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EC-JANE Entertainment launches an innovative film recommendation project utilizing MovieLens data. This project aims to incorporate Big Data analysis and machine learning to enhance movie suggestions, leveraging Apache Spark, Elasticsearch, and a Flask API to provide a personalized and dynamic user experience.

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yassinessadi/movie-recommendation-als-spark

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System Architecture

Flask API (main)

run a Flask API :

cd api

# Debugging is only for development mode.

flask --app main run --debug

by default the id = 1

base url : "http://127.0.0.1:5000/api/movie"

Get the movie by a specific ID.

url : "http://localhost:5000/api/movie?id=10"


|=========================> The expected output:
{
  "age": 60,
  "function": "retired",
  "gender": "M",
  "genre": [
    "Comedy",
    "Drama"
  ],
  "movieId": 45,
  "name": "Eat Drink Man Woman (1994)",
  "number": "95076",
  "rating": 4,
  "release_date": "01-Jan-1994",
  "timestamp": 887736843000,
  "url": "http://us.imdb.com/M/title-exact?Yinshi%20Nan%20Nu%20(1994)",
  "userId": 308
}

Producer:

Consumer:

Flask API (movies-recommendations)

cd api
flask --app mmovies-recommendation run

by default the page = 1 and number of movies = 30

base url : "http://127.0.0.1:5000"

Pagination :

url : "http://localhost:5000/?size=30&page=1"


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EC-JANE Entertainment launches an innovative film recommendation project utilizing MovieLens data. This project aims to incorporate Big Data analysis and machine learning to enhance movie suggestions, leveraging Apache Spark, Elasticsearch, and a Flask API to provide a personalized and dynamic user experience.

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