Query Partitioning for Mixed Workloads in Multicore Environments

抄録

The current generation of computer hardware has brought several new challenges for the underlying software. The number of cores on a chip has grown exponentially, enabling an ever-increasing number of processes to execute in parallel. The efficient utilization of the full range of concurrent processing capabilities offered by such a multicore platform is critical to achieving good system performance. As the number of cores on a chip increases, the increasing processor-memory gap is the bottleneck for most data-intensive applications. We therefore propose a cache-efficient CARIC-DA framework for arranging the execution of concurrent database queries on multicore platforms. This achieves improved database management system (DBMS) performance by improving cache utilization for concurrent queries. Our middleware optimizes the performance of the private-cache levels by providing query-needs-aware dispatching for concurrent online transaction-processing queries to run on different processor cores. By considering both the operating system and the DBMS application, our proposal achieves higher cache utilization for various cache levels. In this paper, we demonstrate how the middleware of CARIC-DA manages a mixed workload, where complex queries with join operations cannot share data with other queries in caches. We describe strategies that enable the middleware to partition complex queries and dispatch concurrent queries to different processor cores. The performance of the extended CARIC-DA for the TPC-W benchmark is evaluated on modern Intel and AMD multicore platforms.