Hi Pedro, currently, Flink does not allow you to explicitly control the scheduling strategy at such a fine grained level. The idea behind this is to achieve location transparency and to make the scheduling easier.
However, there are some tricks you could play depending on the actual job. For example, given that the async operator is the operator with the highest degree of parallelism p, you could set the number of slots per TM to p / #number TMs. That way Flink would use all of the available slots. If the parallelism of the async operator is currently below p, then it might be feasible to increase it to p and to decrease the number of concurrent async calls per async operator. Cheers, Till On Fri, Apr 20, 2018 at 2:30 PM, PedroMrChaves <pedro.mr.cha...@gmail.com> wrote: > That is only used to split the load across all of the subtasks, which am > already doing. > It is not related with the allocation. > > > > ----- > Best Regards, > Pedro Chaves > -- > Sent from: http://apache-flink-user-mailing-list-archive.2336050. > n4.nabble.com/ >
