Open up spark-linear-regression.py file and have a look at the code. First we'll import, from the ML library, a regression, a LinearRegression class:
from pyspark.ml.regression import LinearRegression
Note that we're using ml instead of MLlib here. ml is basically where the new data frame APIs live, and going forward, that's going to be where Spark wants you to start using these. We're also going to import SparkSession and Vectors, which we're going to need in order to represent our feature data within our algorithm:
from pyspark.sql import SparkSession from pyspark.ml.linalg import Vectors
Let's go ahead and look at the script itself, down in line 11. We'll start by creating a SparkSession ...
