Is there a processing speed difference between DataFrames and Datasets?

I've seen a number of visuals showing the processing time benefits of using Datasets+DataFrames over RDDs, but I'd assume that there are performance benefits to using a defined case class instead a generic Dataset[Row]. The tale of three Spark APIs post mentions "If you want higher degree of

Pasting into spark-shell doesn't work for Databricks example

I'm simply pasting in the UDAF example from this page and getting errors (basic EMR setup with Spark 2.0): https://docs.cloud.databricks.com/docs/latest/databricks_guide/index.html#04%20SQL,%20DataFrames%20%26%20Datasets/03%20UDF%20and%20UDAF%20-%20scala.html The imports appear to work, but then

Pasting oddity with Spark 2.0 (scala)

This one has stumped the group here, hoping to get some insight into why this error is happening. I'm going through the Databricks DataFrames scala docs

Re: Newbie question - Best way to bootstrap with Spark

A couple options: (1) You can start locally by downloading Spark to your laptop: http://spark.apache.org/downloads.html , then jump into the Quickstart docs: http://spark.apache.org/docs/latest/quick-start.html (2) There is a free Databricks community edition that runs on AWS: