K.Subieta. SBA and SBQL, appendix, slide 1 Sept Appendix: how the ENVS and QRES stacks work (example) Presentation prepared for OMG Object Database Technology Working Group OMG TECHNICAL MEETING, Anaheim, CA USA September 25-29, 2006 by Prof. Kazimierz Subieta Polish-Japanese Institute of Information Technology, Warsaw, Poland SBA/SBQL pages:

K.Subieta. SBA and SBQL, appendix, slide 2 Sept Query addressing a tiny database Query: For each department get its reference and the average sal of its employees. SBQL: Dept join avg(employs.Emp.sal) Tiny database: Expected result: bag{ struct{i 17, 2500}, struct{i 22, 1450} }

K.Subieta. SBA and SBQL, appendix, slide 3 Sept Execution scenario Dept join avg( ( employs. Emp ). sal ) join1 st dot2 nd dot avg 1 st Dept 2 nd Dept 1 st employs 2 nd employs 1 st Emp 2 nd Emp 3 rd Emp3 rd employs

K.Subieta. SBA and SBQL, appendix, slide 4 Sept Sample query Dept join avg( ( employs. Emp ). sal ) Emp(i 1 ) Emp(i 5 ) Emp(i 9 ) Dept(i 17 ) Dept(i 22 ) ENVSQRES empty Start

K.Subieta. SBA and SBQL, appendix, slide 5 Sept In closing … Please note that this evaluation scenario concerns the formal semantics only, executed by an abstract machine. –Our goal is clear, universal and free of ambiguities semantic specification rather than performance. In real implementation there are many obvious optimizations. –C.f. our implementations in various projects. The evaluation process is also the subject of many sophisticated optimizations (rewriting, indices, caching,…). The entire process is executed in main memory, hence the computations are not critical. –Critical computations concern the access to external storage and network, and avoiding unnecessary (redundant) computations. –This is just the subject of major SBA optimization methods.