Using HEAVY.AI with JupyterLab

HEAVY.AI Enterprise Edition comes with a fully integrated version of JupyterHub. This provides a secure, multi-user notebook environment for data exploration with OmniSci, and is the primary user interface for the HEAVY.AI Data Science Foundation.

You can quickly switch from visual data exploration, to a Data Science environment preloaded with useful open source libraries and tools that work with OmniSci transparently.

You can access JupyterLab, the next generation Jupyter notebook UI from within Immerse via a button located on the dashboard title

In addition, you can also launch JupyterLab from SQL Editor. In this case, a notebook is opened up with the query wrapped in an Ibis expression.

HEAVY.AI Enterprise allows you to control which users have access to JupyterLab and Data Science tools. This is managed as a separate privilege under the HEAVY.AI role-based permissions model. Refer to the installation instructions for how to set this up for specific users

If you are an HEAVY.AI open source edition user, you do not have access to HeavyImmerse, but you can still explore HEAVY.AI with the Data Science Foundation tools.

Using JupyterLab with HEAVY.AI Open Source Edition requires you to connect to HEAVY.AI explicitly from within a Jupyter notebook cell, using Ibis or py mapd connection syntax. Refer to the Ibis or pyomnisci examples for more details.

Using the Anaconda Package Manager

If you are using the Anaconda package manager, you can install the set of Python tools for HEAVY.AI:

conda install -c conda-forge omnisci-pytools

Using the HEAVY.AI Docker Container for Jupyter tools

You can download a prebuilt Docker container and simply start up these tools as a standalone container.

Tools and Utilities

HEAVY.AI provides a collection utilities to work with JupyterLab.

This is a collection of useful functions and Jupyter cell magics that allows running commands that are typically possible from heavysql from inside a notebook environment.

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Last updated 2 years ago