Spark SQL is translated to DataFrame operations by the SQL engine. Use whichever is more comfortable for the task. Unless I'm doing something very straight forward, I go with SQL, since any improvement to the SQL engine will improve the resulting DataFrame operations. Hard-coded DataFrame operation won't change even if a better operation becomes available.
On Mon, May 9, 2016 at 10:37 PM Divya Gehlot <divya.htco...@gmail.com> wrote: > Hi, > I would like to know the uses cases where data frames is best fit and use > cases where Spark SQL is best fit based on the one's experience . > > > Thanks, > Divya > > > > > > -- Mathieu Longtin 1-514-803-8977
