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Polars, the Fastest Dataframe Library You Never Heard of.
Speaker: Ritchie Vink

Summary
This talk will introduce Polars, a blazingly fast DataFrame library written in Rust on top of Apache Arrow. Its a DataFrame library that brings exploritory data analysis closer to the lessons learned in database research.

It's the library that puts python in top for OLAP queries. See the excellent query benchmark performances.

Description
This talk will introduce Polars a blazingly fast DataFrame library written in Rust on top of Apache Arrow. Its a DataFrame library that brings exploratory data analysis closer to the lessons learned in database research.

CPU's today's come with many cores and with their superscalar designs and SIMD registers allow for even more parallelism. Polars is written from the ground up to fully utilize the CPU's of this generation.

Besides blazingly fast algorithms, cache efficient memory layout and multi-threading, it consist of a lazy query engine, allowing Polars to do several optimizations that may improve query time and memory usage.

Read more:

https://github.com/pola-rs/polars https://www.ritchievink.com/blog/2021...

Join the talk to learn more.

Ritchie Vink's Bio
Ritchie Vink is just another person who codes too much. He works as a Machine Learning Engineer @Xomnia.bv and in his free time he likes programming/ blogging/ bouldering.
GitHub: https://github.com/ritchie46/
Twitter:   / ritchievink  
LinkedIn:   / ritchievink  
Website: https://www.ritchievink.com//

PyData Global 2021
Website: https://pydata.org/global2021/
LinkedIn:   / pydata-global  
Twitter:   / pydata  

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