Understanding fsync() and write(): When to Use Each in Linux Programming скачать в хорошем качестве

Understanding fsync() and write(): When to Use Each in Linux Programming

Discover the relationship between `fsync()` and `write()` in Linux programming. Learn the right order to ensure your data is safely written to disk. --- This video is based on the question https://stackoverflow.com/q/73323892/ asked by the user 'Neeraj Sharma' ( https://stackoverflow.com/u/8013131/ ) and on the answer https://stackoverflow.com/a/73329773/ provided by the user 'kjohri' ( https://stackoverflow.com/u/1518661/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Should fsync() be called before or after write() call? Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Understanding fsync() and write(): When to Use Each in Linux Programming When developing applications in C or systems programming on Linux, you often encounter the write() and fsync() system calls. Understanding when to use these functions is critical for ensuring data integrity in your applications. In this guide, we’ll dive into the roles of these two calls and clarify the common confusion surrounding their order of execution. The Role of write() The write() system call is primarily responsible for writing data to a file descriptor. Here’s how it works: Write to Kernel Buffers: When you call write(), the data is sent to the kernel’s buffers. This means that the data isn't immediately written to the physical disk; instead, it resides temporarily in memory. Deferred Writing: The kernel manages these buffers and decides the optimal timing for writing data to disk, often performing batch writes to enhance performance. While write() is an efficient way to handle data, it does not guarantee that the data is saved permanently until it has been flushed to disk. The Purpose of fsync() The fsync() system call is designed to ensure that all data associated with a file descriptor is written and flushed to the disk. Here’s what fsync() does: Flush Buffers: It forces the kernel to write any buffered data to the physical storage device, thus ensuring that the information is safely saved. Metadata Handling: In addition to flushing data, fsync() also ensures that any relevant metadata (like file timestamps) is updated on disk. When to Call fsync() To ensure that your data is securely written to disk, it is crucial to understand the order of calling write() and fsync(). The Correct Order: write() followed by fsync() Write Data First: Start by calling write() to send your data to the kernel buffers. Call fsync() After: Once you’ve confirmed that your data is written using write(), call fsync(). This ensures that all buffered data is flushed to the device. By following this order, you can guarantee that your data is safely stored on disk. Alternative Approach: Using O_SYNC If you're looking for a different method to achieve similar results, consider using the O_SYNC flag with the open() system call: Synchronous Writes: By opening your file with the O_SYNC flag, every subsequent write() call will automatically block until the data is physically written to disk. This means you won’t need a separate fsync() call, as data integrity is maintained at the time of writing. Conclusion In summary, for effective data handling in Linux systems programming: Always call fsync() after a write() call to ensure data integrity. Alternatively, use the O_SYNC flag when opening a file if you prefer synchronous writes. By understanding and implementing these practices, you can significantly reduce the risk of data loss in your applications.