Optimizations

If you use Polars' lazy API, Polars will run several optimizations on your query. Some of them are executed up front, others are determined just in time as the materialized data comes in.

Here is a non-complete overview of optimizations done by polars, what they do and how often they run.

Optimization	Explanation	runs
Predicate pushdown	Applies filters as early as possible/ at scan level.	1 time
Projection pushdown	Select only the columns that are needed at the scan level.	1 time
Slice pushdown	Only load the required slice from the scan level. Don't materialize sliced outputs (e.g. join.head(10)).	1 time
Common subplan elimination	Cache subtrees/file scans that are used by multiple subtrees in the query plan.	1 time
Simplify expressions	Various optimizations, such as constant folding and replacing expensive operations with faster alternatives.	until fixed point
Join ordering	Estimates the branches of joins that should be executed first in order to reduce memory pressure.	1 time
Type coercion	Coerce types such that operations succeed and run on minimal required memory.	until fixed point
Cardinality estimation	Estimates cardinality in order to determine optimal group by strategy.	0/n times; dependent on query