Targeting the streaming engine
You're back with the Seattle library team. Their checkout history is growing, and queries are starting to flirt with memory limits. The simplest fix is to run lazy queries on Polars' streaming engine instead of the default in-memory one.
polars is loaded as pl. The LazyFrame monthly_digital is pre-loaded and totals digital checkouts by month.
This exercise is part of the course
Scaling and Optimizing Data Pipelines with Polars
Exercise instructions
- Run
monthly_digitalusing the streaming engine.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Run the query on the streaming engine
result = monthly_digital.collect(____="____")
print(result)