Michael Armbrust created SPARK-11889: ----------------------------------------
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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org