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Parallel Load And Query Processing In A Distributed Array Database
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Book Synopsis Parallel Load and Query Processing in a Distributed Array Database by : Qian Long (M. Eng.)
Download or read book Parallel Load and Query Processing in a Distributed Array Database written by Qian Long (M. Eng.) and published by . This book was released on 2015 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientists across many research domains collect large amounts of multi-dimensional data in their day to day work. They require high performance, scalable systems to manage and process their data. Oftentimes, the underlying distribution of these types of data is skewed and sparse, rather than dense and uniform. As input data sizes continue to grow at a rapid rate, main memory and storage capacity become bottlenecks on single machines. Thus, we look to distributed array databases as a long term solution for managing and querying this type of data. This thesis presents Multinode-TileDB, a distributed framework that extends TileDB, a new array database management system designed, from the ground up, to handle skewed and sparse arrays. We design the overall distributed architecture and propose and implement parallel algorithms for load, join, subarray, and filter while focusing on load balance and performance. Our experiments show speedup gains as cluster size increases and how different data partitioning schemes benefit the different parallel queries.
Book Synopsis High-Performance Parallel Database Processing and Grid Databases by : David Taniar
Download or read book High-Performance Parallel Database Processing and Grid Databases written by David Taniar and published by John Wiley & Sons. This book was released on 2008-09-17 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest techniques and principles of parallel and grid database processing The growth in grid databases, coupled with the utility of parallel query processing, presents an important opportunity to understand and utilize high-performance parallel database processing within a major database management system (DBMS). This important new book provides readers with a fundamental understanding of parallelism in data-intensive applications, and demonstrates how to develop faster capabilities to support them. It presents a balanced treatment of the theoretical and practical aspects of high-performance databases to demonstrate how parallel query is executed in a DBMS, including concepts, algorithms, analytical models, and grid transactions. High-Performance Parallel Database Processing and Grid Databases serves as a valuable resource for researchers working in parallel databases and for practitioners interested in building a high-performance database. It is also a much-needed, self-contained textbook for database courses at the advanced undergraduate and graduate levels.
Book Synopsis Query Processing in Parallel Relational Database Systems by : Hongjun Lu
Download or read book Query Processing in Parallel Relational Database Systems written by Hongjun Lu and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1994 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides readers with a background knowledge of parallel database query processing and optimization and covers recent developments in the field. Subjects include design approaches, architecture of parallel database systems, parallel sorting, parallel processing of join, data skew and load balancing,
Book Synopsis Scalable Distributed Query Processing in Parallel Main-memory Database Systems by : Wolf-Steffen Rödiger
Download or read book Scalable Distributed Query Processing in Parallel Main-memory Database Systems written by Wolf-Steffen Rödiger and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithms and Architectures for Parallel Processing by : Guojun Wang
Download or read book Algorithms and Architectures for Parallel Processing written by Guojun Wang and published by Springer. This book was released on 2015-11-16 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four volume set LNCS 9528, 9529, 9530 and 9531 constitutes the refereed proceedings of the 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015. The 219 revised full papers presented together with 77 workshop papers in these four volumes were carefully reviewed and selected from 807 submissions (602 full papers and 205 workshop papers). The first volume comprises the following topics: parallel and distributed architectures; distributed and network-based computing and internet of things and cyber-physical-social computing. The second volume comprises topics such as big data and its applications and parallel and distributed algorithms. The topics of the third volume are: applications of parallel and distributed computing and service dependability and security in distributed and parallel systems. The covered topics of the fourth volume are: software systems and programming models and performance modeling and evaluation.
Book Synopsis Euro-Par 2003 Parallel Processing by : Harald Kosch
Download or read book Euro-Par 2003 Parallel Processing written by Harald Kosch and published by Springer. This book was released on 2004-06-01 with total page 1324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Euro-ParConferenceSeries The European Conference on Parallel Computing (Euro-Par) is an international conference series dedicated to the promotion and advancement of all aspects of parallel and distributed computing. The major themes fall into the categories of hardware, software, algorithms, and applications. This year, new and interesting topicswereintroduced,likePeer-to-PeerComputing,DistributedMultimedia- stems, and Mobile and Ubiquitous Computing. For the ?rst time, we organized a Demo Session showing many challenging applications. The general objective of Euro-Par is to provide a forum promoting the de- lopment of parallel and distributed computing both as an industrial technique and an academic discipline, extending the frontiers of both the state of the art and the state of the practice. The industrial importance of parallel and dist- buted computing is supported this year by a special Industrial Session as well as a vendors’ exhibition. This is particularly important as currently parallel and distributed computing is evolving into a globally important technology; the b- zword Grid Computing clearly expresses this move. In addition, the trend to a - bile world is clearly visible in this year’s Euro-Par. ThemainaudienceforandparticipantsatEuro-Parareresearchersinaca- mic departments, industrial organizations, and government laboratories. Euro- Par aims to become the primary choice of such professionals for the presentation of new results in their speci?c areas. Euro-Par has its own Internet domain with a permanent Web site where the history of the conference series is described: http://www.euro-par.org. The Euro-Par conference series is sponsored by the Association for Computer Machinery (ACM) and the International Federation for Information Processing (IFIP).
Book Synopsis Principles of Distributed Database Systems by : M. Tamer Özsu
Download or read book Principles of Distributed Database Systems written by M. Tamer Özsu and published by Springer Science & Business Media. This book was released on 2011-02-24 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: • New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. • Coverage of emerging topics such as data streams and cloud computing • Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.
Book Synopsis Parallel Query Processing Using Shared Memory Multiprocessors and Disk Arrays by : Wei Hong
Download or read book Parallel Query Processing Using Shared Memory Multiprocessors and Disk Arrays written by Wei Hong and published by . This book was released on 1992 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Euro-Par '96 - Parallel Processing by : Luc Bouge
Download or read book Euro-Par '96 - Parallel Processing written by Luc Bouge and published by Springer Science & Business Media. This book was released on 1996-08-14 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #Includes bibliographical references and index.
Book Synopsis Multi-versioned Data Storage and Iterative Processing in a Parallel Array Database Engine by : Emad Soroush
Download or read book Multi-versioned Data Storage and Iterative Processing in a Parallel Array Database Engine written by Emad Soroush and published by . This book was released on 2014 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientists today are able to generate data at an unprecedented scale and rate. For example the Sloan Digital Sky Survey (SDSS) generates 200GB of data containing millions of objects on each night on its routine operation. The large hadron collider is producing even more data today which is approximately 30PB annually. The Large Synoptic Survey Telescope (LSST) also will be producing approximately 30TB of data per night in a few years. Also, in many fields of science, multidimensional arrays rather than flat tables are standard data types because data values are associated with coordinates in space and time. For example, images in astronomy are 2D arrays of pixel intensities. Climate and ocean models use arrays or meshes to describe 3D regions of the atmosphere and oceans. As a result, scientists need powerful tools to help them manage massive arrays. This thesis focuses on various challenges in building parallel array data management systems that facilitate massive-scale data analytics over arrays. The first challenge with building an array data processing system is simply how to store arrays on disk. The key question is how to partition arrays into smaller fragments called chunks that form the unit of IO, processing, and data distribution across machines in a cluster. We explore this question in ArrayStore, a new read-only storage manager for parallel array processing. In ArrayStore, we study the impact of different chunking strategies on query processing performance for a wide range of operations, including binary operators and user-defined functions. ArrayStore also proposes two new techniques that enable operators to access data from adjacent array fragments during parallel processing. The second challenge that we explore in building array systems is the ability to create, archive, and explore different versions of the array data. We address this question in TimeArr, a new append-only storage manager for an array database. Its key contribution is to efficiently store and retrieve versions of an entire array or some sub-array. To achieve high performance, TimeArr relies on several techniques including virtual tiles, bitmask compression of changes, variable-length delta representations, and skip links. The third challenge that we tackle in building parallel array engines is how to provide efficient iterative computation on multi-dimensional scientific arrays. We present the design, implementation, and evaluation of ArrayLoop, an extension of SciDB with native support for array iterations. In the context of ArrayLoop, we develop a model for iterative processing in a parallel array engine. We then present three optimizations to improve the performance of these types of computations: incremental processing, mini-iteration overlap processing, and multi-resolution processing. Finally, as motivation for our work and also to help push our technology back into the hands of science users, we have built the AscotDB system. AscotDB is a new, extensible data analysis system for the interactive analysis of data from astronomical surveys. AscotDB provides a compelling and powerful environment for the exploration, analysis, visualization, and sharing of large array datasets.
Book Synopsis Euro-Par'96 - Parallel Processing by : Luc Bougé
Download or read book Euro-Par'96 - Parallel Processing written by Luc Bougé and published by Springer Science & Business Media. This book was released on 1996-08-14 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #Includes bibliographical references and index.
Book Synopsis Scalable High Performance Computing for Knowledge Discovery and Data Mining by : Paul Stolorz
Download or read book Scalable High Performance Computing for Knowledge Discovery and Data Mining written by Paul Stolorz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scalable High Performance Computing for Knowledge Discovery and Data Mining brings together in one place important contributions and up-to-date research results in this fast moving area. Scalable High Performance Computing for Knowledge Discovery and Data Mining serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Book Synopsis A Load Balancing Data Allocation for Parallel Query Processing by : Wen-Ya Lin
Download or read book A Load Balancing Data Allocation for Parallel Query Processing written by Wen-Ya Lin and published by . This book was released on 1998 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parallel Information Processing by : J. A. Keane
Download or read book Parallel Information Processing written by J. A. Keane and published by . This book was released on 1996 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications by : Wang, John
Download or read book Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications written by Wang, John and published by IGI Global. This book was released on 2008-05-31 with total page 4092 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
Book Synopsis Query Processing for Massively Parallel Systems by : Paraschos Koutris
Download or read book Query Processing for Massively Parallel Systems written by Paraschos Koutris and published by . This book was released on 2015 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need to analyze and understand big data has changed the landscape of data management over the last years. To process the large amounts of data available to users in both industry and science, many modern data management systems leverage the power of massive parallelism. The challenge of scaling computation to thousands of processing units demands that we change our thinking on how we design such systems, and on how we analyze and design parallel algorithms. In this dissertation, I study the fundamental problem of query processing for modern massively parallel architectures. I propose a theoretical model, the MPC model (Massively Parallel Computation), to analyze the performance of parallel algorithms for query processing. In the MPC model, the data is initially evenly distributed among p servers. The computation proceeds in rounds: each round consists of some local computation followed by global exchange of data between the servers. The computational complexity of an algorithm is characterized by both the number of rounds necessary, and the maximum amount of data, or maximum load, that each processor receives. The challenge is to identify the optimal tradeoff between the number of rounds and maximum load for various computational tasks. As a first step towards understanding query processing in the MPC model, we study conjunctive queries (multiway joins) for a single round. We show that a particular type of distributed algorithm, the HyperCube algorithm, can optimally compute join queries when restricted to one communication round and data without skew. In most real-world applications, data has skew (for example a graph with nodes of large degree) that causes an uneven distribution of the load, and thus reduces the effectiveness of parallelism. We show that the HyperCube algorithm is more resilient to skew than traditional parallel query plans. To deal with any case of skew, we also design data-sensitive techniques that identify the outliers in the data and alleviate the effect of skew by further splitting the computation to more servers. In the case of multiple rounds, we present nearly optimal algorithms for conjunctive queries for the case of data without skew. A surprising consequence of our results is that they can be applied to analyze iterative computational tasks: we can prove that, in order to compute the connected components of a graph, any algorithm requires more than a constant number of communication rounds. Finally, we show a surprising connection of the MPC model with algorithms in the external memory model of computation.
Book Synopsis Foundations of Data Organization and Algorithms by : David B. Lomet
Download or read book Foundations of Data Organization and Algorithms written by David B. Lomet and published by Springer Science & Business Media. This book was released on 1993-09-29 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the Fourth International Conference on Data Organization and Algorithms, FODO '93, held in Evanston, Illinois. FODO '93 reflects the maturing of the database field which hasbeen driven by the enormous growth in the range of applications for databasesystems. The "non-standard" applications of the not-so-distant past, such ashypertext, multimedia, and scientific and engineering databases, now provide some of the central motivation for the advances in hardware technology and data organizations and algorithms. The volume contains 3 invited talks, 22 contributed papers, and 2 panel papers. The contributed papers are grouped into parts on multimedia, access methods, text processing, query processing, industrial applications, physical storage, andnew directions.
