The state of Direct IO in Postgres

About this video

### Summary: 1. **Linux Kernel Cache and Direct I/O**: - The system can extract data from the Linux kernel page cache. - By default, the system uses the page cache for operations. - Direct I/O is an option but should rarely be enabled due to inefficiencies. 2. **Direct I/O Characteristics**: - Direct I/O bypasses the page cache, reducing CPU overhead when copying data between kernel and user space. - However, it eliminates caching benefits, making every read/write operation slower. - This approach avoids double caching issues but is unsuitable for most use cases. 3. **Performance Implications**: - With Direct I/O, all reads and writes directly access the disk, which is significantly slower, especially in cloud or networked environments like NAS systems. - Enabling Direct I/O (e.g., via "debug io direct" settings) can drastically slow down operations, as demonstrated in PostgreSQL. 4. **Challenges with Direct I/O**: - Blindly enabling Direct I/O across systems is problematic because small, frequent read/write operations remain inefficient. - Developers are still working on optimizing Direct I/O for broader use cases. 5. **Asynchronous I/O and Concurrency**: - Asynchronous I/O is a related concept aimed at improving performance by allowing non-blocking operations. - PostgreSQL has started implementing worker threads to handle I/O tasks asynchronously, freeing up backend processes for other tasks. 6. **Code Rewrite Necessity**: - Merely enabling asynchronous I/O does not solve all problems; code must be rewritten to take full advantage of non-blocking operations. 7. **Broader Challenges**: - Operating systems like Windows and features like Direct I/O present unique challenges in implementation. - The discussion highlights the complexity of achieving optimal I/O performance. 8. **Developer Passion and Craftsmanship**: - The speaker emphasizes the importance of craftsmanship and passion in software development. - Despite frustrations and long development cycles (e.g., five years for a single feature), dedication to the craft drives progress. 9. **Engagement and Support**: - The speaker expresses gratitude for the audience's support and acknowledges their enthusiasm for technical details. 10. **Key Takeaways**: - Synchronous vs. asynchronous I/O is a critical concept in system performance. - Optimizing I/O requires balancing trade-offs, such as CPU overhead vs. caching benefits. - Progress in this area is ongoing, with significant efforts to improve efficiency and scalability. This summary captures the technical insights, challenges, and philosophical reflections shared in the text.

Course: OS Fundamentals

### Course Description: OS Fundamentals The **OS Fundamentals** course provides a comprehensive exploration of core operating system concepts, focusing on process management, scheduling, and resource allocation in Linux-based systems. Students will gain hands-on knowledge of how processes are prioritized and managed within the Linux environment, including an in-depth understanding of "niceness" values and their impact on CPU resource distribution. The course begins with foundational topics such as assigning priority levels to processes, where values range from -20 (highest priority) to 19 (lowest priority). Through practical demonstrations using tools like `top` and `renice`, students will learn how to monitor and adjust process priorities dynamically, ensuring optimal system performance. Additionally, the course delves into advanced concepts such as real-time processes and their dominance over standard processes, equipping learners with the skills to manage complex workloads effectively. A significant portion of the course is dedicated to understanding workload types and their implications for system scalability. Students will explore two primary categories of workloads: I/O-bound and CPU-bound tasks. Using real-world examples, such as PostgreSQL for I/O-bound applications and custom C programs for CPU-intensive tasks, learners will analyze how different workloads affect system resources. The course emphasizes the importance of vertical scaling (adding more resources to a single machine) versus horizontal scaling (distributing workloads across multiple machines) and provides strategies for achieving cost-effective scalability. By leveraging Linux commands like `top`, students will gain insights into CPU metrics, memory usage, and system-level operations, enabling them to diagnose and optimize performance bottlenecks. Throughout the course, students will engage in interactive experiments using Raspberry Pi devices, simulating multi-core environments to observe process behavior under varying conditions. These hands-on exercises will reinforce theoretical concepts and encourage creative problem-solving. By the end of the course, participants will have a solid grasp of Linux process management, workload optimization, and system monitoring techniques. Whether you're a beginner looking to understand the basics of operating systems or an experienced developer aiming to enhance your system administration skills, this course offers valuable insights and practical tools to help you succeed in managing modern computing environments.