You could easily achieve this by mapPartition. However, it seems that it can not be done by using aggregate type of operation. I can see that it's a general useful operation. For now, you could use mapPartition.
Sincerely, DB Tsai ------------------------------------------------------- My Blog: https://www.dbtsai.com LinkedIn: https://www.linkedin.com/in/dbtsai On Sun, May 4, 2014 at 1:12 AM, Manish Amde <manish...@gmail.com> wrote: > I am currently using the RDD aggregate operation to reduce (fold) per > partition and then combine using the RDD aggregate operation. > def aggregate[U: ClassTag](zeroValue: U)(seqOp: (U, T) => U, combOp: (U, U) > => U): U > > I need to perform a transform operation after the seqOp and before the > combOp. The signature would look like > def foldTransformCombine[U: ClassTag](zeroReduceValue: V, zeroCombineValue: > U)(seqOp: (V, T) => V, transformOp: (V) => U, combOp: (U, U) => U): U > > This is especially useful in the scenario where the transformOp is > expensive and should be performed once per partition before combining. Is > there a way to accomplish this with existing RDD operations? If yes, great > but if not, should we consider adding such a general transformation to the > list of RDD operations? > > -Manish >
