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7th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Han, Binh Omiecinski, Edward Mark, Leo Liu, Ling Georgia Inst Technol Sch Comp Sci Atlanta GA 30332 USA

ISBN: (纸本)9781936968367

parallel processing is the key to speedup performance and to achieve high throughput in processing large scale data analytical workloads. However, failures of nodes involved in the analytical query can interrupt the whole process, resulting in the complete restart of the query if the system does not have query fault-tolerance. Complete restart might be too costly for processing query on very large databases and might not be able to meet the time constraints in decision support systems. In this paper, we present an approach to resume query processing after failure by keeping track of the point at which data has been processed by an operator, called operator tracking. We also consider saving intermediate results using partial materialization. We look at several fundamental parallel database techniques which are widely used today and analyze the performance cost of query processing and recovery using those techniques with our OTPM fault-tolerance approach. We perform simulation-based experiments which show that our approach incurs only a small resume overhead compared to complete pipelining and complete materialization of intermediate results. Also, the combination of our approach with vertically partitioned database in a sharednothing environment yields the best performance among different settings for parallel processing of data intensive analytical workloads.

关键词： Failure handling fault tolerance analytical processing parallel query processing

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Implementace paralelního zpracování dotazů v databázovém systému PostgreSQL

Implementace paralelního zpracování dotazů v databázov...

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作者： Vojtek, Daniel Charles University of Prague

CONTENTS vi Title: Implementation of parallel query processing in PostgreSQL Author: Bc. Daniel Vojtek Department: Department of Software Engineering Supervisor: Mgr. Július Štroffek Supervisors e-mail address: julo@*** Abstract: parallel query processing can help with processing of huge amounts of data stored in database systems. The aim of this diploma the- sis was to explore the possibilities, analyze, design and finally implement parallel query processing in open source database system PostgreSQL. I used a Master/Worker design pattern, in which standard PostgreSQL backend process is a master. As workers I used processes created from postmaster. In the thesis I focused on preparing an infrastructure nec- essary for parallel processing. I defined a new top level memory context over shared memory, which allows efficient and convenient memory al- locations. Then I implemented creation of new worker processes, based on master process requirements. To be able to control these workers I defined controlling structures using state machines. Then I implemented parallel sort operation and SQL operator UNION ALL using this infras- tructure. The result of this diploma thesis is not only implementation of infrastructure and some parallel operations, but also description of the problems encountered during the...

关键词： parallel query processing PostgreSQL Master Worker paradigm

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An adaptive parallel query processing middleware for the Grid

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2006年第6期18卷 621-634页

作者： Da Silva, V. F. V. Dutra, M. L. Porto, F. Schulze, B. Barbosa, A. C. de Oliveira, J. C. Natl Lab Sci Computat Dept Comp Sci BR-25651075 Petropolis RJ Brazil Pontificia Univ Catolica Rio de Janeiro Dept Informat Rio de Janeiro Brazil Mil Inst Engn Dept Syst Engn Rio De Janeiro Brazil Ecole Polytech Fed Lausanne Sch Comp & Commun Sci Database Lab CH-1015 Lausanne Switzerland Univ Fed Espirito Santo Dept Comp Sci Espirito Santo Brazil

Grid services provide an important abstract layer on top of heterogeneous components (hardware and software) that take part in a Grid environment. In this scenario, applications such as scientific visualization require access to data of non-conventional data types, such as fluid path geometry, and the evaluation of special user programs and algebraic operators, such as spatial hash-join, on these data. In order to support such applications we are developing a Configurable Data Integration Middleware System for the Grid (CoDIMS-G). CoDIMS-G provides a query execution environment adapted to the heterogeneity and variations found in a Grid environment by offering a node scheduling algorithm and an adaptive query execution strategy. The latter both adapts to performance variations in a scheduled node and deals efficiently with repetitive evaluation of a query execution plan fragment, as needed for computing a particle's, trajectory. Copyright (c) 2005 John Wiley & Sons, Ltd.

关键词： middleware Grid services database parallel query processing

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An adaptive parallel query processing middleware for the Grid

An adaptive parallel query processing middleware for the Gri...

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1st International Workshop on Middleware for Grid Computing held in Conjunction with the ACM/IFIP/USINIX Middleware Conference

关键词： middleware Grid services database parallel query processing

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Knuckles: bringing the database to the data

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2010年第3-4期5卷 214-225页

作者： Alvaro, Peter Ryaboy, Dmitriy V. Agrawal, Divyakant Ask Com 555 12th StSuite 500 Oakland CA 94607 USA

Click-stream data warehousing has emerged as a monumental information management and processing challenge for commercial enterprises. Traditional solutions based on commercial DBMS technology often suffer from poor scalability and large processing latencies. Although click-stream data tends to be collected in a distributed manner to support scaling the servers that host the websites, in general these partitioned click-stream logs are collated and pushed upstream to a centralised database storage repository, creating storage bottlenecks. In this paper, we propose a design of an ad-hoc retrieval system suitable for click-stream data warehouses, in which the data remains distributed and database queries are rewritten to be executed against the distributed data. The query rewrite does not involve any centralised control and is therefore highly scalable. The elimination of centralised control is achieved by supporting a restricted subset of SQL, which is sufficient for most click-stream data analysis. Evaluations conducted using both synthetic and real data establish the viability of this approach.

关键词： distributed databases parallel query processing peer-to-peer computing data partitioning

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Efficient scheduling of resources for parallel query processing on grid-based architecture

Efficient scheduling of resources for parallel query process...

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6th Asia-Pacific Symposium on Information and Telecommunication Technologies

作者： Soe, Khin Mar Nwe, Aye Aye Aung, Than Nwe Naing, Thinn Thu Thein, Ni Lar Univ Comp Studies Yangon Myanmar

ISBN: (纸本)4885522161

parallel query processing is an increasingly attractive option for improving the performance of database systems. It can also be important in Grid since grid technologies have enabled sophisticated interaction and data sharing between resources that may belong to different departments or organizations. The decreasing cost of computing makes parallel query processing economically viable to reduce the response time of decision support queries by using parallel execution to exploit inexpensive resources. In this paper, the architecture of resource scheduling and site selection for parallel queries which are to be executed on the Grid is proposed The main aims are to address the problems of choosing appropriate resources and matching sub plans with these resources. For this reason, decisions have to be made on allocating the available processors among a number of competing database operations running in parallel. For scheduling intra-query parallelism, the new approaches, resource-balancing based site selection algorithm which determines where to execute the upcoming operation sequence based on above architecture, and the resource assignment policy for handling the idle nodes' efficiency well, are proposed. This paper also present the architecture Of scheduling inter-query parallelism and proposed hierarchical model in order to fully exploit the available parallelism and interactions among the different queries.

关键词： grid computing parallel query processing distributed query processing

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On Efficient Posting List Intersection with Multicore Processors

On Efficient Posting List Intersection with Multicore Proces...

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32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

作者： Tatikonda, Shirish Junqueira, Flavio Barla Cambazoglu, B. Plachouras, Vassilis Ohio State Univ Columbus OH 43210 USA

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Analyzing imbalance among homogeneous index servers in a web search system

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INFORMATION processing & MANAGEMENT 2007年第3期43卷 592-608页

作者： Badue, C. S. Baeza-Yates, R. Ribeiro-Neto, B. Ziviani, A. Ziviani, N. Univ Fed Minas Gerais Dept Comp Sci BR-31270010 Belo Horizonte MG Brazil Google Engn Belo Horizonte Belo Horizonte MG Brazil Natl Lab Sci Comp LNCC Petropolis Brazil

The performance of parallel query processing in a cluster of index servers is crucial for modern web search systems. In such a scenario, the response time basically depends on the execution time of the slowest server to generate a partial ranked answer. Previous approaches investigate performance issues in this context using simulation, analytical modeling, experimentation, or a combination of them. Nevertheless, these approaches simply assume balanced execution times among homogeneous servers (by uniformly distributing the document collection among them, for instance)-a scenario that we did not observe in our experimentation. On the contrary, we found that even with a balanced distribution of the document collection among index servers, correlations between the frequency of a term in the query log and the size of its corresponding inverted list lead to imbalances in query execution times at these same servers, because these correlations affect disk caching behavior. Further, the relative sizes of the main memory at each server (with regard to disk space usage) and the number of servers participating in the parallel query processing also affect imbalance of local query execution times. These are relevant findings that have not been reported before and that, we understand, are of interest to the research community. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： parallel query processing imbalance search engines performance analysis

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Modeling performance-driven workload characterization of web search systems 06

Modeling performance-driven workload characterization of web...

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15th ACM Conference on Information and Knowledge Management, CIKM 2006

作者： Badue, Claudine Baeza-Yates, Ricardo Ribeiro-Neto, Berthier Ziviani, Artur Ziviani, Nivio Computer Science Dept. Federal University of Minas Gerais Belo Horizonte Brazil Petrópolis Brazil Yahoo Research Barcelona Spain Google Engineering Belo Horizonte Brazil

No abstract available

ISBN: (纸本)1595934332

No abstract available

关键词： performance analysis parallel query processing search engines workload characterization

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Performance analysis of "Groupby-After-Join" query processing in parallel database systems

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INFORMATION SCIENCES 2004年第1-4期168卷 25-50页

作者： Taniar, D Tan, RBN Leung, CHC Liu, KH Monash Univ Sch Business Syst Clayton Vic 3800 Australia Victoria Univ MCMC Sch Comp Sci & Math Melbourne Vic 8001 Australia Blueridge Syst Ocean NJ 07712 USA

Queries containing aggregate functions often combine multiple tables through join operations. This query is subsequently called "Groupby-Join". There is a special category of this query whereby the group-by operation can only be performed after the join operation. This is known as "Groupby-After-Join" queries-the focus of this paper. In parallel processing of such queries, it must be decided which attribute is used as a partitioning attribute, particularly join attribute or group-by attribute. Based on the partitioning attribute, two parallel processing methods, namely join partition method (JPM) and aggregate partition method (APM) are discussed. The behaviours of these parallelization methods are described in terms of cost models. Experiments are performed based on simulations. The simulation results show that the aggregate partition method performs better than the join partition method. (C) 2004 Elsevier Inc. All rights reserved.

关键词： Groupby queries Groupby-Join queries parallel query processing parallel query optimization parallel databases performance analysis

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