The content introduces Polars, a new data processing library that aims to address the limitations of existing libraries like Pandas and PySpark. Polars is designed with three key goals in mind: simplicity, scalability, and performance.
The article highlights that while Pandas is known for its ease of use and PySpark leads in scalability, Polars aims to combine the best of both worlds. Polars is built to be intuitive and user-friendly, while also delivering top-tier performance on single machines by leveraging modern hardware efficiently.
The author notes that with the increasing availability of powerful machines with large amounts of RAM and CPU cores, it is now more feasible to perform large-scale data processing on a single machine without the overhead of distributed systems. Polars capitalizes on this by utilizing all available cores and optimizing queries with advanced techniques typically seen in database research.
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by Naser Tamimi 게시일 tamimi-naser.medium.com 09-20-2024
https://tamimi-naser.medium.com/polars-dataframe-on-gpu-17059692bc46더 깊은 질문