Advanced: Performing Predictive Analytics on the Stream using SAM

Requirement 10 of this use case states the following:

Execute a logistical regression Spark ML model on the events in the stream to predict if a driver is going to commit a violation. If violation is predicted, then alert on it.

HDP, the Hortonworks data at rest platform provides a powerful set of tools for data engineers and scientists to build powerful analytics with data processing engines like Spark Streaming, Hive, and Pig. The following diagram illustrates a typical analytics life cycle in HDP.

Once the model has been trained and optimized, you can create insights by scoring the model in real-time as events are coming in. The next set of steps in the life cycle score the model in real-time using HDF components.

In the next few sections we will walk through how to do steps 5 through 9 in SAM.