Spark Notebook
Interactive and Reactive Data Science using Scala and Spark
...It allows developers, data scientists, and analysts to write, run, and visualize Spark code in cells that support multiple languages such as Scala, Python, and SQL, all within the same notebook. Users can interleave runnable code, rich text markup, visualizations, equations, and results, enabling reproducible research and exploratory data analysis workflows. Because it runs on top of Spark’s distributed engine, it can scale from running locally on a laptop to executing on clusters with large datasets without changing user workflow. The UI is notebook-style with support for incremental execution, error inspection, and stateful session continuity, making it easy to iterate on data transformations and model training tasks.