This repo supports a presentation I gave to the fall 2023 Multivariate Density Estimation course at Rice university. It's about some software tools I wish I'd known more about in grad-school including:

• spark
• docker
• r packaging
• ray
• git/github
• sql
• automated testing

I only covered half the topics as I split it with another alumnus. The repo is an example of using spark, docker, and ray to explore the tax filings of nonprofits. Here are the main pieces:

1. Run bash download_2023.sh to download the 2023 tax filings.
2. Use either of python/parse_irs_xml.py or r/xml_benchmark.R to parse the data.
3. The point of these files is to show that there are low-effort ways to greatly speed up parsing, not to be exemplary parsing code.

docker build --rm -t my_docker ./docker

docker-compose spark/docker-compose.yml up

docker exec -it spark-rclient-1 /bin/bash

The data will be in the app directory. Play with the data as desired. There are some examples in r/spark_exploration.