Spark Notebook is an interactive web-based computational notebook designed to make working with Apache Spark more productive, exploratory, and expressive. 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.
Features
- Multi-language cell execution (Scala, Python, SQL)
- Interactive web notebook interface
- Inline visualizations for data and results
- Seamless Spark cluster integration
- Rich text and markup support
- Integration with external data sources