Tuple

About: Tuple is a research topic. Over the lifetime, 6513 publications have been published within this topic receiving 146057 citations. The topic is also known as: tuple & ordered tuplet.

Query optimization and execution plan generation in object-oriented data management systems

Abstract: The generation of execution plans for object-oriented database queries is a new and challenging area of study. Unlike relational algebra, a common set of object algebra operators has not been defined. Similarly, a standardized object manager interface analogous to the storage manager interface of relational subsystems does not exist. We define the interface to an object manager whose operations are the executable elements of query execution plans. Parameters to the object manager interface are streams of tuples of object identifiers. The object manager can apply methods and simple predicates to the objects identified in a tuple. Two algorithms for generating such execution plans for queries expressed in an object algebra are presented. The first algorithm runs quickly but may produce inefficient plans. The second algorithm enumerates all possible execution plans and presents them in an efficient, compact representation. >

Possible and certain SQL keys

Abstract: Driven by the dominance of the relational model, the requirements of modern applications, and the veracity of data, we revisit the fundamental notion of a key in relational databases with NULLs. In SQL database systems primary key columns are NOT NULL by default. NULL columns may occur in unique constraints which only guarantee uniqueness for tuples which do not feature null markers in any of the columns involved, and therefore serve a different function than primary keys. We investigate the notions of possible and certain keys, which are keys that hold in some or all possible worlds that can originate from an SQL table, respectively. Possible keys coincide with the unique constraint of SQL, and thus provide a semantics for their syntactic definition in the SQL standard. Certain keys extend primary keys to include NULL columns, and thus form a sufficient and necessary condition to identify tuples uniquely, while primary keys are only sufficient for that purpose. In addition to basic characterization, axiomatization, and simple discovery approaches for possible and certain keys, we investigate the existence and construction of Armstrong tables, and describe an indexing scheme for enforcing certain keys. Our experiments show that certain keys with NULLs do occur in real-world databases, and that related computational problems can be solved efficiently. Certain keys are therefore semantically well-founded and able to maintain data quality in the form of Codd's entity integrity rule while handling the requirements of modern applications, that is, higher volumes of incomplete data from different formats.

Possible and certain keys for SQL

Abstract: Driven by the dominance of the relational model and the requirements of modern applications, we revisit the fundamental notion of a key in relational databases with NULL. In SQL, primary key columns are NOT NULL, and UNIQUE constraints guarantee uniqueness only for tuples without NULL. We investigate the notions of possible and certain keys, which are keys that hold in some or all possible worlds that originate from an SQL table, respectively. Possible keys coincide with UNIQUE, thus providing a semantics for their syntactic definition in the SQL standard. Certain keys extend primary keys to include NULL columns and can uniquely identify entities whenever feasible, while primary keys may not. In addition to basic characterization, axiomatization, discovery, and extremal combinatorics problems, we investigate the existence and construction of Armstrong tables, and describe an indexing scheme for enforcing certain keys. Our experiments show that certain keys with NULLs occur in real-world data, and related computational problems can be solved efficiently. Certain keys are therefore semantically well founded and able to meet Codd's entity integrity rule while handling high volumes of incomplete data from different formats.

Maximizing Conjunctive Views in Deletion Propagation

Abstract: In deletion propagation, tuples from the database are deleted in order to reflect the deletion of a tuple from the view. Such an operation may result in the (often necessary) deletion of additional tuples from the view, besides the intentionally deleted one. The article studies the complexity of deletion propagation, where the view is defined by a conjunctive query (CQ), and the goal is to maximize the number of tuples that remain in the view. Buneman et al. showed that for some simple CQs, this problem can be solved by a straightforward algorithm, which is called here the unidimensional algorithm. The article identifies additional cases of CQs where the unidimensional algorithm succeeds, and in contrast, shows that for some other CQs the problem is NP-hard to approximate better than some constant ratio. In fact, it is shown here that among the CQs without self joins, the hard CQs are exactly the ones that the unidimensional algorithm fails on. In other words, the following dichotomy result is proved: for every CQ without self joins, deletion propagation is either APX-hard or solvable (in polynomial time) by the unidimensional algorithm.The article then presents approximation algorithms for certain CQs where deletion propagation is APX-hard. Specifically, two constant-ratio (and polynomial-time) approximation algorithms are given for the class of sunflower CQs (i.e., CQs having a sunflower hypergraph) without self joins. The first algorithm, providing the approximation ratio 1 − 1/e, is obtained by formulating the problem at hand as that of maximizing a monotone submodular function subject to a matroid constraint, and then using a known algorithm for such maximization. The second algorithm gives a smaller approximation ratio, 1/2, yet in polynomial time even under combined complexity. Finally, it is shown that self joins can significantly harden approximation in deletion propagation.