input data structure

the requirements for input data structure for each advanced analytics task in MLlib.

In the case of classification and regression, you want to get your data into a column of type Double to represent the label and a column of type Vector (either dense or sparse) to represent the features.

• In the case of recommendation, you want to get your data into a column of users, a column of targets (say movies or books), and a column of ratings.

• In the case of unsupervised learning, a column of type Vector (either dense or sparse) is needed to represent the features.

• In the case of graph analytics, you will want a DataFrame of vertices and a DataFrame of edges.

The best way to do this is through transformers.