Thanks for the confirmation, Fabian.
*Regards,* *Abhishek Kumar Singh* *Search Engine Engineer* *Mob :+91 7709735480 * *...* On Sat, May 25, 2019 at 8:55 PM Fabian Hueske <fhue...@gmail.com> wrote: > Hi Abhishek, > > Your observation is correct. Right now, the Flink ML module is in a > half-baked state and is only supported in batch mode. > It is not integrated with the DataStream API. FLIP-23 proposes a feature > that allows to evaluated an externally trained model (stored as PMML) on a > stream of data. > > There is another effort to implement a new machine learning API / > environment based on the Table API. This will be supported for batch and > streaming sources. > However, this effort just started and the features is not available yet. > > Best, Fabian > > Am So., 19. Mai 2019 um 11:54 Uhr schrieb Abhishek Singh < > asingh2...@gmail.com>: > >> >> Thanks again for the above resources. >> >> I went through the project and also ran the example on my system to get a >> grasp of the architecture. >> >> However, this project does not use Flink ML in it at all. >> >> Also, after having done enough research on Flink ML, I also found that it >> does not let us persist the model, that's why I am not able to re-use the >> model trained using Flink ML. >> >> It looks like Flink ML cannot really be used for real-life use cases as >> it neither lets us persist the trained model, nor can it help us to use the >> trained model on a *DataStream*. >> >> Please correct me if I am wrong. >> >> >> >> >> *Regards,* >> *Abhishek Kumar Singh* >> >> *Search Engine Engineer* >> *Mob :+91 7709735480 * >> >> >> *...* >> >> >> On Wed, May 15, 2019 at 11:25 AM Abhishek Singh <asingh2...@gmail.com> >> wrote: >> >>> >>> Thanks a lot Rong and Sameer. >>> >>> Looks like this is what I wanted. >>> >>> I will try the above projects. >>> >>> *Regards,* >>> *Abhishek Kumar Singh* >>> >>> *Search Engineer* >>> *Mob :+91 7709735480 * >>> >>> >>> *...* >>> >>> >>> On Wed, May 15, 2019 at 8:00 AM Rong Rong <walter...@gmail.com> wrote: >>> >>>> Hi Abhishek, >>>> >>>> Based on your description, I think this FLIP proposal[1] seems to fit >>>> perfectly for your use case. >>>> you can also checkout the Github repo by Boris (CCed) for the PMML >>>> implementation[2]. This proposal is still under development [3], you are >>>> more than welcome to test out and share your feedbacks. >>>> >>>> Thanks, >>>> Rong >>>> >>>> [1] >>>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-23+-+Model+Serving >>>> [2] https://github.com/FlinkML/flink-modelServer / >>>> https://github.com/FlinkML/flink-speculative-modelServer >>>> [3] https://github.com/apache/flink/pull/7446 >>>> >>>> On Tue, May 14, 2019 at 4:44 PM Sameer Wadkar <sam...@axiomine.com> >>>> wrote: >>>> >>>>> If you can save the model as a PMML file you can apply it on a stream >>>>> using one of the java pmml libraries. >>>>> >>>>> Sent from my iPhone >>>>> >>>>> On May 14, 2019, at 4:44 PM, Abhishek Singh <asingh2...@gmail.com> >>>>> wrote: >>>>> >>>>> I was looking forward to using Flink ML for my project where I think I >>>>> can use SVM. >>>>> >>>>> I have been able to run a bath job using flink ML and trained and >>>>> tested my data. >>>>> >>>>> Now I want to do the following:- >>>>> 1. Applying the above-trained model to a stream of events from Kafka >>>>> (Using Data Streams) : For this, I want to know if Flink ML can be used >>>>> with Data Streams. >>>>> >>>>> 2. Persisting the model: I may want to save the trained model for some >>>>> time future. >>>>> >>>>> Can the above 2 use cases be achieved using Apache Flink? >>>>> >>>>> *Regards,* >>>>> *Abhishek Kumar Singh* >>>>> >>>>> *Search Engineer* >>>>> *Mob :+91 7709735480 * >>>>> >>>>> >>>>> *...* >>>>> >>>>>
