Streaming linear regression using Spark

Using Spark Streaming, it is possible to update the parameters of the linear model online. In many ways, Spark Streaming's linear regression solution works very similarly to the k-means streaming solution.

We will be using the StreamingLinearRegressionWithSGD class that is provided as part of Spark MLlib. To initialize a StreamingLinearRegressionWithSGD object, the following needs to be done:

1. Instantiate the StreamingLinearRegressionWithSGD object using the new StreamingLinearRegressionWithSGD() method
2. Set the number of initial weights
3. We should get a model that can be trained in a streaming fashion and can be used to make predictions

Let's explore this solution in a Spark shell by going through the following steps:

1. Start a Spark shell in your Terminal as follows:

$ spark-shell

2. Stop the current Spark session using the following...