Showing papers on "Tuple published in 2000"

A 2-tuple fuzzy linguistic representation model for computing with words

Abstract: The fuzzy linguistic approach has been applied successfully to many problems. However, there is a limitation of this approach imposed by its information representation model and the computation methods used when fusion processes are performed on linguistic values. This limitation is the loss of information; this loss of information implies a lack of precision in the final results from the fusion of linguistic information. In this paper, we present tools for overcoming this limitation. The linguistic information is expressed by means of 2-tuples, which are composed of a linguistic term and a numeric value assessed in (-0.5, 0.5). This model allows a continuous representation of the linguistic information on its domain, therefore, it can represent any counting of information obtained in a aggregation process. We then develop a computational technique for computing with words without any loss of information. Finally, different classical aggregation operators are extended to deal with the 2-tuple linguistic model.

Snowball: extracting relations from large plain-text collections

Abstract: Text documents often contain valuable structured data that is hidden Yin regular English sentences. This data is best exploited infavailable as arelational table that we could use for answering precise queries or running data mining tasks.We explore a technique for extracting such tables from document collections that requires only a handful of training examples from users. These examples are used to generate extraction patterns, that in turn result in new tuples being extracted from the document collection.We build on this idea and present our Snowball system. Snowball introduces novel strategies for generating patterns and extracting tuples from plain-text documents.At each iteration of the extraction process, Snowball evaluates the quality of these patterns and tuples without human intervention,and keeps only the most reliable ones for the next iteration. In this paper we also develop a scalable evaluation methodology and metrics for our task, and present a thorough experimental evaluation of Snowball and comparable techniques over a collection of more than 300,000 newspaper documents.

Eddies: continuously adaptive query processing

Abstract: In large federated and shared-nothing databases, resources can exhibit widely fluctuating characteristics. Assumptions made at the time a query is submitted will rarely hold throughout the duration of query processing. As a result, traditional static query optimization and execution techniques are ineffective in these environments.In this paper we introduce a query processing mechanism called an eddy, which continuously reorders operators in a query plan as it runs. We characterize the moments of symmetry during which pipelined joins can be easily reordered, and the synchronization barriers that require inputs from different sources to be coordinated. By combining eddies with appropriate join algorithms, we merge the optimization and execution phases of query processing, allowing each tuple to have a flexible ordering of the query operators. This flexibility is controlled by a combination of fluid dynamics and a simple learning algorithm. Our initial implementation demonstrates promising results, with eddies performing nearly as well as a static optimizer/executor in static scenarios, and providing dramatic improvements in dynamic execution environments.

Tracing the lineage of view data in a warehousing environment

Abstract: We consider the view data lineageproblem in a warehousing environment: For a given data item in a materialized warehouse view, we want to identify the set of source data items that produced the view item. We formally define the lineage problem, develop lineage tracing algorithms for relational views with aggregation, and propose mechanisms for performing consistent lineage tracing in a multisource data warehousing environment. Our result can form the basis of a tool that allows analysts to browse warehouse data, select view tuples of interest, and then “drill-through” to examine the exact source tuples that produced the view tuples of interest.

Data integration using similarity joins and a word-based information representation language

Abstract: The integration of distributed, heterogeneous databases, such as those available on the World Wide Web, poses many problems. Herer we consider the problem of integrating data from sources that lack common object identifiers. A solution to this problem is proposed for databases that contain informal, natural-language “names” for objects; most Web-based databases satisfy this requirement, since they usually present their information to the end-user through a veneer of text. We describe WHIRL, a “soft” database management system which supports “similarity joins,” based on certain robust, general-purpose similarity metrics for text. This enables fragments of text (e.g., informal names of objects) to be used as keys. WHIRL includes textual objects as a built-in type, similarity reasoning as a built-in predicate, and answers every query with a list of answer substitutions that are ranked according to an overall score. Experiments show that WHIRL is much faster than naive inference methods, even for short queries, and efficient on typical queries to real-world databases with tens of thousands of tuples. Inferences made by WHIRL are also surprisingly accurate, equaling the accuracy of hand-coded normalization routines on one benchmark problem, and outerperforming exact matching with a plausible global domain on a second.

Practical lineage tracing in data warehouses

Abstract: We consider the view data lineage problem in a warehousing environment: for a given data item in a materialized warehouse view, we want to identify the set of source data items that produced the view item. We formalize the problem and we present a lineage tracing algorithm for relational views with aggregation. Based on our tracing algorithm, we propose a number of schemes for storing auxiliary views that enable consistent and efficient lineage tracing in a multi-source data warehouse. We report on a performance study of the various schemes, identifying which schemes perform best in which settings. Based on our results, we have implemented a lineage tracing package in the WHIPS data warehousing system prototype at Stanford. With this package, users can select view tuples of interest, then efficiently "drill through" to examine the exact source tuples that produced the view tuples of interest.

ICICLES: Self-Tuning Samples for Approximate Query Answering

Abstract: Approximate query answering systems provide very fast alternatives to OLAP systems when applications are tolerant to small errors in query answers. Current sampling-based approaches to approximately answer aggregate queries over foreign key joins suffer from the following drawback. All tuples in relations are deemed equally important for answering queries even though, in reality, OLAP queries exhibit locality in their data access. Consequently, they may waste precious real estate by sampling tuples that are not required at all or required very rarely. In this paper, we introduce icicles, a new class of samples that tune themselves to a dynamic workload. Intuitively, the probability of a tuple being present in an icicle is proportional to its importance for answering queries in the workload. Therefore, an icicle consists of more tuples from a subset of the relation that is required to answer more queries in the workload. Consequently, the accuracy of approximate answers obtained by using icicles is better than a static uniform random sample. We show, analytically, that for a certain class of queries reflected by the workload, icicles yield more accurate answers. In a detailed experimental study, we examine the validity and performance of icicles.

Querying Graph Databases

Abstract: Graph data is an emerging model for representing a variety of database contexts ranging from object-oriented databases to hypertext data. Also many of the recursive queries that arise in relational databases are, in practice, graph traversals. In this paper we present a language for searching graph-like databases. The language permits us to express paths in a graph by means of extended regular expressions. The proposed extension is based on the introduction of constructs which permit us i) to define a partial order on the paths used to search the graph and, consequently, on the answers of queries, and ii) to cut off, nondeterministically, tuples with low priority. We present an algebra for partially ordered relations and an algorithm for the computation of path queries. Finally, we present applications to hypertext databases such as the Web.

Indexing system and method

Abstract: A method for generating an index of data available from a server, including processing data on the server to access data items for a central index, the data items including network addresses and terms, compiling an index file including the data items, and transmitting the index file to the central index. The processing may include locating database query statements in the data, and the data items then include input tuples for the statements. The index is accessible from servers, and includes page entries including a program address for a program for generating a dynamic page and input tuples for submission to the program to generate the page, and search entries identifying the dynamic pages and identifying the tuples corresponding to search terms. A search engine operable on the index, is able to access the search entries to identify dynamic pages corresponding to search terms of a search query, and access the page entries to generate addresses for the dynamic pages identified, the addresses being generated on the basis of the program address and the tuples.

Method and system for identifying and processing changes to a network topology

Abstract: A method and system are disclosed for mapping the topology of a network having interconnected nodes by identifying changes in the network and updating a stored network topology based on the changes. The nodal connections are represented by data tuples that store information such as a host identifier, a connector interface, and a port specification for each connection. A topology database stores an existing topology of a network. A topology converter accesses the topology database and converts the existing topology into a list of current tuples. A connection calculator calculates tuples to represent connections in the new topology. The topology converter receives the new tuples, identifies changes to the topology, and updates the topology database using the new tuples. The topology converter identifies duplicate tuples that appear in both the new tuples and the existing tuples and marks the duplicate tuples to reflect that no change has occurred to these connections. The topology converter attempts to resolve swapped port conditions and searches for new singly-heard and multi-heard host link tuples in the list of existing tuples. The topology converter also searches for new conflict link tuples in the existing tuples. The topology converter updates the topology database with the new topology.

Approximate querying method for databases with multiple grouping attributes

Abstract: An approximate querying method comprising grouping tuples within a database according to grouping attributes, determining how many tuples are needed to represent each group, selecting the tuples from a corresponding group to create a database sample, and querying the database sample. The database sample yields statistically unbiased answers when queried. The sample may be created and maintained without a priori knowledge of the data distribution within the database or the queries to be performed.

Compiling Embedded Languages

Abstract: Functional languages are particularly well-suited to the implementation of interpreters for domain-specific embedded languages (DSELs). We describe an implemented technique for producing optimizing compilers for DSELs, based on Kamin's idea of DSELs for program generation. The technique uses a data type of syntax for basic types, a set of smart constructors that perform rewriting over those types, some code motion transformations, and a back-end code generator. Domainspecific optimization results from chains of rewrites on basic types. New DSELs are defined directly in terms of the basic syntactic types, plus host language functions and tuples. This definition style makes compilers easy to write and, in fact, almost identical to the simplest embedded interpreters. We illustrate this technique with a language Pan for the computationally intensive domain of image synthesis and manipulation.

Method and apparatus for representing multidimensional data

Abstract: The invention is directed towards method and apparatus for representing multidimensional data. Some embodiments of the invention provide a two-layered data structure to store multidimensional data tuples that are defined in a multidimensional data space. These embodiments initially divide the multidimensional data space into a number of data regions, and create a data structure to represent this division. For each data region, these embodiments then create a hierarchical data structure to store the data tuples within each region. In some of these embodiments, the multidimensional data tuples are spatial data tuples that represent spatial or geometric objects, such as points, lines, polygons, regions, surfaces, volumes, etc. For instance, some embodiments use the two-layered data structure of the invention to store data relating to geometric objects (such as rectangles) that represent interconnect lines of an IC in an IC design layout.

Methods and apparatus for tuple management in data processing system

Abstract: A data processing system stores information in tuple space as tuples that are accessible by multiple entities. Methods, apparatus, computer-readable media, and data structures provide efficient extensions to tuple space coordination languages for example Linda, that increase concurrency by lessening tuple removal, without requiring compile time analysis, altering existing primitives, or adding new primitives. Traces are used to analyze tuple space access in distributed systems, resulting in optimizations based upon certain conditions which, if met, enable a tuple to remain visible in tuple space without blocking, so that other processes can continue to read the tuple while a first process is updating the tuple. A run-time optimization modifies the conditions if the execution is in a closed system that is known not to intentionally contain deadlock, further improving performance.

Method for coordinating activities and sharing information using a data definition language

Abstract: A widely-used data definition language such as the Extensible Markup Language is used to implement a tuple space-based coordination mechanism. Entries and template entries can represent any type of networked or network-proxied resource, object or service. Using this framework, diverse entry spaces can be aggregated and operated upon as though they were a single large entry space. The flexibility and power of XML constructs can be leveraged to make such aggregation straightforward and efficient.

Incremental maintenance of recursive views using relational calculus/SQL

Abstract: Views are a central component of both traditional database systems and new applications such as data warehouses. Very often the desired views (e.g. the transitive closure) cannot be defined in the standard language of the underlying database system. Fortunately, it is often possible to incrementally maintain these views using the standard language. For example, transitive closure of acyclic graphs, and of undirected graphs, can be maintained in relational calculus after both single edge insertions and deletions. Many such results have been published in the theoretical database community. The purpose of this survey is to make these useful results known to the wider database research and development community.There are many interesting issues involved in the maintenance of recursive views. A maintenance algorithm may be applicable to just one view, or to a class of views specified by a view definition language such as Datalog. The maintenance algorithm can be specified in a maintenance language of different expressiveness, such as the conjunctive queries, the relational calculus or SQL. Ideally, this maintenance language should be less expensive than the view definition language. The maintenance algorithm may allow updates of different kinds, such as just single tuple insertions, just single tuple deletions, special set-based insertions and/or deletions, or combinations thereof. The view maintenance algorithms may also need to maintain auxiliary relations to help maintain the views of interest. It is of interest to know the minimal arity necessary for these auxiliary relations and whether the auxiliary relations are deterministic. While many results are known about these issues for several settings, many further challenging research problems still remain to be solved.

Background, Reserve, and Gandy Machines

Abstract: The reserve of a state of an abstract state machine was defined to be a "naked set". In applications, it may be convenient to have tuples, sets, lists, arrays, etc. defined ahead of time on all elements, including the reserve elements. We generalize the notion of reserve appropriately. As an application, we solve a foundational problem in Gandy's formalization of mechanical devices.

Method and system for generating a statistical summary of a database using a join synopsis

Abstract: A method for generating an approximate answer to a query in a database environment in which the database has a plurality of base relations. A query relating to a database is received, and an approximate answer to the query is generated such that the approximate answer is based on at least one join synopsis formed from the database. The method further includes steps of forming a sample-tuple set for at least one selected base relation of a plurality of base relations of a database such that each sample-tuple set contains at least one sample tuple from a corresponding base relation, and forming a join synopsis set for each selected base relation such that each join synopsis set contains a join synopsis for each sample tuple in a sample-tuple set. A join synopsis of a sample tuple is based on a join of the sample tuple and at least one descendent relation of the sample tuple. All join synopsis sets form a statistical summary of the database and are stored.

Coordination and Access Control in Open Distributed Agent Systems: The TuCSoN Approach

Abstract: Coordination and access control are related issues in open distributed agent systems, being both concerned with governing interaction between agents and resources. In particular, while coordination deals with enabling interaction and making it fruitful, access control is meant to control interaction to make it harmless. We argue that this twofold facet has to be supported by a system in a uniform and decentralised manner. To this end, we describe how the application of the TuCSoN tuple-based coordination model over a hierarchical topology is well-suited in this context. On the one hand, policies can be enforced by means of a single mechanism based on tuples and can be scoped to manage access to groups of distributed resources. On the other hand, agents can interact along a hierarchical infrastructure by applying a standard tuple-based communication template. This makes TuCSoN a single coherent framework for the design and development of Internet-based multiagent systems, which takes coordination as the basis for dealing with network topology and access control in a uniform way.

Locality of order-invariant first-order formulas

Abstract: A query is local if the decision of whether a tuple in a structure satisfies this query only depends on a small neighborhood of the tuple. We prove that all queries expressible by order-invariant first-order formulas are local.

Generating union queries using tensor representations

Abstract: Query results and statistics regarding them are generated using a novel representation of an n-attribute relation as an order n relational tensor. Orders of the relational tensor respectively correspond to each of the attributes, and each coordinate along an order relates to a key value of the corresponding attribute. Numeric values are stored in the relational tensor, each numeric value representing a count of tuples having the attribute key values that correspond to the coordinate of the numeric value along the orders of the relational tensor. This storage representation is useful in a variety of contexts for enhancing the performance of a RDBMS system. Specifically, a data-representing relational tensor can be used to produce results for tuple grouping operations such as the SQL operations COUNT . . . GROUP BY, SUM . . . GROUP BY, AVG . . . GROUP BY, MIN . . . GROUP BY and MAX . . . GROUP BY.

Optimization and evaluation of disjunctive queries

Abstract: It is striking that the optimization of disjunctive queries-i.e. those which contain at least one OR-connective in the query predicate-has been vastly neglected in the literature, as well as in commercial systems. In this paper, we propose a novel technique, called bypass processing, for evaluating such disjunctive queries. The bypass processing technique is based on new selection and join operators that produce two output streams: the TRUE-stream with tuples satisfying the selection (join) predicate and the FALSE-stream with tuples not satisfying the corresponding predicate. Splitting the tuple streams in this way enables us to "bypass" costly predicates whenever the "fate" of the corresponding tuple (stream) can be determined without evaluating this predicate. In the paper, we show how to systematically generate bypass evaluation plans utilizing a bottom-up building-block approach. We show that our evaluation technique allows us to incorporate the standard SQL semantics of null values. For this, we devise two different approaches: one is based on explicitly incorporating three-valued logic into the evaluation plans; the other one relies on two-valued logic by "moving" all negations to atomic conditions of the selection predicate. We describe how to extend an iterator-based query engine to support bypass evaluation with little extra overhead. This query engine was used to quantitatively evaluate the bypass evaluation plans against the traditional evaluation techniques utilizing a CNFor DNF-based query predicate.

Universal test generation using fault tuples

Abstract: A test generation tool for combinational circuits called FATGEN has been developed based on the notion of fault tuples. FATGEN can be used to simultaneously generate tests for many types of misbehavior that occur in digital systems. Individual experiments involving SSL, transistor stuck-open, path delay and bridging faults for the ISCAS85 benchmark circuits reveal an average speedup of nearly 32% and test set compaction of 60% when faults of all types are analyzed simultaneously. In addition, there is an average reduction of approximately 34% in the number of aborted faults.

Shared computation of user-defined metrics in an on-line analytic processing system

Abstract: An On-Line Analytic Processing (OLAP) system computes complex expressions and aggregations in queries by re-using and sharing subparts of the expressions and aggregations. A dependency generation phase performed by the OLAP system identifies dependencies among metrics based on the expressions, aggregations, and other metrics used by the metrics. An access plan generation phase performed by the OLAP system generates an access plan based on the identified dependencies, wherein the access plan ensures that expressions, aggregations, and metrics are computed before they are needed, and that required values and intermediate results are passed up a tree structure of the access plan until they are used or consumed by some operator. An operator assignment phase performed by the OLAP system generates operators based on the access plan, and also generates project list expressions, aggregations to be computed in each operator, and input and output tuple types for each operator.

Exploiting early sorting and early partitioning for decision support query processing

Abstract: Decision support queries typically involve several joins, a grouping with aggregation, and/or sorting of the result tuples. We propose two new classes of query evaluation algorithms that can be used to speed up the execution of such queries. The algorithms are based on (1) early sorting and (2) early partitioning– or a combination of both. The idea is to push the sorting and/or the partitioning to the leaves, i.e., the base relations, of the query evaluation plans (QEPs) and thereby avoid sorting or partitioning large intermediate results generated by the joins. Both early sorting and early partitioning are used in combination with hash-based algorithms for evaluating the join(s) and the grouping. To enable early sorting, the sort order generated at an early stage of the QEP is retained through an arbitrary number of so-called order-preserving hash joins. To make early partitioning applicable to a large class of decision support queries, we generalize the so-called hash teams proposed by Graefe et al. [GBC98]. Hash teams allow to perform several hash-based operations (join and grouping) on the same attribute in one pass without repartitioning intermediate results. Our generalization consists of indirectly partitioning the input data. Indirect partitioning means partitioning the input data on an attribute that is not directly needed for the next hash-based operation, and it involves the construction of bitmaps to approximate the partitioning for the attribute that is needed in the next hash-based operation. Our performance experiments show that such QEPs based on early sorting, early partitioning, or both in combination perform significantly better than conventional strategies for many common classes of decision support queries.

On Timed Coordination Languages

Abstract: Although very simple and elegant, Linda-style coordination models lack the notion of time, and are therefore not able to precisely model real-life coordination applications, featuring time-outs and soft real-time constraints. This paper aims at introducing time in these models. To that end, we consider two notions of time, relative time and absolute time, and, for each notion, two types of features. On the one hand, with respect to relative time, we describe two extensions: (i) a delay mechanism to postpone the execution of communication primitives, and (ii) explicit deadlines on the validity of tuples and on the duration of suspension of communication operations. On the other hand, for absolute time, we introduce: (iii) a wait primitive capable of waiting till an absolute point of time, and (iv) time intervals, both on tuples in the data store and on communication operations. The resulting four coordination models are analyzed and compared both from the semantics viewpoint and from the implementation viewpoint. Moreover, a few programming examples suggest their practical interest.

Processing by use of synchronized tuple spaces and assertions

Abstract: A system for controlling and coordinating activities among entities in an information and process environment comprising a communications pathway for transmitting and receiving communications of the entities, and a shared memory connected to the communications pathway for maintaining a tuple space on which the entities post and receive messages synchronized to discrete time intervals. An entity in charge of an activity will post an intention in the tuple space for a time, and during that time will receive comments from other interested entities. Upon receipt of comments, the entity decides the best course of action for the intended activity. By soliciting "advice", activities dangerous to the operation of the environment are undertaken in a manner to ensure system degradation does not occur.

OpenSpaces: An Object-Oriented Framework for Reconfigurable Coordination Spaces

Abstract: Tuple spaces have turned out to be one of the most fundamental abstractions for coordinating communicating agents. At the same time, researchers continue to propose new variants of tuple spaces, since no one approach seems to be universally applicable to all problem domains. Some models offer a certain configurability, but existing approaches generally stop at a fixed set of configuration options and static configuration at instantiation time. We argue that a more open approach is needed, and present OPENSPACES, an object-oriented framework that supports static configurability through subclassing across several dimensions, as well as dynamic configurability of policies through run-time composition. We introduce OPENSPACES by showing how it can be used to instantiate a typical application, and we present an overview of the framework, implemented in Smalltalk, detailing the various degrees of configurability.

Introduction to the constraint language NCL

Abstract: The design, implementation and application of a natural constraint language NCL are presented. At the solver level, to support the solving of a large scope of combinatorial problems, a rich set of conventional constraints is defined within a constraint framework that strongly combines Boolean logic, integer constraints and set reasoning over finite domains. The basic computation model for solving conjunctions of elementary constraints with possible existential and universal quantifications is described using rewrite rules. At the language level, to upgrade the expressive power, a natural syntax (context-dependent), which completely adopts mathematical notations, is designed. To enhance the constraint handling capability, quantification, logical switch, referencing mechanism, global/dynamic constraints, meta expressions, multi-criteria optimization, and search specifications are cooperatively introduced in a single constraint system. Compared to existing modeling languages, a strong feature of NCL is: Data, constraints and control are fully integrated and are clearly separable. Especially, though NCL deals with several data types such as Boolean, integer, set, index, reference, array and tuple, there is no need to declare data explicitly. This context-sensitive data typing makes NCL programs direct, concise and liberal.