Improving preemptive prioritization via statistical characterization of OLTP locking

Abstract

OLTP and transactional workloads are increasingly common in computer systems, ranging from e-commerce to warehousing to inventory management. It is valuable to provide priority scheduling in these systems, to reduce the response time for the most important clients, e.g. the "big spenders". Two-phase locking, commonly used in DBMS, makes prioritization difficult, as transactions wait for locks held by others regardless of priority. Common lock scheduling solutions, including non-preemptive priority inheritance and preemptive abort, have performance drawbacks for TPC-C type workloads. The contributions of this paper are two-fold: (i) We provide a detailed statistical analysis of locking in TPC-C workloads with priorities under several common preemptive and non-preemptive lock prioritization policies. We determine why non-preemptive policies fail to sufficiently help high-priority transactions, and why preemptive policies excessively hurt low-priority transactions, (ii) We propose and implement a policy, POW, that provides all the benefits of preemptive prioritization without its penalties.