Try using Apache Flink. On Sun, Sep 8, 2019 at 6:23 AM Yu Watanabe <[email protected]> wrote:
> Hello . > > I would like to ask question related to timely processing as stated in > below page. > > https://beam.apache.org/blog/2017/08/28/timely-processing.html > > Python version: 3.7.4 > apache beam version: 2.15.0 > > I currently use timely processing to first buffer events and send *bulk > requests *to elasticsearch. The source of data is bounded source and I > use DirectRunner for runner. > > To have more memory resource , I am considering to move to process the > pipeline on apache spark using portable runner. However, according to > compatibility matrix, > *Timers *is not supported on apache spark. > > > https://beam.apache.org/documentation/runners/capability-matrix/#cap-summary-when > > Is there anyway in portable runner that you can do similar processing as > *timely > processing* ? > This is my first time using portable runner and I appreciate if I can get > help with this. > > Best Regards, > Yu Watanabe > > -- > Yu Watanabe > Weekend Freelancer who loves to challenge building data platform > [email protected] > [image: LinkedIn icon] <https://www.linkedin.com/in/yuwatanabe1> [image: > Twitter icon] <https://twitter.com/yuwtennis> >
