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Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization

作者： Haicheng Wu Gregory Diamos Tim Sheard Molham Aref Sean Baxter Michael Garland Sudhakar Yalamanchili Georgia Institute of Technology NVIDIA Portland State University LogicBlox Inc.

ISBN: (纸本)9781450326704

Modern enterprise applications represent an emergent application arena that requires the processing of queries and computations over massive amounts of data. Large-scale, multi-GPU cluster systems potentially present a vehicle for major improvements in throughput and consequently overall performance. However, throughput improvement using GPUs is challenged by the distinctive memory and computational characteristics of relational Algebra (RA) operators that are central to queries for answering business *** paper introduces the design, implementation, and evaluation of Red Fox, a compiler and runtime infrastructure for executing relational queries on GPUs. Red Fox is comprised of i) a language front-end for LogiQL which is a commercial query language, ii) an RA to GPU compiler, iii) optimized GPU implementation of RA operators, and iv) a supporting runtime. We report the performance on the full set of industry standard TPC-H queries on a single node GPU. Compared with a commercial LogiQL system implementation optimized for a state of art CPU machine, Red Fox on average is 6.48x faster including PCIe transfer time. We point out key bottlenecks, propose potential solutions, and analyze the GPU implementation of these queries. To the best of our knowledge, this is the first reported end-to-end compilation and execution infrastructure that supports the full set of TPC-H queries on commodity GPUs.

关键词： relational query processing GPU

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Top-k query processing in Probabilistic Databases with Non-Materialized Views

Top-k Query Processing in Probabilistic Databases with Non-M...

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29th IEEE International Conference on Data Engineering (ICDE)

作者： Dylla, Maximilian Miliaraki, Iris Theobald, Martin Max Planck Inst Informat Campus E1-4 D-66123 Saarbrucken Germany Univ Antwerp B-2020 Antwerp Belgium

ISBN: (纸本)9781467349093;9781467349086

We investigate a novel approach of computing confidence bounds for top-k ranking queries in probabilistic databases with non-materialized views. Unlike related approaches, we present an exact pruning algorithm for finding the top-ranked query answers according to their marginal probabilities without the need to first materialize all answer candidates via the views. Specifically, we consider conjunctive queries over multiple levels of select-project-join views, the latter of which are cast into Datalog rules which we ground in a top-down fashion directly at query processing time. To our knowledge, this work is the first to address integrated data and confidence computations for intensional query evaluations in the context of probabilistic databases by considering confidence bounds over first-order lineage formulas. We extend our query processing techniques by a tool-suite of scheduling strategies based on selectivity estimation and the expected impact on confidence bounds. Further extensions to our query processing strategies include improved top-k bounds in the case when sorted relations are available as input, as well as the consideration of recursive rules. Experiments with large datasets demonstrate significant runtime improvements of our approach compared to both exact and sampling-based top-k methods over probabilistic data.

关键词： query analysis confidence Bound Database View Exact distributed query processing relational query processing

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MULTIPROCESSOR JOIN SCHEDULING

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1993年第2期5卷 322-338页

作者： MURPHY, MC ROTEM, D SAN FRANCISCO STATE UNIV DEPT COMP SCISAN FRANCISCOCA 94132 SAN JOSE STATE UNIV SCH BUSINESSDEPT MKT & QUANT STUDIESSAN JOSECA 95192

Multiprocessors provide a cost effective high performance alternative for relational join execution. While traditional query processing algorithms can be effectively utilized to realize interquery parallelism, they are not well suited to exploiting intraquery parallelism. In this paper we present a practical join processing strategy which allows effective utilization of arbitrary degrees of parallelism in both the I/O subsystem and join processing (processor) subsystems. Analytic bounds on the minimum execution time, minimum number of processors, and processor utilization are presented along with bounds on the execution time given a fixed number of processors. These bounds assume sufficient buffers are available. We present an analytic lower bound on buffer requirements as well as a practical heuristic for use in limited buffer environments. The paper concludes with a sampling of corroborative simulation results.

关键词： DATABASE SYSTEMS JOIN SCHEDULING MULTIPROCESSOR APPLICATIONS PARALLEL COMPUTATION relational query processing SYSTEM PERFORMANCE EVALUATION

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An Autonomic in-Network query processing for Urban Sensor Networks

An Autonomic in-Network Query Processing for Urban Sensor Ne...

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IEEE Symposium on Computers and Communication

作者： Marcos A. Carrero Rone I. da Silva Aldri L. dos Santos Carmem S. Hara DINF-Universidade Federal do Parana - UFPR-Parana DTECH - Universidade Federal de Sao Joao del-Rei - UFSJ - Minas Gerais

ISBN: (纸本)9781467371957

The sensing of urban environments usually takes into account the deployment of a large number of devices to measure their environmental attributes, such as temperature, pressure, humidity, luminosity and pollution. In such applications, nearby sensors usually produce similar readings due to their spatial and temporal correlation. In the era of big data, management of collected data requires autonomous and scalable Wireless Sensor Network (WSN) structures. In this paper, we propose an in-network data storage model, called AQPM, that provides efficient processing of both spatial and value-based queries. AQPM is autonomous and scalable. That is, it does not rely on any central entity for neither managing data storage on sensor devices nor for processing queries. Scalability is achieved by grouping sensors with similar readings into clusters, while efficient query processing relies on the concept of repositories. Repositories are sensors that store readings of a set of clusters, and are the only ones that have to be contacted for answering queries. AQPM has been implemented on NS2 simulator and experimental results show that it is more effective than existing approaches.

关键词： distributed query processing relational query processing query analysis reading Scalability Sensors Data Storage Wireless sensor networks WAREHOUSE Sensor networks Data Collection Methods

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Performance and scalability of XML query processing

Performance and scalability of XML query processing

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International Conference on Complex, Intelligent and Software Intensive Systems

作者： Gaetan HAINS Muath ALRAMMAL Laboratoire d'Algorithmique Complexite et Logique Universite Paris-Est

ISBN: (纸本)9781467312332

This paper discusses basic issues about the performance of semi-structured query processing in very large datasets. It is based on recent algorithm-engineering work, on the state of the art in performance management for XML query processing and on theoretical studies about the complexity structure of the querying problem. Its main conclusions provide a concrete view on the interaction between terabyte scale XML data, query complexity and current or future computer architectures. To provide a concrete and synthetic view of this diverse body of knowledge, the presentation follows a fictional use case whose characters face query problems of varying complexity that are set in multiple contexts and analyzed today before being projected to 2020 and 2030.

关键词： Parallel and stream-processing for XML queries Scalability of queries and XPath fragments Optimization of data mining applications that use XML databases query analysis extensible markup language Scalability Computer Architecture distributed query processing relational query processing Performance management Concrete Theoretical Study

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Supporting quantified queries in distributed databases

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INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS 2014年第5期29卷 421-459页

作者： Badia, Antonio Dobbs, Michael Univ Louisville Comp Engn & Comp Sci Dept Louisville KY 40292 USA Amazon Seattle WA 98109 USA

We show that some relational queries, which we call quantified queries are not well supported in distributed environments. We give a formal definition of quantified queries, propose a language in which to express said queries and provide a procedure to compute answers in this new language in the context of distributed databases. The proposed language is made up of high-level, declarative operators (called generalised quantifiers), and therefore it can be used in combination with several distributed frameworks. Our approach is designed to be as general as possible;it assumes horizontally partitioned relations, but nothing else, so no data placement or replication is used. We present an implementation and algorithms for the new language, propose some basic optimisations and give experimental results which show that the new approach is indeed quite efficient and scales well.

关键词： distributed query processing relational query processing generalised quantifiers

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A GENERALIZED IMPLEMENTATION METHOD FOR relational DATA SUBLANGUAGES

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1980年第2期6卷 152-162页

作者： BECK, LL Department of Computer Science and Engineering Southern Methodist University

A set of primitive operations on tuples is derived; it is shown that these operations are necessary and sufficient for the implementation tion of any language equivalent in power to the relational algebra. The translation of queries from a variety of relational languages into these tuple operations is discussed and illustrated with several examples. A method is given for the conversion of such a translated query into a network of processes and files. An optimization algorithm which operates on this network is described and demonstrated. Using this method, many different relational languages can be implemented using the same data management software; furthermore, the underlying software can be changed without requiring any changes at the user interface. This approach should yield great benefits in reduced cost and increased flexibility of implementation.

关键词： relational query Translation DBMS Independence Process Networks query Optimization relational Database Implementation relational query processing

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Branch Code: A Labeling Scheme for Efficient query Answering on Trees

Branch Code: A Labeling Scheme for Efficient Query Answering...

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28th IEEE International Conference on Data Engineering (ICDE)

作者： Xiao, Yanghua Hong, Ji Cui, Wanyun He, Zhenying Wang, Wei Feng, Guodong Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

ISBN: (纸本)9781467300421

Labeling schemes lie at the core of query processing for many tree-structured data such as XML data that is flooding the web. A labeling scheme that can simultaneously and efficiently support various relationship queries on trees (such as parent/children, descendant/ancestor, etc.), computation of lowest common ancestors (LCA) and update of trees, is desired for effective and efficient management of tree-structured data. Although a variety of labeling schemes such as prefix-based labeling, interval-based labeling and prime-based labeling as well as their variants have been available to us for encoding static and dynamic trees, these labeling schemes usually show weakness in one aspect or another. In this paper, we propose an integer-based labeling scheme branch code as well as its compressed version as our major solution to simultaneously support efficient query processing on both static and dynamic ordered trees with affordable storage cost. The proposed branch code can answer common queries on ordered trees in constant time, which comes at the cost of consuming O(N logN) storage. To reduce storage cost to O(N), a compressed branch code is further developed. We also give a relationship determination algorithm purely using compressed branch code, which is of quite low possibility to produce false positive results as verified by experimental results. With the support of splay trees, branch code can also support dynamic trees so that updates and queries can be implemented with O(logN) amortized cost. All the results above are either theoretically proved or verified by experimental studies.

关键词： labeling scheme branches Codes query analysis distributed query processing relational query processing

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Selectivity Estimation for Extraction Operators over Text Data

Selectivity Estimation for Extraction Operators over Text Da...

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IEEE 27th International Conference on Data Engineering (ICDE 2011)

作者： Wang, Daisy Zhe Wei, Long Li, Yunyao Reiss, Frederick Vaithyanathan, Shivakumar Univ Calif Berkeley Berkeley CA 94720 USA IBM Corp Almaden Res Ctr San Jose CA 95120 USA

ISBN: (纸本)9781424489589

Recently, there has been increasing interest in extending relational query processing to efficiently support extraction operators, such as dictionaries and regular expressions, over text data. Many text processing queries are sophisticated in that they involve multiple extraction and join operators, resulting in many possible query plans. However, there has been little research on building the selectivity or cost estimation for these extraction operators, which is crucial for an optimizer to pick a good query plan. In this paper, we define the problem of selectivity estimation for dictionaries and regular expressions, and propose to develop document synopses over a text corpus, from which the selectivity can be estimated. We first adapt the language models in the Natural Language processing literature to form the top-k n-gram synopsis as the baseline document synopsis. Then we develop two classes of novel document synopses: stratified bloom filter synopsis and roll-up synopsis. We also develop techniques to decompose a complicated regular expression into subparts to achieve more effective and accurate estimation. We conduct experiments over the Enron email corpus using both real-world and synthetic workloads to compare the accuracy of the selectivity estimation over different classes and variations of synopses. The results show that, the top-k stratified bloom filter synopsis and the roll-up synopsis is the most accurate in dictionary and regular expression selectivity estimation respectively.

关键词： Accuracy Adaptation model Arrays Blogs Data mining Dictionaries Enron email corpus Estimation data structures database management dictionaries dictionaries document synopses extraction operators join operators natural language processing natural language processing query processing regular expressions relational query processing roll-up synopsis selectivity estimation text analysis text data text processing queries top-k stratified bloom filter synopsis

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querying Complex Spatio-Temporal Sequences in Human Motion Databases

Querying Complex Spatio-Temporal Sequences in Human Motion D...

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IEEE 24th International Conference on Data Engineering (ICDE 2008), vol.1

作者： Yueguo Chen Shouxu Jiang Beng Chin Ooi Anthony K. H. Tung School of Computing National University of Singapore Singapore School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424418367;1424418364

Content-based retrieval of spatio-temporal patterns from human motion databases is inherently nontrivial since finding effective distance measures for such data is difficult. These data are typically modelled as time series of high dimensional vectors which incur expensive storage and retrieval cost as a result of the high dimensionality. In this paper, we abstract such complex spatio-temporal data as a set of frames which are then represented as high dimensional categorical feature vectors. New distance measures and queries for high dimensional categorical time series are then proposed and efficient query processing techniques for answering these queries are developed. We conducted experiments using our proposed distance measures and queries on human motion capture databases. The results indicate that significant improvement on the efficiency of query processing of categorical time series (more than 10,000 times faster than that of the original motion sequences) can be achieved while guaranteeing the effectiveness of the search.

关键词： distance measurement Human motion Time series query analysis Effective firing range Database Content retrieval Categorical Nominal DIMENSIONAL distributed query processing relational query processing

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