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Data allocation optimization for query processing in graph databases using Lucene
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DOI：10.1016/j.compeleceng.2018.01.022.png)
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Methodological handling of queries is a crucial requirement in social networks connected to a graph NoSQL database that incorporates massive amounts of data. The massive data need to be partitioned across numerous nodes so that the queries when executed can be retrieved from a parallel structure. A novel storage mechanism for effective query processing must to be established in graph databases for minimizing time overhead. This paper proposes a metaheuristic algorithm for partitioning of graph database across nodes by placement of all related information on same or adjacent nodes. The graph database allocation problem is proved to be NP-Hard. A metaheuristic algorithm comprising of Best Fit Decreasing with Ant Colony Optimization is proposed for data allocation in a distributed architecture of graph NoSQL databases. Lucene index is applied on proposed allocation for faster query processing. The proposed algorithm with Lucene is evaluated based on simulation results obtained from different heuristics available in literature. (C) 2018 Elsevier Ltd. All rights reserved.
Keyword:
Big Data
Query retrieval
Graph NoSQL databases
Data allocation
Best Fit Decreasing
Ant Colony Optimization
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