TY - JOUR
T1 - A scalable execution engine for package queries
AU - Brucato, Matteo
AU - Abouzied, Azza
AU - Meliou, Alexandra
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under grants IIS-1420941, IIS-1421322, and IIS-1453543.
PY - 2017/3
Y1 - 2017/3
N2 - Many modern applications and real-world problems involve the design of item collections, or packages: from planning your daily meals all the way to mapping the universe. Despite the pervasive need for packages, traditional data management does not offer support for their definition and computation. This is because traditional database queries follow a powerful, but very simple model: a query defines constraints that each tuple in the result must satisfy. However, a system tasked with the design of packages cannot consider items independently; rather, the system needs to determine if a set of items collectively satisfy given criteria. In this paper, we present package queries, a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets. We develop a full-fledged package query system, implemented on top of a traditional database engine. Our work makes several contributions. First, we design PaQL, a SQL-based query language that supports the declarative specification of package queries. Second, we present a fundamental strategy for evaluating package queries that combines the capabilities of databases and constraint optimization solvers. The core of our approach is a set of translation rules that transform a package query to an integer linear program. Third, we introduce an offline data partitioning strategy allowing query evaluation to scale to large data sizes. Fourth, we introduce SKETCHREFINE, an efficient and scalable algorithm for package evaluation, which offers strong approximation guarantees. Finally, we present extensive experiments over real-world data. Our results demonstrate that SKETCHREFINE is effective at deriving high-quality package results, and achieves runtime performance that is an order of magnitude faster than directly using ILP solvers over large datasets.
AB - Many modern applications and real-world problems involve the design of item collections, or packages: from planning your daily meals all the way to mapping the universe. Despite the pervasive need for packages, traditional data management does not offer support for their definition and computation. This is because traditional database queries follow a powerful, but very simple model: a query defines constraints that each tuple in the result must satisfy. However, a system tasked with the design of packages cannot consider items independently; rather, the system needs to determine if a set of items collectively satisfy given criteria. In this paper, we present package queries, a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets. We develop a full-fledged package query system, implemented on top of a traditional database engine. Our work makes several contributions. First, we design PaQL, a SQL-based query language that supports the declarative specification of package queries. Second, we present a fundamental strategy for evaluating package queries that combines the capabilities of databases and constraint optimization solvers. The core of our approach is a set of translation rules that transform a package query to an integer linear program. Third, we introduce an offline data partitioning strategy allowing query evaluation to scale to large data sizes. Fourth, we introduce SKETCHREFINE, an efficient and scalable algorithm for package evaluation, which offers strong approximation guarantees. Finally, we present extensive experiments over real-world data. Our results demonstrate that SKETCHREFINE is effective at deriving high-quality package results, and achieves runtime performance that is an order of magnitude faster than directly using ILP solvers over large datasets.
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U2 - 10.1145/3093754.3093761
DO - 10.1145/3093754.3093761
M3 - Article
AN - SCOPUS:85019865418
SN - 0163-5808
VL - 46
SP - 24
EP - 31
JO - SIGMOD Record
JF - SIGMOD Record
IS - 1
ER -