A little over a year ago, I got curious about the 1 Billion Row Challenge (1BRC). It seemed like the perfect playground to test Rust’s performance chops — 1 billion weather station measurements, aggregate per-city statistics (min, max, average), and ...
Apache Arrow is an in-memory columnar data format optimized for analytical workloads. It enables fast data access, zero-copy reads, and efficient interoperability between systems like Pandas, DuckDB, Polars, and query engines like Apache DataFusion. ...
Introduction Parquet has quickly become one of the most popular file formats for storing large-scale analytics data. Parquet is now a top choice due to its efficiency, compression, and seamless integration with big data frameworks. My experience cont...
🚀 Introduction My journey into query engines, databases, and Rust began with curiosity and a passion for systems-level performance. Rust's promise of safety and efficiency drew me in, while databases provided the perfect playground to test its capab...
Intro about Datafusion Apache DataFusion is a Rust-native query engine with a powerful optimizer. One key component of its optimizer is expression simplification, often referred to as the simplify function. In this post, we'll walk through how we imp...
Implementing the trie data structure in typescript
