> > 1) What does this really mean to an Application developer? > It means there are less concepts to learn.
> 2) Why this unification was needed in Spark 2.0? > To simplify the API and reduce the number of concepts that needed to be learned. We only didn't do it in 1.6 because we didn't want to break binary compatibility in a minor release. > 3) What changes can be observed in Spark 2.0 vs Spark 1.6? > There is no DataFrame class, all methods are still available, except those that returned an RDD (now you can call df.rdd.map if that is still what you want) > 4) Compile time safety will be there for DataFrames too? > Slide 7 > 5) Python API is supported for Datasets in 2.0? > Slide 10
