Lukasaz Thank you for the reply.
I will try apache flink. Thanks, Yu On Sun, Sep 8, 2019 at 11:59 PM Lukasz Cwik <[email protected]> wrote: > 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> >> > -- 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>
