问题
I'm trying to write a function to operate on RDD[Seq[String]] objects, e.g.:
def foo(rdd: RDD[Seq[String]]) = { println("hi") }
This function cannot be called on objects of type RDD[Array[String]]:
val testRdd : RDD[Array[String]] = sc.textFile("somefile").map(_.split("\\|", -1))
foo(testRdd)
->
error: type mismatch;
found : org.apache.spark.rdd.RDD[Array[String]]
required: org.apache.spark.rdd.RDD[Seq[String]]
I guess that's because RDD isn't covariant.
I've tried a bunch of definitions of foo to get around this. Only one of them has compiled:
def foo2[T[String] <: Seq[String]](rdd: RDD[T[String]]) = { println("hi") }
But it's still broken:
foo2(testRdd)
->
<console>:101: error: inferred type arguments [Array] do not conform to method foo2's type
parameter bounds [T[String] <: Seq[String]]
foo2(testRdd)
^
<console>:101: error: type mismatch;
found : org.apache.spark.rdd.RDD[Array[String]]
required: org.apache.spark.rdd.RDD[T[String]]
Any idea how I can work around this? This is all taking place in the Spark shell.
回答1:
For this you can use a view bound.
Array is not a Seq, but it can be viewed as a Seq.
def foo[T <% Seq[String]](rdd: RDD[T]) = ???
The <% says that T can be viewed as a Seq[String] so that whenever you use a Seq[String] method on T then T will be converted to Seq[String].
For Array[A] to be viewed as Seq[A] there needs to be an implicit function in scope that can convert Arrays to Seqs. As Ionuț G. Stan said, it exists in scala.Predef.
来源:https://stackoverflow.com/questions/23812913/workaround-for-scala-rdd-not-being-covariant