Efficient optimistic concurrency control using loosely synchronized clocks

  • Authors:

  • Atul Adya;Robert Gruber;Barbara Liskov;Umesh Maheshwari

  • Affiliations:

  • Laboratory for Computer Science, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA;Laboratory for Computer Science, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA;Laboratory for Computer Science, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA;Laboratory for Computer Science, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA

  • Venue:
  • SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
  • Year:
  • 1995

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Abstract

This paper describes an efficient optimistic concurrency control scheme for use in distributed database systems in which objects are cached and manipulated at client machines while persistent storage and transactional support are provided by servers. The scheme provides both serializability and external consistency for committed transactions; it uses loosely synchronized clocks to achieve global serialization. It stores only a single version of each object, and avoids maintaining any concurrency control information on a per-object basis; instead, it tracks recent invalidations on a per-client basis, an approach that has low in-memory space overhead and no per-object disk overhead. In addition to its low space overheads, the scheme also performs well. The paper presents a simulation study that compares the scheme to adaptive callback locking, the best concurrency control scheme for client-server object-oriented database systems studied to date. The study shows that our scheme outperforms adaptive callback locking for low to moderate contention workloads, and scales better with the number of clients. For high contention workloads, optimism can result in a high abort rate; the scheme presented here is a first step toward a hybrid scheme that we expect to perform well across the full range of workloads.