Michael Armbrust created SPARK-11889:
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Summary: Type inference in REPL broken for GroupedDataset.agg
Key: SPARK-11889
URL: https://issues.apache.org/jira/browse/SPARK-11889
Project: Spark
Issue Type: Bug
Reporter: Michael Armbrust
Assignee: Michael Armbrust
Priority: Critical
This works in compiled code, but fails in the REPL.
{code}
/** An `Aggregator` that adds up any numeric type returned by the given
function. */
class SumOf[I, N : Numeric](f: I => N) extends Aggregator[I, N, N] with
Serializable {
val numeric = implicitly[Numeric[N]]
override def zero: N = numeric.zero
override def reduce(b: N, a: I): N = numeric.plus(b, f(a))
override def merge(b1: N,b2: N): N = numeric.plus(b1, b2)
override def finish(reduction: N): N = reduction
}
def sum[I, N : Numeric : Encoder](f: I => N): TypedColumn[I, N] = new
SumOf(f).toColumn
val ds = Seq((1, 1, 2L), (1, 2, 3L), (1, 3, 4L), (2, 1, 5L)).toDS()
ds.groupBy(_._1).agg(count("*"), sum(_._2), sum(_._3)).collect()
{code}
{code}
<console>:38: error: missing parameter type for expanded function ((x$2) =>
x$2._2)
ds.groupBy(_._1).agg(sum(_._2), sum(_._3)).collect()
{code}
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