Architecture for distributed query processing using the RDF data in cloud environment
Architecture for distributed query processing using the RDF data in cloud environment
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DOI：
10.1007/s12065-019-00315-5
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发表时间：
2019-11
影响因子：
2.6
通讯作者：
C. R. Dharmaraj;B. Tripathy
中科院分区：
文献类型：
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作者：
C. R. Dharmaraj;B. Tripathy
近十年来，RDF数据管理领域的发展给研究人员提出了许多挑战。在云中处理大量RDF数据是非常困难的任务。RDF数据实际上包含复杂的图，其中沿着有大量的模式。传统的RDF数据分发方法或传统的RDF数据划分机制会导致错误的分布以及产生大量的连接操作。为了解决上述问题，本文提出了一种基于自适应哈希划分方法沿着哈希连接操作的分布式查询处理体系结构。本文还提出了一种通过最小化连接来执行查询的算法。本文提出了一个评价所提出的模型与其他标准模型。实验结果表明，该方法具有更快的响应时间相比，其他标准模型。
From past decade, the advancement in the field of RDF data management poses many challenges to researchers. Processing large volumes of RDF data is very difficult task in the cloud. The RDF data actually contains complex graphs along with large number of schemas. Distributing the RDF data with traditional approaches or partitioning them with conventional mechanism leads to faulty distribution as well as generated large number of join operations. To address the above issues, this paper developed architecture for distributed query processing using the adaptive hash partitioning approach along with hash join operation. This paper also developed an algorithm for executing the query by minimizing the joins. This paper presented an evaluation of the proposed model with other standard model. The experimental results proved that the proposed method had faster response time compared to the other standard models.