An Improved Distributed Query for Large-Scale RDF Data
An Improved Distributed Query for Large-Scale RDF Data
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DOI：
10.32604/jbd.2020.010358
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Aoran Li;Xinmeng Wang;Xueliang Wang;Bohan Li
中科院分区：
文献类型：
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作者：
Aoran Li;Xinmeng Wang;Xueliang Wang;Bohan Li
: The rigid structure of the traditional relational database leads to data redundancy, which seriously affects the efficiency of the data query and cannot effectively manage massive data. To solve this problem, we use distributed storage and parallel computing technology to query RDF data. In order to achieve efficient storage and retrieval of large-scale RDF data, we combine the respective advantage of the storage model of the relational database and the distributed query. To overcome the disadvantages of storing and querying RDF data, we design and implement a breadth-first path search algorithm based on the keyword query on a distributed platform. We conduct the LUBM query statements respectively with the selected data sets. In experiments, we compare query response time in different conditions to evaluate the feasibility and correctness of our approaches. The results show that the proposed scheme can reduce the storage cost and improve query efficiency.
