Dependence-Cognizant Locking Improvement for the Main Memory Database Systems

The traditional lock manager (LM) seriously limits the transaction throughput of the main memory database systems (MMDB). In this paper, we introduce dependence-cognizant locking (DCLP), an efficient improvement to the traditional LM, which dramatically reduces the locking space while offering efficiency. With DCLP, one transaction and its direct successors are collocated in its context. Whenever a transaction is committed, it wakes up its direct successors immediately avoiding the expensive operations, such as lock detection and latch contention. We also propose virtual transaction which has better time and space complexity by compressing continuous read-only transactions/operations. We implement DCLP in Calvin and carry out experiments in both multicore and shared-nothing distributed databases. Experiments demonstrate that, in contrast with existing algorithms, DCLP can achieve better performance in many workloads, especially high-contention workloads.