STATISTICS COLLECTION AND WORKLOAD MANAGEMENT OF SQL QUERIES
Journal: International Journal of Information Technology and Management information System (IJITMIS) (Vol.11, No. 1)Publication Date: 2020-01-31
Authors : Smruthi.K.M Nagraj Bhat;
Page : 1-7
Keywords : Online Analytical Processing; Mission Critical Environments; NonStop Database Analyzer; Workload Management Services (WMS).;
Abstract
In the late 1980s, data ware house technology introduced Online Analytical Processing (OLAP) in order to process the data to support the business decision and business intelligence. Multiple copies of data were located on different database servers called data mart. Later with the paradigm shift in the technology, big data and analytics are the major trends which are the changing the business world. The data which has been generated in this modern works is huge and growing exponentially. The data which is been generated is of different types. The structured and unstructured data are flooded into the organizations. So, there is a need for missioncritical environments and nonstop servers or system which provides 100% fault tolerance in storing and processing these data. Nonstop eliminates the risk of downtime while meeting large-scale business needs online transaction processing and database requirements. This paper discusses about the different aspects of Nonstop Database Analyzer (NSDA) which is a Manageability product for viewing, monitoring, managing the Database workloads running on the Nonstop System (NSK). Workload Management Services (WMS) provides the infrastructure for monitoring workloads through queries.
Other Latest Articles
- UTILISATION AND CHALLENGES OF THE LEARNING MANAGEMENT SYSTEMS IN THE HIGHER EDUCATION INSTITUTIONS IN MALDIVES: THE LECTURERS’ AND STUDENTS’ PERSPECTIVES
- GROSSESSE ABDOMINALE: A PROPOS D UN CAS
- Effects of Problem Based Learning Method and Lecture Teaching Method on Academic Achievement of Students
- Academist Perceptions on the Use of Web 2.0 Tools Through Maslow's Needs Hierarchy: A Case Study
- Development of a Learning Model for Large Class Cohorts to Strengthen Learning Outcomes of Students Based on Differentiated Instruction
Last modified: 2021-03-11 16:47:34