Synchronous small writes play a critical role in system availability because they safely log recent state modifications for fast recovery from crashes. Demanding systems typically dedicate separate devices to logging for adequate performance during normal operation and redundancy during state reconstruction. However, storage stacks enforce page-sized granularity in data transfers from memory to disk. Thus, they consume excessive storage bandwidth to handle small writes, which hurts performance. The problem becomes worse, as filesystems often handle multiple concurrent streams, which effectively generate random I\/O traffic. In a journaled filesystem, we introduce wasteless journaling<\/i> as a mount mode that coalesces synchronous concurrent small writes of data into full page-sized journal blocks. Additionally, we propose selective journaling<\/i> to automatically activate wasteless journaling on data writes with size below a fixed threshold. We implemented a functional prototype of our design over a widely-used filesystem. Our modes are compared against existing methods using microbenchmarks and application-level workloads on stand-alone servers and a multitier networked system. We examine synchronous and asynchronous writes. Coalescing small data updates to the journal sequentially preserves filesystem consistency while it reduces consumed bandwidth up to several factors, decreases recovery time up to 22%, and lowers write latency up to orders of magnitude.<\/p>\n","protected":false},"excerpt":{"rendered":"
Synchronous small writes play a critical role in system availability because they safely log recent state modifications for fast recovery from crashes. Demanding systems typically dedicate separate devices to logging for adequate performance during normal operation and redundancy during state reconstruction. However, storage stacks enforce page-sized granularity in data transfers from memory to disk. 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