spark课程设计作业：银行用户流式判断+垃圾邮件判断+电影推荐系统（三个spark实战项目）.zip

# recommender ### * Building a Recommender with Apache Spark & Elasticsearch ### * This repo contains demo Jupyter notebooks illustrating the basics of how to use Apache Spark for generating ALS models from ratings data stored in Elasticsearch, saving the model factors to ES, and then using ES to serve real-time recommendations using the user and item factors. Requirements * 1.elasticsearch-spark JAR (version 5.3.0) on the classpath (https://www.elastic.co/downloads/past-releases/elasticsearch-apache-hadoop-5-3-0). * 2.Spark 2.1.x (http://spark.apache.org/downloads.html). * 3.Running instance of Elasticsearch 5.3.0 (https://www.elastic.co/downloads/past-releases/elasticsearch-5-3-0). * 4.Elasticsearch vector scoring plugin installed (https://github.com/MLnick/elasticsearch-vector-scoring). * 5.Jupyter (pip install jupyter).