In a single phrase : if you understand what map() does and what a flatten() might do, then flatMap() is like a map() followed by a flatten().
Like previously said, the concepts in themselves are not Spark specific. Bertrand On Wed, Mar 12, 2014 at 1:19 PM, Xuefeng Wu <ben...@gmail.com> wrote: > It is the same concept with other FP API, > you could learn it from Scala collection map and flatmap > > > http://www.brunton-spall.co.uk/post/2011/12/02/map-map-and-flatmap-in-scala/ > > > Spark doc: > > *map*(*func*) Return a new distributed dataset formed by passing each > element of the source through a function *func*. *flatMap*(*func*) > Similar to map, but each input item can be mapped to 0 or more output > items (so *func* should return a Seq rather than a single item). > > > > > On Wed, Mar 12, 2014 at 7:50 PM, goi cto <goi....@gmail.com> wrote: > >> Hi, >> >> Can someone explain to me the difference between map and flatMap and what >> is a good use case for each? >> >> -- >> Eran | CTO >> > > > > -- > > ~Yours, Xuefeng Wu/吴雪峰 敬上 > >
