Querying and retrieving data from graphs stored in distributed architecture (QRDA). (7th December 2022) - Devi, N. Mithili; Kasireddy, Sandhya Rani
The ability to handle huge amount of data using big graphs and graph data structures plays a vital role in ever growing areas like IOT, social networking, e-commerce and bioinformatics applications. Querying graphs and extracting data in an effective manner is very crucial in big graph processing. This paper presents a framework that focuses on reassignment of vertices among partitions based on query graph so that entire query related information gets shifted to one partition to the extent possible leading to minimised query execution time. This technique first finds the partitions in which the query graph nodes are present and performs searching only in those partitions leading to minimised retrieval time. The proposed QRDA technique is compared with various state-of-art graph querying practices and the outcomes show that QRDA performance is better over other approaches.