Hi, could you tell me how exactly you started the cluster and with which parameters (configured memory, maybe vcores, etc.)?
Cheers, Till On Thu, Jan 3, 2019 at 2:37 AM varuy322 <rui2.w...@intel.com> wrote: > Hi, Till > It's very kind of your reply. I got your point, I'm sorry to not make it > clear about my issue. > I generated data by streaming benchmark just as the link: > > https://github.com/dataArtisans/databricks-benchmark/blob/master/src/main/scala/com/databricks/benchmark/flink/EventGenerator.scala > . > > What I wanna to say is that, let the parallelism is same assume to 96, just > changes the tm and slots/tm. The first test to configure tm 3 with 32 > slots/tm, there does not occur data skew, three machine receive same data > and each partition processed approximate data. Then second test to > configure > tm 6 with 16 slots/tm, I find each partition processed same data too, but > one machine processed data more than the other two machine. > > I wonder whether the taskmanager(jvm) competes in one machine? What's more, > how does the streaming benchmark do with backpressure? I test on cluster > with 4 node, one for master and three for worker, each node with Intel Xeon > E5-2699 v4 @ 2.20GHz/3.60GHz, 256G memory, 88 cores, 10Gbps network, I > could > not find the bottleneck. It confused me! > > Best Regards & Thanks > > Rui > > > > ----- > stay hungry, stay foolish. > -- > Sent from: > http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/ >
