Research on Optimizatiion for Complex Query in Parallel Databases

最近，无共享体系结构正在成为标准的商业高度并行机，如SP-2，AP-1000，PARAGON等，因此，已经有一些商业并行数据库系统上实现这些并行机或并行环境。为了利用操作间的并行性，已经有相当大的努力集中在开发高效的多路连接处理并行数据库系统的并行处理器。从目前无共享系统上的大型数据库系统的观点来看，多路连接的管道处理对于通过网络平滑地传输大量数据是重要的。因此，在无共享体系结构上进行并行数据库处理时，必须考虑网络带宽的影响，而目前的研究大多假设在无共享体系结构上进行并行数据库处理，而忽略了网络通信开销。因此，在无共享环境中需要多路连接 ...更多信息 在本研究中，我们考虑在一个无共享的环境中的并行多路连接处理，并展示了如何在有限的网络带宽下，对于给定的资源环境，多路连接调度可以有效地构造。虽然目前通信带宽显著增加，但磁盘阵列的出现也增加了I/O数据流的带宽。这意味着当连接操作的数量不是很小时，网络很容易饱和。我们的算法首先产生子树种子，充分消耗网络带宽的流水线处理。然后，将这些子树种子相互组合，最终产生最优查询树。详细描述了生成一棵平衡I/O访问和网络传输、占用较少内存的短树的约束条件。所提出的算法生成的多路连接计划进行评估，与以前的工作相比，通过使用引入的成本公式。从评估结果来看，不仅是质量的所提出的方法优于以前提出的算法，如左深，右深和分割的右深树，但我们的算法的质量并没有相对恶化。少

Recently, shared-nothing architecture is becoming the standard for commercial highly parallel machines such a SP-2, AP-1000, PARAGON etc. Thus, there have been a number of commercial parallel database systems implemented on these parallel machines or parallel environment. In order to exploit an inter-operation parallelism, there has been considerable effort focused on developing efficient multi-way join processing schedulers for parallel database systems. From the point of view of large database systems on a shared-nothing system these days, it is important for pipeline processing of multi-way join to transfer large amount of data through the network smoothly. So, parallel database processing on a shared-nothing architecture has to take the network bandwidth into account for query compilation, while most the researches so far done assumed shared everything architecture where network communication cost is neglected. Thus, it is necessary for multi-way joins in shared-nothing environment … More to exploit a new optimization algorithm considering the overlap of the I/O accesses and the network transfers.In this research, we consider parallel multi-way join processing in a shared-nothing environment and show how multi-way join scheduling can be constructed efficiently for a given resource environment under finite network bandwidth. Although the communication bandwidth increases significantly these days, the advent of the disk array also increases the bandwidth of I/O data stream. This means the network could easily saturate when the number of join operation is not so small. Our algorithm first generates sub-tree seeds which fully consumes the network bandwidth in a pipeline processing. Then, these sub-tree seeds are combined each other to finally produce an optimal query tree. The restriction conditions for generating a short-tree which balances the I/O accesses and the network transfers and uses less memory are described in detail. The proposed algorithm for generating the multi-way join plan is evaluated in comparison with former work by using the introduced cost formula. From the evaluation results, not only is the quality of the proposed method better than previously presented algorithms such as left-deep, right-deep and segmented right-deep trees, but the quality of our algorithm does not deteriorate comparatively. Less