water8394/flink-recommandSystem-demo

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

4480 stars · 1478 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A real-time product recommendation system built on Apache Flink, demonstrating streaming computation of product popularity, user profiles, and collaborative filtering with data stored in Redis and HBase. It includes a web front end for serving recommendations and an admin dashboard showing real-time metrics.

Use cases

• build a real-time recommendation engine with Flink
• learn how to combine collaborative filtering and tag-based recommendations
• compute real-time product popularity rankings from Kafka logs
• store user browsing history and profiles in HBase via Flink jobs
• serve personalized re-ranked hot product lists to users
• display real-time recommendation metrics on a data dashboard

When to choose

• you want a reference implementation of a streaming recommendation pipeline in Java/Flink
• you need to learn Flink windowing, state management, and Kafka/HBase/Redis integration
• you are prototyping an e-commerce recommendation system with Docker-based deployment

When to avoid

• you need a production-grade, maintained recommendation platform with a license and active support
• you want a turnkey recommender library rather than a demo application
• your stack does not include Flink, Kafka, HBase, and Redis

Facets

application · maturity maintenance

streaming machine-learning caching database data-visualization etl big-data e-commerce analytics jvm self-hosted flink recommendation-system collaborative-filtering kafka hbase redis real-time-recommendation user-profiling demo-project data-engineering real-time docker

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