Creation of Gene Database and Implementation of Transaction Processing
A rich set of concepts and techniques has been used in the context of gene database creation and transaction processing along withperformance and tuning for the efficient and robust execution of queries. So far, this work has mostly focused on issues related to data-retrievalqueries. However, update...
Main Authors: | , |
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Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
International Journal of Advanced Research in Computer Science
2017
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Subjects: | |
Online Access: | http://www.ijarcs.info/index.php/Ijarcs/article/view/132 https://doi.org/10.26483/ijarcs.v1i3.132 |
Summary: | A rich set of concepts and techniques has been used in the context of gene database creation and transaction processing along withperformance and tuning for the efficient and robust execution of queries. So far, this work has mostly focused on issues related to data-retrievalqueries. However, update operations can also exhibit a number of query processing issues, depending on the complexity of the operations and thevolume of data to process. Such issues include lookup and matching of values, navigational vs. set-oriented algorithms and trade-offs between plansthat do serial or random I/Os .In this paper we present an overview of the basic techniques used to support SQL DML (Data ManipulationLanguage) in ORACLE database 10g. Our focus is on the collection of gene information and implementation of some concepts of transactionoperations and performance and tuning operation into the gene database and cancer database. Although atomicity is a well studied topic in transactionprocessing and business workflows, such an important capability needs to be revisited in a scientific workflow environment. Atomicity needs to bedefined in dataflow-oriented scientific workflow model. The basic principles of all transaction-processing systems are the same. However, theterminology may vary from one transaction-processing system to another. Keywords: GeneBank, SQL DML, DB Transaction Management, Tuning. |
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