Scaling Multicore Databases Via Constrained Parallel Execution
SIGMOD/PODS'16: International Conference on Management of Data San Francisco California USA June, 2016(2016)
摘要
Multicore in-memory databases often rely on traditional con currency control schemes such as two-phase-locking (2PL) or optimistic concurrency control (OCC). Unfortunately, when the workload exhibits a non-trivial amount of contention, both 2PL and OCC sacrifice much parallel execution opportunity. In this paper, we describe a new concurrency control scheme, interleaving constrained concurrency control (IC3), which provides serializability while allowing for parallel execution of certain conflicting transactions. IC3 combines the static analysis of the transaction workload with runtime techniques that track and enforce dependencies among concurrent transactions. The use of static analysis simplifies IC3's runtime design, allowing it to scale to many cores. Evaluations on a 64-core machine using the TPCC benchmark show that IC3 outperforms traditional con currency control schemes under contention. It achieves the throughput of 434K transactions sec on the TPC-C benchmark configured with only one warehouse. It also scales better than several recent concurrent control schemes that also target contended workloads.
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