LEO - DB2's LEarning Optimizer

@inproceedings{citeulike:180884, abstract = {Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer's estimates for the number of rows that will result at each step of the QEP for complex queries involving many predicates and/or operations. These estimates rely upon statistics on the database and modeling assumptions that may or may not be true for a given database. In this paper we introduce LEO, DB2's LEarning...}, author = {Stillger, Michael and Lohman, Guy M. and Markl, Volker and Kandil, Mokhtar }, booktitle = {The VLDB Journal}, citeulike-article-id = {180884}, keywords = {statistics}, pages = {19--28}, posted-at = {2005-05-05 16:11:08}, priority = {0}, title = {LEO - DB2's LEarning Optimizer}, url = {http://citeseer.ist.psu.edu/stillger01leo.html}, year = {2001} }

TY - CONF ID - citeulike:180884 L3 - citeulike-article-id:180884 TI - LEO - DB2's LEarning Optimizer T2 - The VLDB Journal SP - 19 EP - 28 N2 - Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer's estimates for the number of rows that will result at each step of the QEP for complex queries involving many predicates and/or operations. These estimates rely upon statistics on the database and modeling assumptions that may or may not be true for a given database. In this paper we introduce LEO, DB2's LEarning... KW - statistics AU - Stillger, Michael AU - Lohman, Guy AU - Markl, Volker AU - Kandil, Mokhtar PY - 2001/// UR - http://citeseer.ist.psu.edu/stillger01leo.html ER -