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Spatial Data Dynamic Balancing Distribution Method Based on the Minimum Spatial Proximity for Parallel Spatial Database
2011
Journal of Software
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decomposing Hilbert space-filling curve code to allocate approximately even spatial data volume to parallel nodes in distributed network. ...
Spatial data balancing distribution can evidently improve the performance of parallel spatial database in shared nothing parallel architecture. ...
Data balancing distribution is one of the most important factors to improve the performance of parallel spatial database under shared nothing parallel architecture [2] . ...
doi:10.4304/jsw.6.7.1337-1344
fatcat:dz4esgdw7fhbndly3p34chxvze
Transaction Management in Distributed Scheduling Environment for High Performance Database Applications
[chapter]
2003
Lecture Notes in Computer Science
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Though high performance database systems like distributed and parallel database systems distribute data to different sites, most of the systems tend to nominate a single node to manage all relevant information ...
The problem of synchronisation increases many folds, as the nature of application becomes distributed or volume of data approaches to terabyte sizes. ...
Introduction Continuously growing volume of data and expanding business needs have justified the needs of high performance database systems like Distributed and Parallel Database Systems (PDS) [2, 8, ...
doi:10.1007/978-3-540-24604-6_12
fatcat:ruq4cm34gjbkbkzrkxwucfkula
Just-In-Time Data Distribution for Analytical Query Processing
[chapter]
2012
Lecture Notes in Computer Science
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In this paper, we explore an alternative approach that starts from a master node in control of the complete database, and a variable number of worker nodes for delegated query processing. ...
Our experiments show that the proposed adaptive distributed architecture is a viable and flexible alternative for small scale MapReduce-type of settings. ...
This work was partially supported by the Dutch research programme COMMIT and the European project TELEIOS. ...
doi:10.1007/978-3-642-33074-2_16
fatcat:aawgczggwvc2dadn6wo62pklma
Secure two-party k-means clustering
2007
Proceedings of the 14th ACM conference on Computer and communications security - CCS '07
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of software,Journal of
Parallel and Distributed Computing,
Volume 66 , ,Issue 9 (September 2006),Special issue:
Security in grid and distributed systems,Pages: 1116 -
1128 ,Year of Publication: 2006 ...
"Query optimization distributed networks of autonomous database systems" Journal in Transactions on Database Systems. pp. 561-565. Volume 31, Issue 2 june 2006. ...
doi:10.1145/1315245.1315306
dblp:conf/ccs/BunnO07
fatcat:hv3vdom7kfhp7llmhvsvmdierm
Comparative Study of Apriori Algorithms for Parallel Mining of Frequent Itemsets
2014
International Journal of Computer Applications
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The parallel frequent itemsets mining algorithms addresses the issue of distributing the candidates among processors such that their counting and creation is effectively parallelized. ...
Thus majority of parallel apriori algorithms focus on parallelizing the process of frequent item set discovery. ...
PARALLEL APRIORI ALGORITHMS 4.1 Count Distribution Algorithm [10] Each processor generates the partial support of all candidate itemsets from its local database partition in parallel. ...
doi:10.5120/15594-4337
fatcat:flcabqaxenapvgyuw6rvrecfxy
Benchmarking SciDB data import on HPC systems
2016
2016 IEEE High Performance Extreme Computing Conference (HPEC)
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2016 pre-print arXiv:1609.07545v1 fatcat:dy2g4xuyvve5jjzd4aioylc5ue
This performance was achieved by using parallel inserts, a in-database merging of arrays as well as supercomputing techniques, such as distributed arrays and single-program-multiple-data programming. ...
It is designed to be massively parallel and can run on commodity hardware in a high performance computing (HPC) environment. ...
We would also like to thank David Martinez (Associate Division Head, Cyber Security and Information Sciences, MIT Lincoln Laboratory) and Dr. ...
doi:10.1109/hpec.2016.7761617
dblp:conf/hpec/SamsiBABBBGHJKM16
fatcat:swikmonoura5tkgwowidvutaqe
Data Dissemination and Parallel Processing Techniques Research Based on Massively Parallel Processing
2017
DEStech Transactions on Computer Science and Engineering
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In the current distributed database system architecture enterprise-class, the massively parallel processing architecture is used frequently. ...
Experimental results show that the proposed MPP data distribution and parallel processing scheme can support large volume of data processing, ensuring data consistency in the premise of improving query ...
Figure 2 . 2 Basic Schematic Diagram of Distributed System Resource Management.
Figure 3 . 3 Distributed MPP Data Distribution and Parallel Processing. ...
doi:10.12783/dtcse/wcne2016/5115
fatcat:yixho4cqera5tdq43brejx7hwq
Evolution of data management systems
2012
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services - IIWAS '12
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Valduriez, : "Parallel Database Systems: Open Problems and News Issues", in: Distributed and Parallel DB, Vol. 1, pp. 137--165, Kluwer Academic, (1993) • H. ...
., "Query Processing in Parallel Relational Database Systems", IEEE CS Press, 1994 • D. Taniar et al., "High Performance Parallel DB Processing and Grid Databases", Ed. Wiley, 2008 • A. ...
doi:10.1145/2428736.2428738
dblp:conf/iiwas/Hameurlain12
fatcat:ayoxhgsd7nfcrk6pbph3s6psy4
Design of Electric Energy Acquisition System on Hadoop
2015
International Journal of Grid and Distributed Computing
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and parallel processed from the nodes. ...
Recently, the environment of high performance distributed network parallel computation, represented by Hadoop architecture, is deployed step by step [4] . ...
Under the architecture of Hadoop, Map Reduce programming pattern is a distributed parallel computing model on processing large volume data. It applies to the parallel computation of large scale data. ...
doi:10.14257/ijgdc.2015.8.5.04
fatcat:q4mcwengfzbobh63bkuk3am3ca
A Review on Need of MapReduce in Big Data Application
2015
International Journal of Science and Research (IJSR)
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The growing power of Big Data assume the significance of analyzing huge amount of data with a frequent and quick rate of growth and change in databases and data warehouses. ...
The main fact of data analytics is scalability, due to the huge volume of data that need to be extracted, processed, and analyzed in a sensible fashion. ...
Hadoop consist of 1) Hadoop Distributed File System (HDFS) and 2) Hadoop MapReduce: a software framework [4]. ...
doi:10.21275/v4i12.nov152248
fatcat:y7qhomvdqnhw3hkli2iwfryt6i
Special issue on Data-driven Science
2021
Distributed and parallel databases
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The issue advances the state of statistical and scientific database management by providing data-driven guidance for knowledge discovery and analytics. ...
This special issue on data-driven science explores the issues of data volume, data variety, and data velocity through a single lens. ...
doi:10.1007/s10619-021-07332-3
fatcat:bkicg7cfunfpbjcsa53a5ig3ji
The Design of an ODMG Compatible Parallel Object Database Server
[chapter]
1999
Lecture Notes in Computer Science
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Therefore we present an overview of the design of parallel relational database servers and investigate how their design choices could be adopted for a parallel object database server. ...
We believe that it is important to build on experience gained in the design and usage of parallel relational database systems over the last ten years, as much is also relevant to parallel object database ...
We would like to thank Francisco Pereira and Jim Smith (Newcastle), and Norman Paton (Manchester) for discussions which have contributed to the contents of this paper. ...
doi:10.1007/10703040_45
fatcat:qamywn7wdvbd5dwff4wopqauu4
Mining of Association Rules on Large Database Using Distributed and Parallel Computing
2016
Procedia Computer Science
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Hence hybrid architecture is proposed which consists of integrated distributed and parallel computing concept. ...
Later drawback of the Apriori algorithm is overcome by many algorithms / parallel algorithms (model) but those are also inefficient to find frequent item sets from large database with less time and with ...
In such scenarios the task can be achieved in less time by using Distributed and Parallel Computing approaches. Fig. 2 shows Methodology used in proposed system and its key concerns. ...
doi:10.1016/j.procs.2016.03.029
fatcat:fo3ayddv45flrlqr7o3pg4guei
Power of Big Data System for Storing and Processing Huge Data
2019
International Journal of Scientific Research in Science and Technology
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This challenging task of storing and managing huge volume of data is achieved in Big Data Systems. ...
Nowadays the volume of data used by the people throughout the world is increasing enormously and exponentially. ...
It has the scalability and
programming flexibility of distributed MapReduce-
like platforms with query optimization capabilities as
in parallel databases. ...
doi:10.32628/ijsrst196422
fatcat:golivpxwpfb5licqfnpstrz67q
Review of Apriori Based Algorithms on MapReduce Framework
[article]
2017
arXiv
pre-print
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The problems with most of the distributed framework are overheads of managing distributed system and lack of high level parallel programming language. ...
Now days many algorithms have been proposed on parallel and distributed platforms to enhance the performance of Apriori algorithm. ...
CD and DD algorithms are categorized under data parallelism and task parallelism while candidate distribution algorithm is hybrid of data parallelism and task parallelism [38] . ...
arXiv:1702.06284v1
fatcat:khpoq35xcfhzfc4v7mm362bbyq
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