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  • License
    Apache License 2.0
  • Created over 9 years ago
  • Updated about 1 year ago


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Repository Details

Interactive and Reactive Data Science using Scala and Spark.

Spark Notebook


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

notebook intro

The Spark Notebook allows performing reproducible analysis with Scala, Apache Spark and the Big Data ecosystem.

Features Highlights

Apache Spark

Apache Spark is available out of the box, and is simply accessed by the variable sparkContext or sc.

Multiple Spark Context Support

One of the top most useful feature brought by the Spark Notebook is its separation of the running notebooks. Each started notebook will spawn a new JVM with its own SparkSession instance. This allows a maximal flexibility for:

  • dependencies without clashes
  • access different clusters
  • tune differently each notebook
  • external scheduling (on the roadmap)

Metadata-driven configuration

We achieve maximum flexibility with the availability of multiple sparkContexts by enabling metadata driven configuration.


The Spark Notebook 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.

The Spark Notebook is available for *NIX and Windows systems in easy to use ZIP/TAR, Docker and DEB packages.


All components in the Spark Notebook are dynamic and reactive.

The Spark Notebook comes with dynamic charts and most (if not all) components can be listened for and can react to events. This is very helpful in many cases, for example:

  • data entering the system live at runtime
  • visually plots of events
  • multiple interconnected visual components Dynamic and reactive components mean that you don't have write the html, js, server code just for basic use cases.

Quick Start

Go to Quick Start for our 5-minutes guide to get up and running with the Spark Notebook.

C'mon on to Gitter to discuss things, to get some help, or to start contributing!

Learn more


Skymind - Deeplearning4j

Spark Notebook gives us a clean, useful way to mix code and prose when we demo and explain our tech to customers. The Spark ecosystem needed this.

It allows our analysts and developers (15+ users) to run ad-hoc queries, to perform complex data analysis and data visualisations, prototype machine learning pipelines. In addition, we use it to power our BI dashboards.


Name Logo URL Description
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EMBL European Bioinformatics Institute EMBL - EBI website EMBL-EBI provides freely available data from life science experiments, performs basic research in computational biology and offers an extensive user training programme, supporting researchers in academia and industry.
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kt NexR kt NexR website the kt NexR is one of the leading BigData company in the Korea from 2007.
Skymind website At Skymind, we’re tackling some of the most advanced problems in data analysis and machine intelligence. We offer start-of-the-art, flexible, scalable deep learning for industry.
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Vinted Vinted website Online marketplace and a social network focused on young women’s lifestyle.
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47 Degrees website 47 Degrees is a global consulting firm and certified Typesafe & Databricks Partner specializing in Scala & Spark.
Barclays Barclays website Barclays is a British multinational banking and financial services company headquartered in London.
Swisscom Swisscom website Swisscom is the leading mobile service provider in Switzerland.
Knoldus knoldus website Knoldus is a global consulting firm and certified "Select" Lightbend & Databricks Partner specializing in Scala & Spark ecosystem.