CodeRayZhang/Movie_Recommend

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3007 stars · 1051 forks observed · 2026-08-28

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

A full-stack movie recommendation system built on Spark, including a Scrapy crawler, an SSM-based movie website, an admin backend, and a Spark streaming recommendation engine using Hadoop, Kafka, Hive, and MySQL. It serves real-time personalized movie recommendations based on user click and rating events.

Use cases

• build a movie recommendation website
• learn how to build a spark recommendation system
• real-time recommendations from user click events
• scrape movie data with scrapy
• end-to-end big data recommendation pipeline example
• spark mllib collaborative filtering project

When to choose

• learning big data and Spark recommendation architectures end to end
• you want a complete reference project covering crawler, web frontend, admin, and recommendation engine
• teaching or studying Spark MLlib and streaming in a realistic system

When to avoid

• you need a production-ready, actively maintained recommender
• you want a lightweight solution without a Hadoop/Spark cluster
• your stack is not Java/Scala/Python on Linux

Facets

application · maturity maintenance

machine-learning web-scraping web-framework streaming data-science search-engine machine-learning big-data web-development e-commerce python jvm spark-mllib recommendation-system collaborative-filtering scrapy ssm kafka hive movie-recommendation big-data-pipeline data-engineering linux web-server docker

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For agents

markdown · JSON · MCP: product_card(name="CodeRayZhang/Movie_Recommend")