道下面这行可能有点不对劲,但我想不通
val ds: Dataset[MyData2] = df.as[MyData2]
我是个新手,所以可能犯了一个基本的错误。有人能帮忙吗?短暂性脑缺血发作
2条答案
按热度按时间qncylg1j1#
您忘记将新创建的Dataframe分配给
df
df = df.withColumn("hashed", lit("hash"))
withcolumn
spark医生说通过添加列或替换具有相同名称的现有列返回新数据集。
qco9c6ql2#
更好的read函数版本如下:,
尽量避免
null
作业,var
,和return
声明不是必须的