High-Performance File Searching with Rust: Parallelized Indexing for Enhanced Computational Efficiency

Conventional file explorer tools have many limitations, from sluggish performance to cluttered user interfaces. The Windows File Explorer is often criticized for its slow performance, taking an exorbitant amount of time to load search results, especially for extensive file collections. In contrast, the Rust-based file searcher employs parallelization to rapidly parse the file system and build a comprehensive index. This index is stored in memory using a HashMap data structure, providing constant-time lookups. This study presents a high-performance alternative using the Rust programming language to address these shortcomings. The study shows the advantages of parallelization of search in Rust and then compares file search using Rust and traditional Windows file explorer on multiple parameters, including Search time, CPU usage, and Memory usage. The Rust-Based File Searcher provides faster results at around 80 to 180 milliseconds compared to 4-16 seconds using Windows File Search.