Add notebook for Bokeh

"[Bokeh](http://bokeh.pydata.org/en/latest/) is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of novel graphics in the style of D3.js, but also deliver this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications."

Bokeh seems like a good candidate to feed data from Spark streaming and sharing results to stakeholders who don't use visualization tools like Tableau.

[Bokeh at Pycon](https://www.youtube.com/watch?v=O5OvOLK-xqQ)

No target notebook, test, or entry point is named. Review the repository's existing notebook organization and the linked Bokeh overview first, then determine how a notebook should demonstrate Bokeh with data relevant to Spark streaming; done means a complete, runnable Bokeh notebook is added in the established style.

Written by the indexing model from the issue text.