Till Rohrmann wrote > I'm not sure whether I grasp the whole problem, but can't you split > thevector up into the different rows, group by the row index and then > applysome kind of continuous aggregation or window function?
So I could flatMap my incoming Arrays into (rowId, arrayElement) and gather them appropriately in a window operation.Here is brief code to describe the problem: // Source emits Array[Double] val input: DataStream[Array[Double]] = env.addSource(new MyArraySource()) // Collect windowSize Array[Double] input.countWindowAll(windowSize, slideLength) Now I have a windowSize (representing time) by arrayLength (representing voxels) matrix. Flink lets me parallelize by time easily, but I'd like to parallelize by voxel. -- View this message in context: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Parallelizing-DataStream-operations-on-Array-elements-tp9911p9916.html Sent from the Apache Flink User Mailing List archive. mailing list archive at Nabble.com.
