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You searched for subject:(MapReduce). Showing records 1 – 30 of 238 total matches.

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1. De Ruiter, T.A. A workload model for MapReduce:.

Degree: 2012, Delft University of Technology

MapReduce is a parallel programming model used by Cloud service providers for data mining. To be able to enhance existing and to develop new MapReduce(more)

Subjects/Keywords: MapReduce

…viii Contents 1 Introduction 1.1 MapReduce . . . . . . . . . . . . . 1.2 Real-World… …MapReduce Workloads 1.3 Goals . . . . . . . . . . . . . . . . 1.3.1 Research Questions… …1 1 3 3 4 4 4 5 6 2 State of the Art 2.1 MapReduce Studies… …2.1.1 MapReduce Performance Evaluation . 2.1.2 MapReduce Workload Models . . . . 2.1.3… …MapReduce Workload Generation . . 2.1.4 MapReduce Simulators . . . . . . . . 2.1.5 MapReduce… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

De Ruiter, T. A. (2012). A workload model for MapReduce:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1647e1cb-84fd-46ca-b1e1-21aaf38ef30b

Chicago Manual of Style (16th Edition):

De Ruiter, T A. “A workload model for MapReduce:.” 2012. Masters Thesis, Delft University of Technology. Accessed August 20, 2019. http://resolver.tudelft.nl/uuid:1647e1cb-84fd-46ca-b1e1-21aaf38ef30b.

MLA Handbook (7th Edition):

De Ruiter, T A. “A workload model for MapReduce:.” 2012. Web. 20 Aug 2019.

Vancouver:

De Ruiter TA. A workload model for MapReduce:. [Internet] [Masters thesis]. Delft University of Technology; 2012. [cited 2019 Aug 20]. Available from: http://resolver.tudelft.nl/uuid:1647e1cb-84fd-46ca-b1e1-21aaf38ef30b.

Council of Science Editors:

De Ruiter TA. A workload model for MapReduce:. [Masters Thesis]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:1647e1cb-84fd-46ca-b1e1-21aaf38ef30b


University of Illinois – Urbana-Champaign

2. Cai, Xiao. Phurti: application and network-aware flow scheduling for MapReduce.

Degree: MS, Computer Science, 2015, University of Illinois – Urbana-Champaign

 Traffic for a typical MapReduce job in a datacenter consists of multiple network flows. Traditionally, network resources have been allocated to optimize network-level metrics such… (more)

Subjects/Keywords: Network; MapReduce

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APA (6th Edition):

Cai, X. (2015). Phurti: application and network-aware flow scheduling for MapReduce. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78595

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cai, Xiao. “Phurti: application and network-aware flow scheduling for MapReduce.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed August 20, 2019. http://hdl.handle.net/2142/78595.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cai, Xiao. “Phurti: application and network-aware flow scheduling for MapReduce.” 2015. Web. 20 Aug 2019.

Vancouver:

Cai X. Phurti: application and network-aware flow scheduling for MapReduce. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/2142/78595.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cai X. Phurti: application and network-aware flow scheduling for MapReduce. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78595

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rice University

3. Zhang, Yunming. Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters.

Degree: MS, Engineering, 2014, Rice University

 This research proposes a novel runtime system, Habanero Hadoop, to tackle the inefficient utilization of multi-core machines' memory in the existing Hadoop MapReduce runtime system.… (more)

Subjects/Keywords: MapReduce; Memory

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APA (6th Edition):

Zhang, Y. (2014). Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/87782

Chicago Manual of Style (16th Edition):

Zhang, Yunming. “Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters.” 2014. Masters Thesis, Rice University. Accessed August 20, 2019. http://hdl.handle.net/1911/87782.

MLA Handbook (7th Edition):

Zhang, Yunming. “Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters.” 2014. Web. 20 Aug 2019.

Vancouver:

Zhang Y. Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters. [Internet] [Masters thesis]. Rice University; 2014. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/1911/87782.

Council of Science Editors:

Zhang Y. Optimized Runtime Systems for MapReduce Applications in Multi-core Clusters. [Masters Thesis]. Rice University; 2014. Available from: http://hdl.handle.net/1911/87782


Brunel University

4. Hammoud, Suhel. MapReduce network enabled algorithms for classification based on association rules.

Degree: PhD, 2011, Brunel University

 There is growing evidence that integrating classification and association rule mining can produce more efficient and accurate classifiers than traditional techniques. This thesis introduces a… (more)

Subjects/Keywords: 005.3; MapReduce simulator; MapReduce association rule miner; MapReduce associative rules classifier; MPApriori

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APA (6th Edition):

Hammoud, S. (2011). MapReduce network enabled algorithms for classification based on association rules. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/5833 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539925

Chicago Manual of Style (16th Edition):

Hammoud, Suhel. “MapReduce network enabled algorithms for classification based on association rules.” 2011. Doctoral Dissertation, Brunel University. Accessed August 20, 2019. http://bura.brunel.ac.uk/handle/2438/5833 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539925.

MLA Handbook (7th Edition):

Hammoud, Suhel. “MapReduce network enabled algorithms for classification based on association rules.” 2011. Web. 20 Aug 2019.

Vancouver:

Hammoud S. MapReduce network enabled algorithms for classification based on association rules. [Internet] [Doctoral dissertation]. Brunel University; 2011. [cited 2019 Aug 20]. Available from: http://bura.brunel.ac.uk/handle/2438/5833 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539925.

Council of Science Editors:

Hammoud S. MapReduce network enabled algorithms for classification based on association rules. [Doctoral Dissertation]. Brunel University; 2011. Available from: http://bura.brunel.ac.uk/handle/2438/5833 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539925


Brunel University

5. Liu, Yang. A resource aware distributed LSI algorithm for scalable information retrieval.

Degree: PhD, 2011, Brunel University

 Latent Semantic Indexing (LSI) is one of the popular techniques in the information retrieval fields. Different from the traditional information retrieval techniques, LSI is not… (more)

Subjects/Keywords: 005.3; Mapreduce; Simulation; Load balancing

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APA (6th Edition):

Liu, Y. (2011). A resource aware distributed LSI algorithm for scalable information retrieval. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/5559 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537015

Chicago Manual of Style (16th Edition):

Liu, Yang. “A resource aware distributed LSI algorithm for scalable information retrieval.” 2011. Doctoral Dissertation, Brunel University. Accessed August 20, 2019. http://bura.brunel.ac.uk/handle/2438/5559 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537015.

MLA Handbook (7th Edition):

Liu, Yang. “A resource aware distributed LSI algorithm for scalable information retrieval.” 2011. Web. 20 Aug 2019.

Vancouver:

Liu Y. A resource aware distributed LSI algorithm for scalable information retrieval. [Internet] [Doctoral dissertation]. Brunel University; 2011. [cited 2019 Aug 20]. Available from: http://bura.brunel.ac.uk/handle/2438/5559 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537015.

Council of Science Editors:

Liu Y. A resource aware distributed LSI algorithm for scalable information retrieval. [Doctoral Dissertation]. Brunel University; 2011. Available from: http://bura.brunel.ac.uk/handle/2438/5559 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.537015


NSYSU

6. Huang, Jun-neng. Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results.

Degree: Master, Computer Science and Engineering, 2011, NSYSU

 This thesis describes a method of reducing communication overheads within the MapReduce infrastructure of a cloud computing environment. MapReduce is an framework for parallelizing the… (more)

Subjects/Keywords: cloud computing; MapReduce; Hadoop

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Huang, J. (2011). Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0822111-220155

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Huang, Jun-neng. “Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results.” 2011. Thesis, NSYSU. Accessed August 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0822111-220155.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Huang, Jun-neng. “Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results.” 2011. Web. 20 Aug 2019.

Vancouver:

Huang J. Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 Aug 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0822111-220155.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huang J. Reducing Communication Overhead and Computation Costs in a Cloud Network by Early Combination of Partial Results. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0822111-220155

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


California State University – San Bernardino

7. Sherikar, Vishnu Vardhan Reddy. I2MAPREDUCE: DATA MINING FOR BIG DATA.

Degree: MSin Computer Science, School of Computer Science and Engineering, 2017, California State University – San Bernardino

  This project is an extension of i2MapReduce: Incremental MapReduce for Mining Evolving Big Data . i2MapReduce is used for incremental big data processing, which… (more)

Subjects/Keywords: Mapreduce; Other Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sherikar, V. V. R. (2017). I2MAPREDUCE: DATA MINING FOR BIG DATA. (Thesis). California State University – San Bernardino. Retrieved from http://scholarworks.lib.csusb.edu/etd/437

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sherikar, Vishnu Vardhan Reddy. “I2MAPREDUCE: DATA MINING FOR BIG DATA.” 2017. Thesis, California State University – San Bernardino. Accessed August 20, 2019. http://scholarworks.lib.csusb.edu/etd/437.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sherikar, Vishnu Vardhan Reddy. “I2MAPREDUCE: DATA MINING FOR BIG DATA.” 2017. Web. 20 Aug 2019.

Vancouver:

Sherikar VVR. I2MAPREDUCE: DATA MINING FOR BIG DATA. [Internet] [Thesis]. California State University – San Bernardino; 2017. [cited 2019 Aug 20]. Available from: http://scholarworks.lib.csusb.edu/etd/437.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sherikar VVR. I2MAPREDUCE: DATA MINING FOR BIG DATA. [Thesis]. California State University – San Bernardino; 2017. Available from: http://scholarworks.lib.csusb.edu/etd/437

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Debrecen

8. Auer, Bence. Biológiai géninterakciók feldolgozása Apache Hadoop segítségével .

Degree: DE – Informatikai Kar, University of Debrecen

 A funkcionális genomika az egyes gének biológiai folyamatokban betöltött szerepét vizsgálja. Az ezen a területen végzett kutatások elengedhetetlen feltétele a kísérletek alapos megtervezése, azonban az… (more)

Subjects/Keywords: hadoop; mapreduce

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APA (6th Edition):

Auer, B. (n.d.). Biológiai géninterakciók feldolgozása Apache Hadoop segítségével . (Thesis). University of Debrecen. Retrieved from http://hdl.handle.net/2437/201799

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Auer, Bence. “Biológiai géninterakciók feldolgozása Apache Hadoop segítségével .” Thesis, University of Debrecen. Accessed August 20, 2019. http://hdl.handle.net/2437/201799.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Auer, Bence. “Biológiai géninterakciók feldolgozása Apache Hadoop segítségével .” Web. 20 Aug 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Auer B. Biológiai géninterakciók feldolgozása Apache Hadoop segítségével . [Internet] [Thesis]. University of Debrecen; [cited 2019 Aug 20]. Available from: http://hdl.handle.net/2437/201799.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Auer B. Biológiai géninterakciók feldolgozása Apache Hadoop segítségével . [Thesis]. University of Debrecen; Available from: http://hdl.handle.net/2437/201799

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


University of Waterloo

9. Khoshdel Nikkhoo, Hani. The Impact of Near-Duplicate Documents on Information Retrieval Evaluation.

Degree: 2011, University of Waterloo

 Near-duplicate documents can adversely affect the efficiency and effectiveness of search engines. Due to the pairwise nature of the comparisons required for near-duplicate detection, this… (more)

Subjects/Keywords: near-duplicate detection; MapReduce; shingles

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APA (6th Edition):

Khoshdel Nikkhoo, H. (2011). The Impact of Near-Duplicate Documents on Information Retrieval Evaluation. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/5750

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Khoshdel Nikkhoo, Hani. “The Impact of Near-Duplicate Documents on Information Retrieval Evaluation.” 2011. Thesis, University of Waterloo. Accessed August 20, 2019. http://hdl.handle.net/10012/5750.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Khoshdel Nikkhoo, Hani. “The Impact of Near-Duplicate Documents on Information Retrieval Evaluation.” 2011. Web. 20 Aug 2019.

Vancouver:

Khoshdel Nikkhoo H. The Impact of Near-Duplicate Documents on Information Retrieval Evaluation. [Internet] [Thesis]. University of Waterloo; 2011. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/10012/5750.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Khoshdel Nikkhoo H. The Impact of Near-Duplicate Documents on Information Retrieval Evaluation. [Thesis]. University of Waterloo; 2011. Available from: http://hdl.handle.net/10012/5750

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

10. Su, Du. GreenMap: MapReduce with ultra-high-efficiency power delivery.

Degree: MS, Electrical & Computer Engr, 2017, University of Illinois – Urbana-Champaign

 With the continuous growth of online services, energy consumption has become a significant fraction of the total cost of ownership of large data centers. Though… (more)

Subjects/Keywords: Green computing; MapReduce; Load Balance

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APA (6th Edition):

Su, D. (2017). GreenMap: MapReduce with ultra-high-efficiency power delivery. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/100882

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Su, Du. “GreenMap: MapReduce with ultra-high-efficiency power delivery.” 2017. Thesis, University of Illinois – Urbana-Champaign. Accessed August 20, 2019. http://hdl.handle.net/2142/100882.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Su, Du. “GreenMap: MapReduce with ultra-high-efficiency power delivery.” 2017. Web. 20 Aug 2019.

Vancouver:

Su D. GreenMap: MapReduce with ultra-high-efficiency power delivery. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2017. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/2142/100882.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Su D. GreenMap: MapReduce with ultra-high-efficiency power delivery. [Thesis]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/100882

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

11. Morán Barbón, Jesús. Functional testing techniques for new massive data processing paradigms .

Degree: 2019, Universidad de Oviedo

 Los programas Big Data son aquellos que analizan información utilizando nuevos modelos de procesamiento que superan las limitaciones de la tecnología tradicional en cuanto al… (more)

Subjects/Keywords: Big Data; MapReduce; Defectos funcionales

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APA (6th Edition):

Morán Barbón, J. (2019). Functional testing techniques for new massive data processing paradigms . (Doctoral Dissertation). Universidad de Oviedo. Retrieved from http://hdl.handle.net/10651/51702

Chicago Manual of Style (16th Edition):

Morán Barbón, Jesús. “Functional testing techniques for new massive data processing paradigms .” 2019. Doctoral Dissertation, Universidad de Oviedo. Accessed August 20, 2019. http://hdl.handle.net/10651/51702.

MLA Handbook (7th Edition):

Morán Barbón, Jesús. “Functional testing techniques for new massive data processing paradigms .” 2019. Web. 20 Aug 2019.

Vancouver:

Morán Barbón J. Functional testing techniques for new massive data processing paradigms . [Internet] [Doctoral dissertation]. Universidad de Oviedo; 2019. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/10651/51702.

Council of Science Editors:

Morán Barbón J. Functional testing techniques for new massive data processing paradigms . [Doctoral Dissertation]. Universidad de Oviedo; 2019. Available from: http://hdl.handle.net/10651/51702


New Jersey Institute of Technology

12. Du, Zongxuan. Data analytics with mapreduce in apache spark and hadoop systems.

Degree: MSin Computer Science - (M.S.), Computer Science, 2016, New Jersey Institute of Technology

MapReduce comes from a traditional problem solving method: separating a big problem and solving each small parts. With the target of computing larger dataset… (more)

Subjects/Keywords: Data analytics; Mapreduce; Computer Sciences

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APA (6th Edition):

Du, Z. (2016). Data analytics with mapreduce in apache spark and hadoop systems. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Du, Zongxuan. “Data analytics with mapreduce in apache spark and hadoop systems.” 2016. Thesis, New Jersey Institute of Technology. Accessed August 20, 2019. https://digitalcommons.njit.edu/theses/269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Du, Zongxuan. “Data analytics with mapreduce in apache spark and hadoop systems.” 2016. Web. 20 Aug 2019.

Vancouver:

Du Z. Data analytics with mapreduce in apache spark and hadoop systems. [Internet] [Thesis]. New Jersey Institute of Technology; 2016. [cited 2019 Aug 20]. Available from: https://digitalcommons.njit.edu/theses/269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Du Z. Data analytics with mapreduce in apache spark and hadoop systems. [Thesis]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/theses/269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

13. Gault, Sylvain. Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul.

Degree: Docteur es, Informatique, 2015, Lyon, École normale supérieure

Beaucoup de disciplines scientifiques s'appuient désormais sur l'analyse et la fouille de masses gigantesques de données pour produire de nouveaux résultats. Ces données brutes sont… (more)

Subjects/Keywords: MapReduce; BigData; Ordonnancement; Optimisation; MapReduce; BigData; Scheduling; Optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gault, S. (2015). Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul. (Doctoral Dissertation). Lyon, École normale supérieure. Retrieved from http://www.theses.fr/2015ENSL0985

Chicago Manual of Style (16th Edition):

Gault, Sylvain. “Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul.” 2015. Doctoral Dissertation, Lyon, École normale supérieure. Accessed August 20, 2019. http://www.theses.fr/2015ENSL0985.

MLA Handbook (7th Edition):

Gault, Sylvain. “Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul.” 2015. Web. 20 Aug 2019.

Vancouver:

Gault S. Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul. [Internet] [Doctoral dissertation]. Lyon, École normale supérieure; 2015. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2015ENSL0985.

Council of Science Editors:

Gault S. Improving MapReduce Performance on Clusters : Amélioration des performances de MapReduce sur grappe de calcul. [Doctoral Dissertation]. Lyon, École normale supérieure; 2015. Available from: http://www.theses.fr/2015ENSL0985


Brno University of Technology

14. Čecho, Jaroslav. Optimalizace platformy pro distribuované výpočty Hadoop .

Degree: 2012, Brno University of Technology

 Tato diplomová práce se zabývá možnostmi optimalizace frameworku Hadoop za pomocí platformy CUDA. Apache Hadoop je frameworku umožnující analýzu obrovských objemů dat. Obsahuje distribuovaný souborový… (more)

Subjects/Keywords: Hadoop; CUDA; mapreduce; optimalizace; Hadoop; CUDA; mapreduce; optimalization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Čecho, J. (2012). Optimalizace platformy pro distribuované výpočty Hadoop . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53607

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Čecho, Jaroslav. “Optimalizace platformy pro distribuované výpočty Hadoop .” 2012. Thesis, Brno University of Technology. Accessed August 20, 2019. http://hdl.handle.net/11012/53607.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Čecho, Jaroslav. “Optimalizace platformy pro distribuované výpočty Hadoop .” 2012. Web. 20 Aug 2019.

Vancouver:

Čecho J. Optimalizace platformy pro distribuované výpočty Hadoop . [Internet] [Thesis]. Brno University of Technology; 2012. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/11012/53607.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Čecho J. Optimalizace platformy pro distribuované výpočty Hadoop . [Thesis]. Brno University of Technology; 2012. Available from: http://hdl.handle.net/11012/53607

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Louisiana State University

15. Bai, Shuju. A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications.

Degree: PhD, Computer Sciences, 2013, Louisiana State University

 Developing platforms for large scale data processing has been a great interest to scientists. Hadoop is a widely used computational platform which is a fault-tolerant… (more)

Subjects/Keywords: Molecular dynamics; Hadoop; MPI; MapReduce; Framework

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bai, S. (2013). A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-07012013-211426 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2662

Chicago Manual of Style (16th Edition):

Bai, Shuju. “A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications.” 2013. Doctoral Dissertation, Louisiana State University. Accessed August 20, 2019. etd-07012013-211426 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2662.

MLA Handbook (7th Edition):

Bai, Shuju. “A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications.” 2013. Web. 20 Aug 2019.

Vancouver:

Bai S. A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2019 Aug 20]. Available from: etd-07012013-211426 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2662.

Council of Science Editors:

Bai S. A hybrid framework of iterative MapReduce and MPI for molecular dynamics applications. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-07012013-211426 ; https://digitalcommons.lsu.edu/gradschool_dissertations/2662


University of Sydney

16. Lu, Peng. Application profiling and resource management for MapReduce .

Degree: 2015, University of Sydney

 Scale of data generated and processed is exponential growth in the Big Data ear. It poses a challenge that is far beyond the goal of… (more)

Subjects/Keywords: Resource management; MapReduce; scheduling; slot layering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lu, P. (2015). Application profiling and resource management for MapReduce . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/13969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lu, Peng. “Application profiling and resource management for MapReduce .” 2015. Thesis, University of Sydney. Accessed August 20, 2019. http://hdl.handle.net/2123/13969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lu, Peng. “Application profiling and resource management for MapReduce .” 2015. Web. 20 Aug 2019.

Vancouver:

Lu P. Application profiling and resource management for MapReduce . [Internet] [Thesis]. University of Sydney; 2015. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/2123/13969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lu P. Application profiling and resource management for MapReduce . [Thesis]. University of Sydney; 2015. Available from: http://hdl.handle.net/2123/13969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Virginia Tech

17. Wang, Guanying. Evaluating MapReduce System Performance: A Simulation Approach.

Degree: PhD, Computer Science, 2012, Virginia Tech

 Scale of data generated and processed is exploding in the Big Data era. The MapReduce system popularized by open-source Hadoop is a powerful tool for… (more)

Subjects/Keywords: performance prediction; performance modeling; simulation; MapReduce; Hadoop

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, G. (2012). Evaluating MapReduce System Performance: A Simulation Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28820

Chicago Manual of Style (16th Edition):

Wang, Guanying. “Evaluating MapReduce System Performance: A Simulation Approach.” 2012. Doctoral Dissertation, Virginia Tech. Accessed August 20, 2019. http://hdl.handle.net/10919/28820.

MLA Handbook (7th Edition):

Wang, Guanying. “Evaluating MapReduce System Performance: A Simulation Approach.” 2012. Web. 20 Aug 2019.

Vancouver:

Wang G. Evaluating MapReduce System Performance: A Simulation Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/10919/28820.

Council of Science Editors:

Wang G. Evaluating MapReduce System Performance: A Simulation Approach. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28820

18. Hartog, Jessica L. Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration.

Degree: PhD, Computer Science, 2018, Binghamton University

  This dissertation presents the techniques for adaptation of MapReduce frameworks to incorporate heterogeneity-aware scheduling algorithms, an inspection of cluster configurations and how they impact… (more)

Subjects/Keywords: Applied sciences; Heterogeneity; MapReduce; Platform; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hartog, J. L. (2018). Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration. (Doctoral Dissertation). Binghamton University. Retrieved from https://orb.binghamton.edu/dissertation_and_theses/32

Chicago Manual of Style (16th Edition):

Hartog, Jessica L. “Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration.” 2018. Doctoral Dissertation, Binghamton University. Accessed August 20, 2019. https://orb.binghamton.edu/dissertation_and_theses/32.

MLA Handbook (7th Edition):

Hartog, Jessica L. “Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration.” 2018. Web. 20 Aug 2019.

Vancouver:

Hartog JL. Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration. [Internet] [Doctoral dissertation]. Binghamton University; 2018. [cited 2019 Aug 20]. Available from: https://orb.binghamton.edu/dissertation_and_theses/32.

Council of Science Editors:

Hartog JL. Mapreduce and Heterogeneity: Power-Aware Bag-of-Tasks, Framework Parameter Sensitivity, and Dynamic Cluster Aware Framework Configuration. [Doctoral Dissertation]. Binghamton University; 2018. Available from: https://orb.binghamton.edu/dissertation_and_theses/32


Florida International University

19. Cary, Ariel. Scaling Geospatial Searches in Large Spatial Databases.

Degree: PhD, Computer Science, 2011, Florida International University

  Modern geographical databases store a rich set of aspatial attributes in addition to geographic data. Retrieving spatial records constrained on spatial and aspatial attributes… (more)

Subjects/Keywords: Spatial databases; searches; MapReduce; scalability; indexing.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Cary, A. (2011). Scaling Geospatial Searches in Large Spatial Databases. (Doctoral Dissertation). Florida International University. Retrieved from http://digitalcommons.fiu.edu/etd/548 ; 10.25148/etd.FI11120810 ; FI11120810

Chicago Manual of Style (16th Edition):

Cary, Ariel. “Scaling Geospatial Searches in Large Spatial Databases.” 2011. Doctoral Dissertation, Florida International University. Accessed August 20, 2019. http://digitalcommons.fiu.edu/etd/548 ; 10.25148/etd.FI11120810 ; FI11120810.

MLA Handbook (7th Edition):

Cary, Ariel. “Scaling Geospatial Searches in Large Spatial Databases.” 2011. Web. 20 Aug 2019.

Vancouver:

Cary A. Scaling Geospatial Searches in Large Spatial Databases. [Internet] [Doctoral dissertation]. Florida International University; 2011. [cited 2019 Aug 20]. Available from: http://digitalcommons.fiu.edu/etd/548 ; 10.25148/etd.FI11120810 ; FI11120810.

Council of Science Editors:

Cary A. Scaling Geospatial Searches in Large Spatial Databases. [Doctoral Dissertation]. Florida International University; 2011. Available from: http://digitalcommons.fiu.edu/etd/548 ; 10.25148/etd.FI11120810 ; FI11120810


Texas A&M University

20. Ahmed, Sarker Tanzir. Analysis, Modeling, and Algorithms for Scalable Web Crawling.

Degree: PhD, Computer Science, 2016, Texas A&M University

 This dissertation presents a modeling framework for the intermediate data generated by external-memory sorting algorithms (e.g., merge sort, bucket sort, hash sort, replacement selection) that… (more)

Subjects/Keywords: MapReduce; BigData; Web crawling; External Sorting

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ahmed, S. T. (2016). Analysis, Modeling, and Algorithms for Scalable Web Crawling. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157811

Chicago Manual of Style (16th Edition):

Ahmed, Sarker Tanzir. “Analysis, Modeling, and Algorithms for Scalable Web Crawling.” 2016. Doctoral Dissertation, Texas A&M University. Accessed August 20, 2019. http://hdl.handle.net/1969.1/157811.

MLA Handbook (7th Edition):

Ahmed, Sarker Tanzir. “Analysis, Modeling, and Algorithms for Scalable Web Crawling.” 2016. Web. 20 Aug 2019.

Vancouver:

Ahmed ST. Analysis, Modeling, and Algorithms for Scalable Web Crawling. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/1969.1/157811.

Council of Science Editors:

Ahmed ST. Analysis, Modeling, and Algorithms for Scalable Web Crawling. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157811


University of Minnesota

21. Eldawy, Ahmed. SpatialHadoop: A MapReduce Framework for Big Spatial Data.

Degree: PhD, Computer Science, 2016, University of Minnesota

 There has been a recent explosion in the amounts of spatial data produced by several devices such as smart phones, satellites, space telescopes, medical devices,… (more)

Subjects/Keywords: Big Data; Hadoop; MapReduce; Spatial; SpatialHadoop

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Eldawy, A. (2016). SpatialHadoop: A MapReduce Framework for Big Spatial Data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182261

Chicago Manual of Style (16th Edition):

Eldawy, Ahmed. “SpatialHadoop: A MapReduce Framework for Big Spatial Data.” 2016. Doctoral Dissertation, University of Minnesota. Accessed August 20, 2019. http://hdl.handle.net/11299/182261.

MLA Handbook (7th Edition):

Eldawy, Ahmed. “SpatialHadoop: A MapReduce Framework for Big Spatial Data.” 2016. Web. 20 Aug 2019.

Vancouver:

Eldawy A. SpatialHadoop: A MapReduce Framework for Big Spatial Data. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/11299/182261.

Council of Science Editors:

Eldawy A. SpatialHadoop: A MapReduce Framework for Big Spatial Data. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/182261


University of Bridgeport

22. Alshammari, Hamoud H. Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow .

Degree: 2016, University of Bridgeport

 Cloud Computing provides different services to the users with regard to processing data. One of the main concepts in Cloud Computing is BigData and BigData… (more)

Subjects/Keywords: Big data; Cloud computing; Hadoop; MapReduce

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Alshammari, H. H. (2016). Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow . (Thesis). University of Bridgeport. Retrieved from https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Alshammari, Hamoud H. “Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow .” 2016. Thesis, University of Bridgeport. Accessed August 20, 2019. https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Alshammari, Hamoud H. “Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow .” 2016. Web. 20 Aug 2019.

Vancouver:

Alshammari HH. Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow . [Internet] [Thesis]. University of Bridgeport; 2016. [cited 2019 Aug 20]. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alshammari HH. Improving Hadoop Performance by Using Metadata of Related Jobs in Text Datasets Via Enhancing MapReduce Workflow . [Thesis]. University of Bridgeport; 2016. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

23. Gottimukkula, Srikanth. Big Data Analysis By using Hadoop MapReduce and Apache Hive.

Degree: 2017, Ferris State University

 Big data analytics is the process of analysis the extremely large sets of data. Analyzing the big data is a challenging task to the data… (more)

Subjects/Keywords: Data analysis.; Computer software.; Hadoop.; MapReduce.; Hive.

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APA (6th Edition):

Gottimukkula, S. (2017). Big Data Analysis By using Hadoop MapReduce and Apache Hive. (Thesis). Ferris State University. Retrieved from http://hdl.handle.net/2323/6385

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gottimukkula, Srikanth. “Big Data Analysis By using Hadoop MapReduce and Apache Hive.” 2017. Thesis, Ferris State University. Accessed August 20, 2019. http://hdl.handle.net/2323/6385.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gottimukkula, Srikanth. “Big Data Analysis By using Hadoop MapReduce and Apache Hive.” 2017. Web. 20 Aug 2019.

Vancouver:

Gottimukkula S. Big Data Analysis By using Hadoop MapReduce and Apache Hive. [Internet] [Thesis]. Ferris State University; 2017. [cited 2019 Aug 20]. Available from: http://hdl.handle.net/2323/6385.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gottimukkula S. Big Data Analysis By using Hadoop MapReduce and Apache Hive. [Thesis]. Ferris State University; 2017. Available from: http://hdl.handle.net/2323/6385

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

24. Fabiano da Guia Rocha. Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação.

Degree: 2013, Universidade Federal de São Carlos

Durante os últimos anos, houve um significativo crescimento na quantidade de dados processados diariamente por companhias, universidades e outras instituições. Mapreduce é um modelo de… (more)

Subjects/Keywords: Multiprocessor systems; Scalability; Computação; Sistemas multiprocessados; Escalabilidade; Modelo mapReduce; MapReduce; CIENCIA DA COMPUTACAO

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rocha, F. d. G. (2013). Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação. (Thesis). Universidade Federal de São Carlos. Retrieved from http://www.bdtd.ufscar.br/htdocs/tedeSimplificado//tde_busca/arquivo.php?codArquivo=6567

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rocha, Fabiano da Guia. “Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação.” 2013. Thesis, Universidade Federal de São Carlos. Accessed August 20, 2019. http://www.bdtd.ufscar.br/htdocs/tedeSimplificado//tde_busca/arquivo.php?codArquivo=6567.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rocha, Fabiano da Guia. “Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação.” 2013. Web. 20 Aug 2019.

Vancouver:

Rocha FdG. Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação. [Internet] [Thesis]. Universidade Federal de São Carlos; 2013. [cited 2019 Aug 20]. Available from: http://www.bdtd.ufscar.br/htdocs/tedeSimplificado//tde_busca/arquivo.php?codArquivo=6567.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rocha FdG. Análise de escalabilidade de aplicações Hadoop/Mapreduce por meio de simulação. [Thesis]. Universidade Federal de São Carlos; 2013. Available from: http://www.bdtd.ufscar.br/htdocs/tedeSimplificado//tde_busca/arquivo.php?codArquivo=6567

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

25. Pan, Jie. Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures.

Degree: Docteur es, Mathématiques appliquées, 2010, Châtenay-Malabry, Ecole centrale de Paris

 Des quantités de données colossalles sont générées quotidiennement. Traiter de grands volumes de données devient alors un véritable challenge pour les logiciels d'analyse des données… (more)

Subjects/Keywords: MapReduce; Analyse de données multidimentionnelles; Optimisation de performance; MapReduce; Multidimensional data analysis; Performance optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pan, J. (2010). Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures. (Doctoral Dissertation). Châtenay-Malabry, Ecole centrale de Paris. Retrieved from http://www.theses.fr/2010ECAP0040

Chicago Manual of Style (16th Edition):

Pan, Jie. “Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures.” 2010. Doctoral Dissertation, Châtenay-Malabry, Ecole centrale de Paris. Accessed August 20, 2019. http://www.theses.fr/2010ECAP0040.

MLA Handbook (7th Edition):

Pan, Jie. “Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures.” 2010. Web. 20 Aug 2019.

Vancouver:

Pan J. Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures. [Internet] [Doctoral dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2010. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2010ECAP0040.

Council of Science Editors:

Pan J. Modélisation et exécution des applications d'analyse de données multi-dimentionnelles sur architectures distribuées. : Modelling and executing multidimensional data analysis applications over distributed architectures. [Doctoral Dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2010. Available from: http://www.theses.fr/2010ECAP0040

26. Lambert, Thomas. On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs.

Degree: Docteur es, Informatique, 2017, Bordeaux

 Avec l’émergence du calcul haute-performance (HPC) et des applications Big Data, de nouvelles problématiques cruciales sont apparues. Parmi elles on trouve le problème du transfert… (more)

Subjects/Keywords: Algorithmique; MapReduce; Produit de matrices; Calcul Parallèle; Ordonnancement; Algorithmic; MapReduce; Matrix Product; Parallel Computing; Scheduling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lambert, T. (2017). On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs. (Doctoral Dissertation). Bordeaux. Retrieved from http://www.theses.fr/2017BORD0656

Chicago Manual of Style (16th Edition):

Lambert, Thomas. “On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs.” 2017. Doctoral Dissertation, Bordeaux. Accessed August 20, 2019. http://www.theses.fr/2017BORD0656.

MLA Handbook (7th Edition):

Lambert, Thomas. “On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs.” 2017. Web. 20 Aug 2019.

Vancouver:

Lambert T. On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs. [Internet] [Doctoral dissertation]. Bordeaux; 2017. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2017BORD0656.

Council of Science Editors:

Lambert T. On the Effect of Replication of Input Files on the Efficiency and the Robustness of a Set of Computations : Étude de l’effet de la réplication de fichiers d’entrée sur l’efficacité et la robustesse d’un ensemble de calculs. [Doctoral Dissertation]. Bordeaux; 2017. Available from: http://www.theses.fr/2017BORD0656

27. Berekmeri, Mihaly. La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability.

Degree: Docteur es, Automatique et productique, 2015, Grenoble Alpes

Le grand volume de données généré par nos téléphones mobiles, tablettes, ordinateurs, ainsi que nos montres connectées présente un défi pour le stockage et l'analyse.… (more)

Subjects/Keywords: Modélisation; Contrôle; Cloud; MapReduce; Performance; Fiabilité; Modeling; Control; MapReduce; Performance; Dependability; Feedback; Feedfoward; Optimal; 620

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Berekmeri, M. (2015). La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability. (Doctoral Dissertation). Grenoble Alpes. Retrieved from http://www.theses.fr/2015GREAT126

Chicago Manual of Style (16th Edition):

Berekmeri, Mihaly. “La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability.” 2015. Doctoral Dissertation, Grenoble Alpes. Accessed August 20, 2019. http://www.theses.fr/2015GREAT126.

MLA Handbook (7th Edition):

Berekmeri, Mihaly. “La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability.” 2015. Web. 20 Aug 2019.

Vancouver:

Berekmeri M. La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability. [Internet] [Doctoral dissertation]. Grenoble Alpes; 2015. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2015GREAT126.

Council of Science Editors:

Berekmeri M. La modélisation et le contrôle des services BigData : application à la performance et la fiabilité de MapReduce : Modeling and control of cloud services : application to MapReduce performance and dependability. [Doctoral Dissertation]. Grenoble Alpes; 2015. Available from: http://www.theses.fr/2015GREAT126

28. Phan, Tien-Dat. Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds.

Degree: Docteur es, Informatique, 2017, Rennes, École normale supérieure

La consommation d’énergie est une préoccupation importante pour les systèmes de traitement Big Data à grande échelle, ce qui entraîne un coût monétaire énorme. En… (more)

Subjects/Keywords: Big Data; Clouds; MapReduce; Performance; Prévention de stragglers; Big Data; Clouds; MapReduce; Performance; Straggler Mitigation

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APA (6th Edition):

Phan, T. (2017). Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds. (Doctoral Dissertation). Rennes, École normale supérieure. Retrieved from http://www.theses.fr/2017ENSR0008

Chicago Manual of Style (16th Edition):

Phan, Tien-Dat. “Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds.” 2017. Doctoral Dissertation, Rennes, École normale supérieure. Accessed August 20, 2019. http://www.theses.fr/2017ENSR0008.

MLA Handbook (7th Edition):

Phan, Tien-Dat. “Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds.” 2017. Web. 20 Aug 2019.

Vancouver:

Phan T. Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds. [Internet] [Doctoral dissertation]. Rennes, École normale supérieure; 2017. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2017ENSR0008.

Council of Science Editors:

Phan T. Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds : Amélioration de l'efficacité énergétique de la prévention des stragglers pour les applications Big Data sur les Clouds. [Doctoral Dissertation]. Rennes, École normale supérieure; 2017. Available from: http://www.theses.fr/2017ENSR0008

29. Pastorelli, Mario. Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems.

Degree: Docteur es, Informatique et réseaux, 2014, Paris, ENST

La dernière décennie a vu l’émergence de systèmes parallèles pour l’analyse de grosse quantités de données (DISC) , tels que Hadoop, et la demande qui… (more)

Subjects/Keywords: Système distribué; Planification des tâches par taille; MapReduce; Distributed system; Size-based job scheduling; MapReduce

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pastorelli, M. (2014). Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2014ENST0048

Chicago Manual of Style (16th Edition):

Pastorelli, Mario. “Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems.” 2014. Doctoral Dissertation, Paris, ENST. Accessed August 20, 2019. http://www.theses.fr/2014ENST0048.

MLA Handbook (7th Edition):

Pastorelli, Mario. “Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems.” 2014. Web. 20 Aug 2019.

Vancouver:

Pastorelli M. Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems. [Internet] [Doctoral dissertation]. Paris, ENST; 2014. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2014ENST0048.

Council of Science Editors:

Pastorelli M. Disciplines basées sur la taille pour la planification des jobs dans data-intensif scalable computing systems : Size-based disciplines for job scheduling in data-intensive scalable computing systems. [Doctoral Dissertation]. Paris, ENST; 2014. Available from: http://www.theses.fr/2014ENST0048

30. Huang, Xin. Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles.

Degree: Docteur es, Sciences de données, 2016, Sorbonne Paris Cité

Le Web sémantique est la vision de la prochaine génération de Web proposé par Tim Berners-Lee en 2001. Avec le développement rapide des technologies du… (more)

Subjects/Keywords: RDF; Requête; Raisonnement; MapReduce; Incertitude; Incohérence; RDF; Query; Reasoning; MapReduce; Uncertainty; Inconsistency; 005.7

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Huang, X. (2016). Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles. (Doctoral Dissertation). Sorbonne Paris Cité. Retrieved from http://www.theses.fr/2016USPCB124

Chicago Manual of Style (16th Edition):

Huang, Xin. “Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles.” 2016. Doctoral Dissertation, Sorbonne Paris Cité. Accessed August 20, 2019. http://www.theses.fr/2016USPCB124.

MLA Handbook (7th Edition):

Huang, Xin. “Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles.” 2016. Web. 20 Aug 2019.

Vancouver:

Huang X. Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles. [Internet] [Doctoral dissertation]. Sorbonne Paris Cité; 2016. [cited 2019 Aug 20]. Available from: http://www.theses.fr/2016USPCB124.

Council of Science Editors:

Huang X. Querying big RDF data : semantic heterogeneity and rule-based inconsistency : Interrogation de gros volumes données : hétérogénéité sémantique et incohérence à la base des règles. [Doctoral Dissertation]. Sorbonne Paris Cité; 2016. Available from: http://www.theses.fr/2016USPCB124

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