To help people that are new to Spark get feedback more easily, we should implement the repr methods for Jupyter python kernels. That way, when users run pyspark in jupyter console or notebooks, they get good feedback about the queries they've defined.
This should include an option for eager evaluation, (maybe spark.jupyter.eager-eval?). When set, the formatting methods would run dataframes and produce output like show. This is a good balance between not hiding Spark's action behavior and getting feedback to users that don't know to call actions.
Here's the dev list thread for context: http://apache-spark-developers-list.1001551.n3.nabble.com/eager-execution-and-debuggability-td23928.html