Demonstration shows preemptive scheduling enhances throughput and fairness in DBMS, prioritizing transactions.
Conventional non-preemptive scheduling strategies struggle to meet the latency requirements of mixed workloads: low-priority, long-running analytics can dominate CPU cores while short, high-priority transactions wait a long time to be scheduled. Although preemptive scheduling appears to be a natural solution, it has long been discouraged in DBMSs by conventional wisdom due to concerns about deadlocks and interrupt-handling overheads. In this demonstration, we highlight that this is no longer the case with PreemptDB, a modern memory-optimized DBMS that we built around (1) optimistic concurrency and (2) userspace interrupts that recently became available in x86 CPUs. PreemptDB proposes user-interruptassisted context switching to renew preemptive scheduling in modern DBMSs. Through a set of demonstration scenarios, we show that preemptive scheduling is practical and prioritizes high-priority transactions while preserving throughput and fairness.
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Zhou et al. (2025) studied this question.
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