performance

Optimize parsing throughput by applying rayon for parallel file parsing and simd_json for fast JSON processing. This combination speeds up large-scale analysis tasks while satisfying strict latency and memory-usage requirements.

Reduce memory usage by implementing lazy message loading in the TUI and utilizing memory-efficient data structures. This minimizes the memory footprint during active session views and large-scale processing workflows.

Parallel analyzer loading uses futures::join_all() to run stats collection concurrently. This reduces wait times during analyzer initialization and directly improves throughput for real-time analytics workflows.

Yes, rayon and simd_json work together to speed up file parsing. Rayon handles parallel file processing across threads while simd_json accelerates JSON deserialization using SIMD instructions.

Minimize I/O bottlenecks during directory traversal by using jwalk. It provides fast, parallelized directory traversal that significantly reduces the file system I/O wait times encountered during large-scale analysis.

Apply lazy loading to minimize memory footprint during TUI session views, and use parallel processing with rayon or futures to maximize throughput for large-scale parsing and stats collection tasks.