analyzing-chicago-crimes

Analyzing Chicago Crimes

In this recipe we'll learn how to analyze the Chicago Crimes dataset with Apache Pinot and Streamlit

Pinot Version	0.9.0
Schema	config/schema.json
Table Config	config/table.json
Ingestion Job	config/job-spec.yml

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Clone this repository and navigate to this recipe:

git clone git@github.com:startreedata/pinot-recipes.git
cd pinot-recipes/recipes/analyzing-chicago-crimes

Download the Chicago Crimes dataset:

curl "https://data.cityofchicago.org/api/views/ijzp-q8t2/rows.csv?accessType=DOWNLOAD&bom=true&query=select+*" -o data/Crimes_-_2001_to_Present.csv

Setup Python environment:

pipenv shell
pipenv install

Clean up the data so that it's sorted by the Beat column:

python data_cleanup.py

Spin up a Pinot cluster using Docker Compose:

docker-compose up

Open another tab to add the crimes table:

docker exec -it manual-pinot-controller-chicago bin/pinot-admin.sh AddTable   \
  -tableConfigFile /config/table.json   \
  -schemaFile /config/schema.json \
  -exec

Import Chicago Crimes CSV file into Pinot:

docker exec -it manual-pinot-controller-chicago bin/pinot-admin.sh LaunchDataIngestionJob \
  -jobSpecFile /config/job-spec.yml \
  -values pinot-controller

Run Streamlit app:

streamlit run app.py

Navigate to http://localhost:8501/