TY - GEN
T1 - PAQO
T2 - 30th IEEE International Conference on Data Engineering, ICDE 2014
AU - Farnan, Nicholas L.
AU - Lee, Adam J.
AU - Chrysanthis, Panos K.
AU - Yu, Ting
PY - 2014
Y1 - 2014
N2 - The declarative nature of SQL has traditionally been a major strength. Users simply state what information they are interested in, and the database management system determines the best plan for retrieving it. A consequence of this model is that should a user ever want to specify some aspect of how their queries are evaluated (e.g., a preference to read data from a specific replica, or a requirement for all joins to be performed by a single server), they are unable to. This can leave database administrators shoehorning evaluation preferences into database cost models. Further, for distributed database users, it can result in query evaluation plans that violate data handling best practices or the privacy of the user. To address such issues, we have developed a framework for declarative, user-specified constraints on the query optimization process and implemented it within PosgreSQL. Our Preference-Aware Query Optimizer (PAQO) upholds both strict requirements and partially ordered preferences that are issued alongside of the queries that it processes. In this paper, we present the design of PAQO and thoroughly evaluate its performance.
AB - The declarative nature of SQL has traditionally been a major strength. Users simply state what information they are interested in, and the database management system determines the best plan for retrieving it. A consequence of this model is that should a user ever want to specify some aspect of how their queries are evaluated (e.g., a preference to read data from a specific replica, or a requirement for all joins to be performed by a single server), they are unable to. This can leave database administrators shoehorning evaluation preferences into database cost models. Further, for distributed database users, it can result in query evaluation plans that violate data handling best practices or the privacy of the user. To address such issues, we have developed a framework for declarative, user-specified constraints on the query optimization process and implemented it within PosgreSQL. Our Preference-Aware Query Optimizer (PAQO) upholds both strict requirements and partially ordered preferences that are issued alongside of the queries that it processes. In this paper, we present the design of PAQO and thoroughly evaluate its performance.
UR - http://www.scopus.com/inward/record.url?scp=84901760585&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2014.6816670
DO - 10.1109/ICDE.2014.6816670
M3 - Conference contribution
AN - SCOPUS:84901760585
SN - 9781479925544
T3 - Proceedings - International Conference on Data Engineering
SP - 424
EP - 435
BT - 2014 IEEE 30th International Conference on Data Engineering, ICDE 2014
PB - IEEE Computer Society
Y2 - 31 March 2014 through 4 April 2014
ER -