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tagged with all of: rust + performance
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The author discusses the slow build times associated with the Rust compiler when deploying applications in Docker, particularly when using statically linked binaries. By exploring various compilation techniques and tools like cargo-chef, they aim to improve build efficiency while analyzing the performance bottlenecks in the compilation process, specifically focusing on link-time optimization (LTO) and LLVM-related tasks.
UV is a new package manager developed by Astral that addresses the slow performance issues of traditional Python packaging by utilizing innovative techniques such as a static Rust binary, SAT-solving dependency resolution, and optimized installation processes. These advancements lead to significant speed improvements, enabling developers to create virtual environments quickly and streamline their workflows, ultimately allowing them to focus more on coding rather than managing dependencies.
The author reflects on the challenges faced while developing a terminal-based UI library, Ratatui, particularly focusing on performance issues related to diffing changes in frames and the complexity of widget layout management. They explore the trade-offs between maintaining Unicode support and achieving better performance, ultimately considering a new approach to overcome these limitations.
SQLite query optimization significantly improved the performance of the Matrix Rust SDK, boosting event processing from 19,000 to 4.2 million events per second. The article details the structure of data persistence using LinkedChunk and how identifying and addressing inefficiencies in SQL queries led to this enhancement. It emphasizes the importance of profiling tools and strategic indexing to optimize database interactions.
Combining Rust and Java can enhance performance and memory management in applications. This guide details how to integrate Rust into Java projects using JNI, covering topics like packaging native libraries, unifying logging, handling async functions, and mapping errors to exceptions. A practical example is provided to demonstrate these integrations effectively.
Radar has developed HorizonDB, a high-performance geospatial database in Rust, to replace Elasticsearch and MongoDB for their geolocation services. This transition has significantly improved operational efficiency, reduced costs, and enhanced performance, allowing the platform to handle over 1 billion API calls daily with low latency and better scalability.
The first Rust Compiler Performance Survey revealed that while many developers rate their build performance positively, significant challenges remain, particularly with incremental rebuilds and type checking. With over 3,700 responses, the survey highlights diverse workflows and identifies key bottlenecks that affect productivity, prompting plans for ongoing annual surveys to track improvements over time.
OSV is a high-performance CSV parser for Ruby, built using Rust, and offers both hash-based and array-based row formats. It provides significant speed advantages over the standard Ruby CSV library and other CSV gems, especially when using the array-based mode. Users can easily integrate OSV into their applications by adding it to their Gemfile or installing it directly via gem install.
Codex CLI is transitioning to a native version written in Rust to improve cross-platform stability, performance, and security. The new version aims to reduce dependencies, enhance extensibility, and maintain feature parity with the TypeScript implementation. Feedback from the community continues to shape ongoing development, with an invitation for contributors to join the effort.
Rust 1.86.0 has been released, featuring important updates and enhancements aimed at improving performance and usability for developers. Key changes include new language features, library updates, and improved tooling to facilitate more efficient coding practices. This release continues Rust's commitment to safety and concurrency in programming.
Agoda's decision to migrate their Feature Store Serving component from JVM-based languages to Rust was driven by challenges such as unpredictable latency and scaling bottlenecks. The transition not only improved performance and resource efficiency but also allowed the team to leverage Rust's safety guarantees, despite initial concerns over their lack of experience with the language. The migration process included a proof of concept that demonstrated significant performance gains, leading to a successful full implementation.
Rust developers frequently express frustration over the compiler's slow performance and long compilation times, prompting questions about the Rust Project's commitment to addressing these issues. While significant improvements have been made, the complexity of the compiler and the need for careful trade-offs pose challenges to achieving faster build times. The article discusses both the ongoing efforts to enhance compilation performance and the technical hurdles that slow progress.
The article discusses the implementation of a time series engine using Rust, focusing on optimizing performance under heavy load conditions. It highlights various techniques such as throttling to manage resource allocation effectively and ensure system stability during peak usage. Key challenges and solutions in developing a robust time series database are also addressed.
The article introduces Brahma-Firelight, a web framework for Node.js built using Rust, Tokio, and Hyper, which emphasizes memory safety and high performance. It highlights the framework's ability to handle over 130,000 requests per second with low latency, while providing an Express-style API for ease of use by JavaScript developers. Additionally, it includes a quick start guide and performance benchmarks demonstrating its capabilities.