Abstract
Cloud computing has been widely introduced because of its ability to increase resource utilization. Furthermore, cloud computing offers resources as services that taken part as one of the next generation computing technologies. Before delivery application to cloud computing environment, the first step is the migration of the data. Migrating data from relational database management system (RDBMS) to Google App Engine is time-consuming problem. Hence, Google App Engine (GAE) Datastore provides NoSQL data storage with configuration file that contains table schema and CSV or XML file. This study presents the method for simplifying data migration from RDBMS to GAE including blob data migration. The proposed method leverages AppCfg to provide convenience way for data migration. As a result, user has eliminated at least 75 % task effort for data migration.
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References
Elsenpeter R, Velte AT, Velte TJ (2010) Cloud computing—a practical approach. McGraw-Hill, USA, p 23
Ingthorsson O (2012) 5 Reasons cloud computing is key to business success. http://www.datacenterknowledge.com/archives/2012/06/25/5-reasons-cloud-computing-is-key-to-businesss-success/. Retrieved 5 Nov 2012
Paul F (2012) 8 Reasons why cloud computing is even better for small businesses. http://readwrite.com/2012/04/06/8-reasons-why-cloud-computing. Retrieved 5 Nov 2012
Google (2012) What is Google App Engine? https://developers.google.com/appengine/docs/whatisgoogleappengine. Retrieved 29 Dec 2012
Severance C (2009) Using Google App Engine. O’Reilly Media, USA, p 14
Burrows M, Chandra T, Chang F, Dean J, Fikes A, Ghemawat S, Gruber RE, Hsieh WC, Wallach DA (2008) Bigtable: a distributed storage system for structured data. J ACM Trans Comput Syst 26(2), article no. 4, June 2008
Matthes F, Schulz C, Haller K (2011) Testing & quality assurance in data migration projects. In: 2011 27th IEEE international conference on software maintenance (ICSM), pp 438–447, Sept 2011
Kang S, Reddy ALN (2008) User-centric data migration in networked storage systems. In: IEEE international symposium on parallel and distributed processing, IPDPS 2008, pp 1–12, June 2008
IBM (2007) Best practices for data migration: methodologies for planning, designing, migrating and validating data migration. https://www-935.ibm.com/services/us/gts/pdf/softek-best-practices-data-migration.pdf. Retrieved 29 Jan 2013
Wikipedia (2013) Relational database. http://en.wikipedia.org/wiki/Relational_database. Retrieved 9 Jan 2012
Google (2012) Google App Engine—the platform for your next great idea
Prodan R, Sperk M, Osterman S (2012) Evaluating high-performance computing on Google App Engine. Software IEEE 29(2):52–58
Google (2012) Datastore overview. https://developers.google.com/appengine/docs/python/datastore/overview. Retrieved 15 Dec 2012
Elamparithi M (2010) Database migration tool (DMT)—accomplishments & future directions. In: 2010 International conference on communication and computational intelligence (INCOCCI), Dec 2010, pp 481–485
Walek B, Klimes C (2012) A methodology for data migration between different database management systems. Int J Comput Inf Eng 6:85–90
Walek B, Klimes C (2012) Data migration between document-oriented and relational databases. World Acad Sci, Eng Technol (69):894–898, Sept 2012
Shirazi MN, Kuan HC, Dolatabadi H () Design patterns to enable data portability between clouds’ databases. In: 2012 12th International conference on computational science and its applications (ICCSA), June 2012, pp 117–120
Lahman S (2012) Download Lahman’s baseball database. http://www.seanlahman.com/baseball-archive/statistics/. Retrieved 30 Dec 2012
Imagenet (n.d) ImageNet. http://www.image-net.org. Retrieved 1 Jan 2012
Couchbase (2012) NoSQL database technology
Google (2012) Blobstore python API overview. https://developers.google.com/appengine/docs/python/blobstore/overview. Retrieved 15 Dec 2012
Dancis K (2009) AppRocket 2.0.0. http://kaspa.rs/. Retrieved 16 Dec 2012
Acknowledgments
The authors would like to thank the National Science Council of the Republic of China, Taiwan for financially/partially supporting this research under Contract No. NSC101-2221-E-143-005-, NSC101-2221-E-259-003- and NSC101-2221-E-259-005-MY2.
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Chang, YC., Chang, RS., Chen, Y. (2014). Simplifying Data Migration from Relational Database Management System to Google App Engine Datastore. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_101
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DOI: https://doi.org/10.1007/978-94-007-7262-5_101
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