In the previous recipes, we saw various steps of performing data analysis. In this recipe, let's download the commonly used dataset for movie recommendations. The dataset is known as the MovieLens
dataset. The dataset is quite applicable for recommender systems as well as potentially for other machine learning tasks.
To step through this recipe, you will need a running Spark cluster in any one of the modes, that is, local, standalone, YARN, or Mesos. For installing Spark on a standalone cluster, please refer to http://spark.apache.org/docs/latest/spark-standalone.html. Also, include the Spark MLlib package in the build.sbt
file so that it downloads the related libraries and the API can be used. Install Hadoop (optionally), Scala, and Java.
Let's see how to analyse the MovieLens dataset.
Let's download the
MovieLens
dataset from the following location: https://drive.google.com/file/d/0Bxr27gVaXO5sRUZnMjBQR0lqNDA/view?usp=sharing...