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.

Efficient indexing methods for temporal relations

Abstract: The primary issues that affect the design of indexing methods are examined, and several structures and algorithms for specific cases are proposed. The append-only tree (AP-tree) structure indexes data for append-only databases to help event-join optimization and queries that can exploit the inherent time ordering of such databases. Two variable indexing for the surrogate and time is discussed. It is shown that a nested index could be a very efficient structure in this context and is preferable to a composite B-tree or an index that involves linear lists of historical tuples. The problems of indexing time intervals, as related to nonsurrogate joint-indexing, are discussed. Several algorithms to partition the time line are introduced. A two-variable AT index based on nested indexing is outlined. >

Temporal specialization and generalization

Abstract: A standard relation has two dimensions: attributes and tuples. A temporal relation contains two additional orthogonal time dimensions: valid time records when facts are true in the modeled reality, and transaction time records when facts are stored in the temporal relation. Although there are no restrictions between the valid time and transaction time associated with each fact, in many practical applications the valid and transaction times exhibit restricted interrelationships that define several types of specialized temporal relations. This paper examines areas where different specialized temporal relations are present. In application systems with multiple, interconnected temporal relations, multiple time dimensions may be associated with facts as they flow from one temporal relation to another. The paper investigates several aspects of the resulting generalized temporal relations, including the ability to query a predecessor relation from a successor relation. The presented framework for generalization and specialization allows one to precisely characterize and compare temporal relations and the application systems in which they are embedded. The framework's comprehensiveness and its use in understanding temporal relations are demonstrated by placing previously proposed temporal data models within the framework. The practical relevance of the defined specializations and generalizations is illustrated by sample realistic applications in which they occur. The additional semantics of specialized relations are especially useful for improving the performance of query processing. >

Standing Out in a Crowd: Selecting Attributes for Maximum Visibility

Abstract: In recent years, there has been significant interest in development of ranking functions and efficient top-k retrieval algorithms to help users in ad-hoc search and retrieval in databases (e.g., buyers searching for products in a catalog). In this paper we focus on a novel and complementary problem: how to guide a seller in selecting the best attributes of a new tuple (e.g., new product) to highlight such that it stands out in the crowd of existing competitive products and is widely visible to the pool of potential buyers. We develop several interesting formulations of this problem. Although these problems are NP-complete, we can give several exact algorithms as well as approximation heuristics that work well in practice. Our exact algorithms are based on integer programming (IP) formulations of the problems, as well as on adaptations of maximal frequent itemset mining algorithms, while our approximation algorithms are based on greedy heuristics. We conduct a performance study illustrating the benefits of our methods on real as well as synthetic data.

System and method for caching identification and location information in a computer network

Abstract: Methods and systems are provided for caching information in a distributed computer system such as a directory service system. Tuples in a client cache contain component identifiers and corresponding location identifiers. Tuples may contain a list of network addresses specifying at least one server containing additional location or object information, as well as replica flags which distinguish between read-only replicas, read-write replicas, and a master replica. Requests to access an object may be serviced by using cached information rather than making one or more attempts to obtain location information from servers. Tuples may be modified or invalidated such that read operations tend to be performed using read-only replicas. Cached tuples which contain a component identifier that is no longer valid because an object was moved or renamed may be invalidated. The cache may also be modified to redirect operations from a master replica to a non-master replica.

A compression algorithm for large arity extensional constraints

Abstract: We present an algorithm for compressing table constraints representing allowed or disallowed tuples. This type of constraint is used for example in configuration problems, where the satisfying tuples are read from a database. The arity of these constraints may be large. A generic GAC algorithm for such a constraint requires time exponential in the arity of the constraint to maintain GAC, but Bessiere and Regin showed in [1] that for the case of allowed tuples, GAC can be enforced in time proportional to the number of allowed tuples, using the algorithm GAC-Schema. We introduce a more compact representation for a set of tuples, which allows a potentially exponential reduction in the space needed to represent the satisfying tuples and exponential reduction in the time needed to enforce GAC. We show that this representation can be constructed from a decision tree that represents the original tuples and demonstrate that it does in practice produce a significantly shorter description of the constraint. We also show that this representation can be efficiently used in existing algorithms and can be used to improve GAC-Schema further. Finally, we show that this method can be used to improve the complexity of enforcing GAC on a table constraint defined in terms of forbidden tuples.