Analytics Are Heavy. The DBMS Is Busy. When Will My Mission-Critical Transaction Start Running?

  • Jiatang Zhou
  • , Kaisong Huang
  • , Zhuoyue Zhao
  • , Dong Xie
  • , Tianzheng Wang

Research output: Contribution to journalConference articlepeer-review

Abstract

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, highpriority 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.

Original languageEnglish (US)
Pages (from-to)5299-5302
Number of pages4
JournalProceedings of the VLDB Endowment
Volume18
Issue number12
DOIs
StatePublished - 2025
Event51st International Conference on Very Large Data Bases, VLDB 2025 - London, United Kingdom
Duration: Sep 1 2025Sep 5 2025

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • General Computer Science

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