Release of Polars 2.0
Polars 2.0 has been released, marking a significant shift toward treating SQL as a first-class citizen within the data processing engine. The update includes major performance optimizations, such as improved join reordering and dynamic predicate pushdown, to compete with engines like DuckDB.
Why it matters
As data engineering workflows increasingly rely on high-performance SQL engines, these optimizations provide developers with faster, more efficient tools for large-scale data analysis.
Today we are shipping Polars 2.0. In the earlier announcement post we went through the rationale of the version bump. This post we will discuss what features 2.0 brings. Even though we didn’t intend to make it a big feature release, it still packs a lot to get enthousiastic about.
Let’s go through the highlights of this release:
Polars 2.0 will be the marking point where we will treat SQL as first class citizen. Polars SQL coverage has increased dramatically over last few months. We know we have been building a solid engine for the last couple of years. In Polars 2.0, we want to enable that to more workloads, including SQL. To make this performant, we shipped many improvements to our optimizer and engine. The highlights here join reordering, much better common-subplan-elimination and dynamic predicates/bloom filters.
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