Spark Notebook – Interactive and Reactive Data Science using Scala and Spark

The Spark Notebook is an open source notebook aimed at enterprise environments, providing data scientists and data engineers with an interactive web-based editor combining Scala code, SQL queries, Markup and JavaScript in a collaborative manner to explore, analyse and learn from massive data sets.

The notebook offers an easy way to prototype Scala/Spark code with SQL queries to analyse data.

Spark is a general-purpose framework for cluster computing.

Features include:

  • Multiple Spark Context Support – each notebook spawns a new JVM with its own SparkSession instance.
  • Perform reproducible analysis with Scala, Apache Spark, and the Big Data ecosystem.
  • Visualize the output of SQL queries directly as tables and charts.
  • Focused on Scala, SQL and Apache Spark.
  • Supports exclusively the Scala programming language, the Unpredicted Lingua Franca for Data Science and extensibly exploits the JVM ecosystem of libraries to drive an smooth evolution of data-driven software from exploration to production.
  • Components in the Spark Notebook are dynamic and reactive.
  • Run Spark Notebook from a secured YARN cluster, Amazon EMR, and Mesosphere Data Center Operating System (DCOS).
  • Various widgets to enrich the interaction with the data.
    • HTML widgets – dedicated to display and interact with data elements. They can be useful to show samples of large datasets, to choose specific data points, or to show continuous updates of streaming data.
    • Graphical widgets – customizable charts ranging from simple line and bar charts to advanced pivot tables and geo-charts.
  • Metadata driven configuration. The metadata in the notebook allows you to configure many runtime aspects of the Spark Notebook, any cluster it connects to, specific library dependencies needed, as well as JVM parameters and definition of variables that describe your environment.

This software requires Java 7 or higher.

Website: spark-notebook.io
Support: Quick Start Guide, GitHub, Twitter, Gitter, Mailing List
Developer: Andy Petrella and contributors
License: Apache License 2.0

Spark Notebook

Spark Notebook is written in JavaScript. Learn JavaScript with our recommended free books and free tutorials.

Return to Data Science Notebooks Home Page


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