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Primary Recommender System: online[matching|ranking...](Flask|Vue) - nearline[model serving|real-time service](Flink|tensorflow serving|redis) - offline[feature engine|model training](Spark|Hdfs(Hbase)|tf)

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Simple Recommender System

What's Important

Maybe in several months, I'll come back to update the repository.(now: 📖🏃🏻‍♂️💖)

what you can do:

  • rs models
  • docker files
  • other fns
  • directly flink to redis (now it seems a trick) [import specific jar]

Contact me: Silvensn@163.com

!!! the system now is really really really rudimentary

Functions

  • similar movies

    image-20220327232506488

  • movies (genres)

    image-20220327232704653

  • recommend for specific user

    image-20220327233147395

  • movies on hot (click shot)

    image-20220327233039243

    image-20220327233147395

Envirenment

front

~ recfront

npm install

npm run dev

back

~ root

make sure: zookeeper kafka(topic: rec3) redis

python3 flinkForRec.py

python3 app.py

  • pyspark 3.0.3
  • pyfink 1.14.4
  • kafka 2.4.0 (scala 2.11) - redis 5.0.9
  • node v14.17.5 npm 6.14.14 ( vue3 element-plus )

Architecture

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Primary Recommender System: online[matching|ranking...](Flask|Vue) - nearline[model serving|real-time service](Flink|tensorflow serving|redis) - offline[feature engine|model training](Spark|Hdfs(Hbase)|tf)

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