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SQL Scorecard for Improved Stability and Performance of Data Warehouses

SQL Scorecard for Improved Stability and Performance of Data Warehouses

Nayem Rahman
Copyright: © 2016 |Volume: 4 |Issue: 3 |Pages: 16
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781466693845|DOI: 10.4018/IJSI.2016070102
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MLA

Rahman, Nayem. "SQL Scorecard for Improved Stability and Performance of Data Warehouses." IJSI vol.4, no.3 2016: pp.22-37. http://doi.org/10.4018/IJSI.2016070102

APA

Rahman, N. (2016). SQL Scorecard for Improved Stability and Performance of Data Warehouses. International Journal of Software Innovation (IJSI), 4(3), 22-37. http://doi.org/10.4018/IJSI.2016070102

Chicago

Rahman, Nayem. "SQL Scorecard for Improved Stability and Performance of Data Warehouses," International Journal of Software Innovation (IJSI) 4, no.3: 22-37. http://doi.org/10.4018/IJSI.2016070102

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Abstract

Scorecard-based measurement techniques are used by organizations to measure the performance of their business operations. A scorecard approach could be applied to a database system to measure performance of SQL (Structured Query Language) being executed and the extent of resources being used by SQL. In a large data warehouse, thousands of jobs run daily via batch cycles to refresh different subject areas. Simultaneously, thousands of queries by business intelligence tools and ad-hoc queries are being executed twenty-four by seven. There needs to be a controlling mechanism to make sure these batch jobs and queries are efficient and do not consume database systems resources more than optimal. The authors propose measurement of SQL query performance via a scorecard tool. The motivation behind using a scorecard tool is to make sure that the resource consumption of SQL queries is predictable and the database system environment is stable. The experimental results show that queries that pass scorecard evaluation criteria tend to utilize optimal level of database systems computing resources. These queries also show improved parallel efficiency (PE) in using computing resources (CPU, I/O and spool space) that demonstrate the usefulness of SQL scorecard.

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