DSA Container Images

Please only use the container assigned for your course or approved by your instructor. Failing to do this may compromise resources for other students.

If your are running into resource issues, make sure you are following the advice in Jupyter Server Memory Issues. If this problem persists or is common to students in your course, raise the issue with your instructor. The sysadmin adjusts container resources in conjunction with the instructor and considering system-wide needs.

Each container has specific libraries installed. You can list those libraries with the following two commands in the terminal. Together these two commands will list all the packages. It depends on what was used to install the packages when creating the image.

pip list
conda list # Note: R packages will be prepended with r- before the package name

Another way to list only R packages is from an R notebook, running this code:

my_packages <- as.data.frame(installed.packages()[ , c(1, 3:4)])           
my_packages <- my_packages[is.na(my_packages$Priority), 1:2, drop = FALSE] 
rownames(my_packages) <- NULL
print(my_packages, n = "all")

Note:

  • The Data Science - Database container max memory is adjusted during the course per the instructor's direction, to aid teaching big data concepts.
  • The GEO-AI-GPU container is limited to specific users.
  • The GPUs have 20G memory.

As of November 2025, the following containers are available with the specified resources.

Container

Memory Guarantee

Memory
Max

CPU
Guarantee

CPU
Max

GPU Guarantee

GPU
Max

Data Science - Core

2G

6G

0.5

4

NA

NA

Data Science – R DataViz

2G

8G

0.5

4

NA

NA

NLP

4G

16G

0.5

4

NA

NA

Data Science – Database

2G

4G *

0.5

4

NA

NA

Data Science – Stat Math

4G

8G

1

2

NA

NA

Data Science – DMIR

4G

8G

0.5

4

NA

NA

Data Science – GeoData

4G

32G

0.5

4

NA

NA

DataScience – Data Journalism

2G

7G

0.5

4

NA

NA

Data Science – AWS

2G

4G

1

2

NA

NA

Data Science – GCP

2G

4G

1

2

NA

NA

Alllspark

2G

4G

1

2

NA

NA

Tensorflow – CPU

2G

12G

0.5

4

NA

NA

PyTorch – CPU

2G

6G

0.5

4

NA

NA

Genomics 2

2G

6G

0.5

4

NA

NA

CaseStudy-Capstone

8G

32G

1

4

NA

NA

DSP

2G

16G

0.5

4

NA

NA

Minimal

2G

6G

0.5

4

NA

NA

GEO-AI-GPU*

none

48G

0.5

4

1

1

Need more information or help? Reach out to us at 📧 jcwdw@missouri.edu