For business and marketing teams it would be interesting to know which products are most commonly purchased together. For instance:
To answer such questions and gain insights, in this section, we will use Notebooks in QDS to:
Notebooks are great for developing applications in Scala, Python, R, running ETL jobs in Apache Spark, as well as visualizing the results of SQL in a single, collaborative environment.
Note: The default input language for a Spark Notebook is Scala and the default context is SparkContext (sc).
The engine best suited for quick analytics on object relationships is Apache Spark, which is available as a service on QDS.
Note: This is one approach to creating a model that can be used for product recommendations.