Thank you. Michael
> On Apr 12, 2018, at 2:45 AM, Gary Yao <g...@data-artisans.com> wrote: > > Hi Michael, > > You can configure the default state backend by setting state.backend in > flink-conf.yaml, or you can configure it per job [1]. The default state > backend > is "jobmanager" (MemoryStateBackend), which stores state and checkpoints on > the > Java heap. RocksDB must be explicitly enabled, e.g., by setting state.backend > to > "rocksdb". > > Best, > Gary > > [1] > https://ci.apache.org/projects/flink/flink-docs-master/ops/state/state_backends.html#configuring-a-state-backend > > <https://ci.apache.org/projects/flink/flink-docs-master/ops/state/state_backends.html#configuring-a-state-backend> > > On Wed, Apr 11, 2018 at 11:04 PM, TechnoMage <mla...@technomage.com > <mailto:mla...@technomage.com>> wrote: > I am pretty new to flink and have an initial streaming job working both > locally and remotely. But, both ways if the data volume is too high it runs > out of heap. I am using RichMapFunction to process multiple streams of data. > I assumed Flink would manage keeping state in ram when possible, and spill > to RocksDB when it exceeded heap. > > Is this correct? If so are there configs I need to set to enable or tune > this so it can run within a fixed memory size? > > Michael >
