Implementing Query Terms Linked to Virtual Databases by Metaheuristic Techniques
Suman Sourav Prasad1, Sambit Kumar Mishra2
1Suman Sourav Prasad*, Department of Computer Engg. Ajay Binay Institute of Technology, Cuttack, Affiliated to Biju Patnaik University of Technology, Rourkela.
2Sambit Kumar Mishra, Department of Computer Engg. Gandhi Institute of Technology, Baniatangi, Affiliated to Biju Patnaik University of Technology, Rourkela.
Manuscript received on July 02 2019. | Revised Manuscript received on July 22, 2019. | Manuscript published on December 30, 2019. | PP: 1081-1085 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3376129219/2020©BEIESP | DOI: 10.35940/ijeat.B3376.129219
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In general case, the database trigger may be quite applicable to signified queries to validate the database requests. Specifically, these may be essential to adopt search mechanisms to identify the query terms. In such cases it may also be required to eradicate ambiguities during updates by checking consistencies, durability. Many database systems support aggregate functions as it may be really linked to statistical analysis of large scale data. Again as per the requirement and schedule, multilevel aggregation may be thought of towards report generation and implementation of join predicates. In case of complexity, direct requests may be accessed to schedule the entire database operations. While optimizing the database queries, alternative query plans may be thought of implementing specific routines to eradicate the duplicity of query terms. It may be quite possible to containerize the query plans linked to several data servers exploring the inter operator parallelism. Also the assemblers linked to the query plans in the servers may steer the process accordingly. Considering the implementation mechanisms of database query plans inside a cloud storage system, the data may be automatically partitioned and replicated. The servers may change dynamically the existing load in response to the query plans. The queries as well as the transactions may be uncommon during optimization process and applications may be communicated following standard activity protocols linked to the database servers. Linking the query terms to the databases, it may also be required to incorporate metadata towards plan execution. Many times transactional database applications linked to relational cloud may have the provision of configuring and accessing the data and may face the challenges like scalability and privacy. To overcome these issues, the tasks may be relocated and rearranged linked to database servers by which better performance may be achieved dealing with complex transactions. Also the aggregation methods or techniques linked to data partitioning may enable the structured queries to yield better performance. In this paper it is intended to obtain query terms along with the threshold values linked to virtual databases.
Keywords: Query terms, Join indices, Virtual machine, Query plans, Metaheuristic, Threshold value.