QScheduler: A Tool for Parallel Query Processing in Database Systems
QScheduler: A Tool for Parallel Query Processing in Database Systems
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QScheduler：数据库系统中并行查询处理的工具
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Jing Xu
中科院分区：
文献类型：
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作者：
Qing;Shan;Jing Xu
数据库系统中的并行查询处理在过去的几年中一直被积极研究。当多个查询同时执行时，所有并行任务将竞争对底层I/O和计算资源的访问，这将导致更多的争用和颠簸。当一系列不同类型的查询在数据库系统中并发运行时，如果我们改变这些查询的执行顺序，查询任务的整个执行时间可能会不同。执行顺序的这种简单更改可以直接影响并行查询之间的交互。因此，我们认为，重要的是要考虑到并行查询之间的相互作用。在本文中，我们考虑的问题，以提高并行查询任务的性能的基础上，一个名为的工具，它的设计和实现，以控制查询执行顺序。我们的调度器将数据库系统视为一个黑盒子，并根据不同的算法来决定优先调度哪些查询。我们使用TPC-H基准测试的实验结果表明，该方法可以捕获复杂查询交互的影响，并将有效地提高系统的性能。
Parallel query processing in database systems has been actively investigated for the past several years. When several queries execute at the same time, all parallel tasks will compete for access to the underlying I/O and computation resources and this will lead to more contention and thrashing. When a series of queries of different types run concurrently in a database system, if we change the execution sequence of these queries, the whole execution time of the query task may be different. This simple change in the execution order can directly affect the interactions among parallel queries. Hence, we argue that it is important to take the interactions among parallel queries into account. In this paper, we consider the problem of improving the performance of parallel query tasks based on a tool named Scheduler which is designed and implemented to control the query execution sequence. Our Scheduler treats the database system as a black box and decides which query to schedule preferentially according to the different algorithm. Our experimental evaluation using TPC-H benchmark shows that the Scheduler can capture the impact of complex query interactions and will improve the system performance efficiently.