A few weeks ago I submitted a PR for supporting rdd.drop(n), under SPARK-2315: https://issues.apache.org/jira/browse/SPARK-2315
Supporting the drop method would make some operations convenient, however it forces computation of >= 1 partition of the parent RDD, and so it would behave like a "partial action" that returns an RDD as the result. I wrote up a discussion of these trade-offs here: http://erikerlandson.github.io/blog/2014/07/20/some-implications-of-supporting-the-scala-drop-method-for-spark-rdds/
