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A Query Mechanism of Massive Relational Data Cross Regional and Multiple Data Centers

机译:大规模关系数据交叉区域和多个数据中心的查询机制

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In this paper, we propose a collaborative query system on large-scale relational data available on multiple nodes in several data centers. This mechanism has a special query engine which can access data across all the nodes. We design and implement a process which is suitable to query tasks characteristics, to ensure efficient implementation of these tasks. The system uses direct data transfer between the query engine and each data center, thus to reduce time consumption caused by data transmission. In addition, we introduce an appropriate data caching mechanism to reserve partial remote data at a local data center and to avoid redundant transmission. Our approach improves the transmission efficiency and reduces the bandwidth requirements for networks and their costs. The test shows that the performance of the proposed system with and higher hit rate of cache data is higher more than the traditional collaborative query method.
机译:在本文中,我们提出了一个在多个数据中心中的多个节点上提供的大规模关系数据的协作查询系统。该机制具有特殊的查询引擎,可以在所有节点上访问数据。我们设计和实现适合查询任务特性的过程,以确保有效地实现这些任务。该系统使用查询引擎和每个数据中心之间的直接数据传输,从而减少由数据传输引起的时间消耗。此外,我们介绍了一个适当的数据缓存机制,以便在本地数据中心预留部分远程数据,并避免冗余传输。我们的方法提高了传输效率,降低了网络的带宽要求及其成本。该测试表明,所提出的系统的性能具有和更高的高速缓存数据击中率的比率高于传统的协作查询方法。

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