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Jupyter Server Memory Issues

Some common errors or symptoms you may see due to memory issues: * "Unexpected error while saving file" * "Error loading notebook Unreadable notebook: <path to notebook" MemoryError()" * "An unknown error occurred while loading this notebook. This version can load notebook formats or earlier. See

Moving data files to your group data share

The Case Study and Capstone teams are assigned team data shares to store all their data files. Data files are not to be committed to your shared repository. Instructions: 1. Open a terminal on Jupyter. 2. Although files can be moved directly from the Jupyter terminal, we recommend that you

Error Loading Notebook - Unreadable Notebook

Problem: You receive an error message "Unreadable Notebook: <path to a notebook> NotJSONError("Notebook does not appear to be JSON: "...") Solution: If you look in the Jupyter directory for the notebook, you may see that there is another copy of the file with an

Installing the University AnyConnect VPN

To access any of the DSA GitLab servers you need to either be on the university network or connect via VPN. To download and install the university’s AnyConnect VPN client: 1. Go to https://anyconnect.missouri.edu. 2. Click on Login. 3. Sign in with your username@umsystem.edu

Downloading Datasets

Some of our students desire to download notebooks and datasets and work on your personal computers. We do not recommend your personal computers for completing your normal course work. The JupyterHub environment and our containers have been tested to work with the course materials, and provide a standardized environment. Our

GPU Resources

Overview There are several GPU nodes in the Europa cluster available to DSA students. * 2 3x GPU nodes * 2 1x GPU nodes Card Model: * Nvidia Tesla P100 GPUs [https://www.nvidia.com/en-us/data-center/tesla-p100/] * CUDA Capability: 6.0 (Pascal Gen) * Device Memory: 12 GiB Node Configuration: * at least 4

Maintanenace Windows

Maintanenace Windows

Regular Weekly Maintenance Windows * Every Friday from 10:00 AM to 12:00 PM (CST/CDT) * "All Clear" will always be announced in the Datagoggles Slack General channel when systems are back online and ready for use. Look for "Systems are back online and ready. Faculty and

Install conda packages locally

Install conda packages locally

Below is code that can be installed into a code cell of a jupyter notebook to install conda packages. !conda install opencv Please note that once your container stops and restarts this will reset any change in the environment. Your packages will not persist after a session restart.

Install R Packages Locally

Install R Packages Locally

To install an R Package, insert the below into a code cell. install.packages("rtweet") Please note that once your container stops and restarts this will reset any change in the environment. Your packages will not persist after a session restart.

How to reset a Jupyter notebook(to resolve kernel crashes)

How to reset a Jupyter notebook(to resolve kernel crashes)

A guide to clearing the output of Jupyter notebooks when the results of a code cell makes them unresponsive.

Switching Containers

Switching Containers

This is a quick guide for how to switch your current running environment/container. Let's start logged in running the Core container. Click Control Panel Click "Stop My Server" Wait a few seconds for the "Stop My Server" button to disappear. Once "Start

Leda

Leda is our Legacy Jupyterhub. This machine is meant for accessing notebooks that may not be directly compatible with the Data Science container on Europa. Leda uses a single virtual machine that with a moderate amount of resources to allow for legacy notebook access. This machine is not intended for

Group Jupyterhub VMs

Group Jupyterhub VMs

Access Group Workspace Login C2019GXX.dsa.missouri.edu C2019G01, C2019G02, C2019G03 Click Control Panel Click on Admin Start Jovyan server Access Jovyan server The Jovyan is the group account where your collaboration will happen. Your login account will not be shared with the group. Install Packages As Jovyan user launch

Using Course Containers

Using Course Containers

What is Docker and how do we use it? Docker is a container platform that allows us to package Jupyter notebooks into deliverable course environments. Install Docker Locally Windows https://docs.docker.com/docker-for-windows/install/ Mac https://docs.docker.com/docker-for-mac/install/ Linux https://docs.docker.com/install/ Take a

Container Catalog

Container Catalog

Below are the base containers and their hierarchy. Since some containers only build on the previous, not all of these are available on Europa. * Base - Best for Building a completely customized environment (Not Available on Europa) * Minimal - Includes basic Python 3 kernel and packages (Not Available on Europa)

SSH Landing Zone

SSH Landing Zone

DSA supports ssh/sftp for more direct access to your data. How do I connect? Address ssh username@lz.dsa.missouri.edu Windows Users Please refrence RCSS [http://docs.rnet.missouri.edu/HowTo/mobaxterm] Documentation for MobaXterm Campus/VPN Password Authentication is allowed when on campus or using Anyconnect [anyconnect.

Spawning Notebooks

Spawning Notebooks

Login When you first login you will click the "Start My Server" button. Select Container Select the desired container image that is relavent to relavent to the course materal being worked on. For a list of images and their packages click here. Note: The items under the "

R Shiny Web Hosting

R Shiny Web Hosting

R Shiny Web Hosting R Shiny Server Commercial Edition R Version 3.4.1 Hosting is based on files put in the ShinyApps folder in a users home directory. /dsa/home/<Pawprint>/ShinyApps/ or ~/ShinyApps/ The Web URL for accessing user's hosted directory:This will be

Apache Web Hosting

Apache Web Hosting

Apache 2.4 W/ PHP version 7.2 Hosting is based on files put in the public_html folder in a users home directory. This path can be accessed via ssh on lz.dsa.missouri.edu or Europa's web based terminal. /dsa/home/<Pawprint>/public_html/

Europa

Europa is our Primary Jupyterhub. This machine is meant for the bulk of your Data Science & Analytics course work. Europa uses a Kubernetes cluster that allows for flexible resources that coincide with coursework needs. Base Resource Limits: * 2 cores * 4 GB RAM * 1 GB SWAP * 95 GB Shared Storage

Install Python Packages Locally

Install Python Packages Locally

Below is code that can be inserted into a cell of a Jupyter notebook to install python packages. #Define PIP Installer import pip def install(package): pip.main(['install','--upgrade', package]) #Notebook Requirements install('pip') install('jinja2') Alternatively, you can use the