Notebooks on Redivis provide an integrated environment for performing data analysis, connecting Redivis tables to the open-source community and scientific compute stack. Redivis notebooks are built on top of Jupyter notebooks and the
.ipynb notebook format.
From within a notebook, you will be able to query and analyze any data that you have access to. Importantly, because data referenced in a notebook never leaves Redivis, you can securely analyze data that would otherwise be bound by export restrictions.
On your workspace, navigate to the Notebooks tab to view and manage your notebooks. To open an existing notebook, double-click on that notebook. Right click on a notebook to change its name or type, to copy it, or to delete it.
After 30 minutes of inactivity, any running notebook will automatically be stopped. If this happens when the notebook is still open (e.g., in another tab), you may see "Kernel disconnected" errors. Reload the page or return to your workspace to restart the notebook.
Redivis notebooks are designed as an analytical interface, whose output is the code and figures in the notebook itself. While you can use the attached hard disk as a temporary scratch space during your analysis, all content outside of the notebook file will be cleared when the notebook is restarted. To persist the outputs of data manipulation, we suggest utilizing the various tools in the project interface.
Notebooks are currently deployed with access to 2 CPUs and 8GB working memory, alongside a 100GB hard disk. These values may fluctuate based on system utilization.
In order to use Stata notebooks, you must have a valid license for Stata version 17, or be a member of an organization that provides such a license. Please contact us if you would like to add a Stata license.
Stata notebooks are built on top of Python notebooks, and come with the officially-supported pystata package pre-installed and configured. This package provides a
%%stata magic command (among others), allowing you to pass data from a python dataframe and execute arbitrary stata code.
In order to use SAS notebooks, you must have a valid license for SAS 9.4, or be a member of an organization that provides such a license. Please contact us if you would like to add a SAS license.
SAS notebooks are built on top of Python notebooks, and come with the officially-supported saspy package pre-installed and configured. This package provides an interface to pass data from a python dataframe and execute arbitrary SAS code.
The following are known issues in the alpha that will be addressed before wider release.
By default, notebooks autosave every 2 minutes. When navigating away from the page, it is possible that recent changes to your notebook will not be saved. To ensure that you don't lose any work, make sure to manually save (ctrl/cmd + s) before closing your notebook.
In some instances, a notebook may take several minutes to start (typically, you can expect <10s). If a notebook is taking a while to start, try reloading the page, or force-stopping and then restarting the notebook.
Notebooks cannot currently be shared with other users. Notebook collaboration is planned for a future release.
Opening the same notebook in multiple tabs / windows may lead to unexpected behavior, where one window overwrites the save progress of another. Make sure to only have one instance of each notebook open a time.