<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Low-Latency Transaction Scheduling via Userspace Interrupts: Why Wait or Yield When You Can Preempt?</dc:title><dc:creator>Huang, Kaisong (ORCID:0000000179195426); Zhou, Jiatang (ORCID:0009000454209579); Zhao, Zhuoyue (ORCID:000000021631718X); Xie, Dong (ORCID:000000034857900X); Wang, Tianzheng (ORCID:0000000309659592)</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Traditional non-preemptive scheduling can lead to long latency under workloads that mix long-running and short transactions with varying priorities. This occurs because worker threads tend to monopolize CPU cores until they finish processing long-running transactions. Thus, short transactions must wait for the CPU, leading to long latency. As an alternative, cooperative scheduling allows for transaction yielding, but it is difficult to tune for diverse workloads. Although preemption could potentially alleviate this issue, it has seen limited adoption in DBMSs due to the high delivery latency of software interrupts and concerns on wasting useful work induced by read-write lock conflicts in traditional lock-based DBMSs.&lt;/p&gt; &lt;p&gt;In this paper, we propose PreemptDB, a new database engine that leverages recent userspace interrupts available in modern CPUs to enable efficient preemptive scheduling. We present an efficient transaction context switching mechanism purely in userspace and scheduling policies that prioritize short, high-priority transactions without significantly affecting long-running queries. Our evaluation demonstrates that PreemptDB significantly reduces end-to-end latency for high-priority transactions compared to non-preemptive FIFO and cooperative scheduling methods.</dc:description><dc:publisher>ACM</dc:publisher><dc:date>2025-06-17</dc:date><dc:nsf_par_id>10672205</dc:nsf_par_id><dc:journal_name>Proceedings of the ACM on Management of Data</dc:journal_name><dc:journal_volume>3</dc:journal_volume><dc:journal_issue>3</dc:journal_issue><dc:page_range_or_elocation>1 to 25</dc:page_range_or_elocation><dc:issn>2836-6573</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1145/3725319</dc:doi><dcq:identifierAwardId>2339596</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>