Thanks Aljoscha. As I was suspecting, currently there's no unobtrusive way for that, but I can live with it..
Best, Flavio On Tue, Jun 6, 2017 at 3:48 PM, Aljoscha Krettek <aljos...@apache.org> wrote: > Hi, > > There is no way of doing it with any Flink UI but you could try and do it > manually: in your job, instead of doing the actual computation just count > how many elements you have per key (in your GroupReduce). Then put a > MapPartition right after the GroupReduce (which should preserve the same > partitioning) and inside that see what keys you have and how many elements > you had per key. With this you know which partition, i.e. which parallel > instance had which keys and how many they were. > > Best, > Aljoscha > > > On 5. Jun 2017, at 12:01, Flavio Pompermaier <pomperma...@okkam.it> > wrote: > > > > Hi everybody, > > in my job I have a groupReduce operator with parallelism 4 and one of > the sub-tasks takes a huge amount of time (wrt the others). > > My guess is that the objects assigned to that slot have much more data > to reduce (an thus are somehow computationally heavy within the groupReduce > operator). > > What I'm trying to understand which keys are assigned to that slot: is > there any way (from the JobManager UI or from the logs) to investigate the > keys distribution (that from the plan visualization is the result of an > hash partition)? > > > > Best, > > Flavio >
