Migration of Stored Procedure to Distributed Cloud Database

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Many legacy applications rely on a single instance relational database. In the age of big data, applications with growing popularity may continue to generate large amount of data. The data would be beyond the limit of a traditional relational database. These applications can be migrated to a distributed database system for acquiring high scalability and performance. But the migration process is complicated especially for user defined stored procedure. In order to obtain the correct behavior, a stored procedure usually has to be rewritten in the application code. This rewriting is usually a time consuming and unpleasant task. This study gives a mechanism for migrating stored procedure from single instance relational database to distributed sharded database without the need of application code rewriting. In the migration solution offered by this study, Oracle stored procedure code is parsed, analyzed, and translated so as to be stored and executed globally in a sharded database.

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2115-2120

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February 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Divyakant Agrawal, Sudipto Das, and Amr El Abbadi. Big data and cloud computing: current state and future opportunities[C]. In Proceedings of the 14th International Conference on Extending Database Technology (EDBT/ICDT '11). (2011).

DOI: 10.1145/1951365.1951432

Google Scholar

[2] Chang F; Dean J; Ghemawat S. Bigtable: A distributed storage system for structured data[J]. ACM Trans on Computer System (TOCS), 2008, 26(02): 1-26.

DOI: 10.1145/1365815.1365816

Google Scholar

[3] B. F. Cooper, R. Ramakrishnan, U. Srivastava, etc. PNUTS: Yahoo!'s hosted data serving platform[J]. Proc. VLDB Endow., 2008, 1(2): 1277-1288.

DOI: 10.14778/1454159.1454167

Google Scholar

[4] Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, etc. Dynamo: Amazon's Highly Available Key-value Store[J]. Operating systems review, 2007, 41(6): 205-220.

DOI: 10.1145/1323293.1294281

Google Scholar

[5] D. Agrawal, A. E. Abbadi, S. Antony, etc. Data management challenges in cloud computing inftrastructures[J]. In DNIS, 2010, 5999: 1-10.

Google Scholar

[6] D. J. Abadi. Consistency tradeoffs in modern distributed database system design: CAP is only part of the story[J]. Computer. 2012, 45(2): 37-42.

DOI: 10.1109/mc.2012.33

Google Scholar

[7] Yuan Long, Yan Zheng. A construction method of shard-nothing distributed database[J]. Computer technology and development, 2012, 22(10): 79-82.

Google Scholar

[8] Sukheja, D. Singh, U.K. Design of shared-nothing cluster architecture for fast accessing and highly availability of data in heterogeneous database environment[C]. Information and communication Technologies(WICT), 2011, 112-115.

DOI: 10.1109/wict.2011.6141227

Google Scholar

[9] Prabin R. Sahoo. Effective database migration strategy-the need for addressing database migration challenges of today, tomorrow and beyond[C]. 13th International Conference on Enterprise Information Systems. 2011: 2219-2222.

DOI: 10.5220/0003418103350338

Google Scholar

[10] Hengming Zou. Cloud computing déjà vu[M]. Beijing: Tsinghua University Press, 2013. 178-181.

Google Scholar

[11] Intple. DBOne. http: /www. intple. com/product-page_13/DBOne. html.

Google Scholar