Abstract
Existing model persistence frameworks either store models as a whole or object by object. Since most modeling tasks work with larger aggregates of a model, existing persistence frameworks either load too many objects or access many objects individually. We propose to persist a model broken into larger fragments.
First, we assess the size of large models and describe typical usage patterns to show that most applications work with aggregates of model objects. Secondly, we provide an analytical framework to assess execution time gains for partially loading models fragmented with different granularity. Thirdly, we propose meta-model-based fragmentation that we implemented in an EMF based framework. Fourthly, we analyze our approach in comparison to other persistence frameworks based on four common modeling tasks: create/modify, traverse, query, and partial loads.
We show that there is no generally optimal fragmentation, that fragmentation can be achieved automatically and transparently, and that fragmentation provides considerable performance gains.
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References
Connected Data Objects (CDO), http://www.eclipse.org/cdo/
Grabats 2009, 5th International Workshop on Graph-based Tools: A Reverse Engineering Case Study (July 2009), http://is.tm.tue.nl/staff/pvgorp/events/grabats2009
Anderson, J.C., Lehnardt, J., Slater, N.: CouchDB: The Definitive Guide Time to Relax, 1st edn. O’Reilly Media, Inc. (2010)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A Distributed Storage System for Structured Data. In: Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2006, vol. 7, p. 15. USENIX Association, Berkeley (2006)
Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. Commun. ACM 51, 107–113 (2008)
DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., Sivasubramanian, S., Vosshall, P., Vogels, W.: Dynamo: Amazon’s Highly Available Key-Value Store. In: Proceedings of Twenty-First ACM SIGOPS Symposium on Operating Systems Principles, SOSP 2007, pp. 205–220. ACM, New York (2007)
Fowler, M.: Aggregate Oriented Databases (January 2012), http://martinfowler.com/bliki
Gröger, G., Kolbe, T.H., Czerwinski, A., Nagel, C.: OpenGIS City Geography Markup Language (CityGML) Encoding Standard, Version 1.0.0. Tech. Rep. Doc. No. 08-007r1, OGC, Wayland (MA), USA (2008)
Haerder, T., Reuter, A.: Principles of Transaction-Oriented Database Recovery. ACM Comput. Surv. 15, 287–317 (1983)
Hunt, B.: Mongoemf, http://github.com/BryanHunt/mongo-emf/wiki
Jézéquel, J.M., Barais, O., Fleurey, F.: Model Driven Language Engineering with Kermeta. In: Fernandes, J.M., Lämmel, R., Visser, J., Saraiva, J. (eds.) GTTSE 2011. LNCS, vol. 6491, pp. 201–221. Springer, Heidelberg (2011)
Khetrapal, A., Ganesh, V.: HBase and Hypertable for Large Scale Distributed Storage Systems A Performance evaluation for Open Source BigTable Implementations. Tech. rep., Purdue University (2008)
Lakshman, A., Malik, P.: Cassandra: Structured Storage System on a P2P Network. In: Proceedings of the 28th ACM Symposium on Principles of Distributed Computing, PODC 2009, p. 5. ACM, New York (2009)
Orend, K.: Analysis and Classification of NoSQL Databases and Evaluation of their Ability to Replace an Object-relational Persistence Layer. Master’s thesis, Technische Universität München (2010)
Pagán, J.E., Cuadrado, J.S., Molina, J.G.: Morsa: A Scalable Approach for Persisting and Accessing Large Models. In: Whittle, J., Clark, T., Kühne, T. (eds.) MODELS 2011. LNCS, vol. 6981, pp. 77–92. Springer, Heidelberg (2011)
Plugge, E., Hawkins, T., Membrey, P.: The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing, 1st edn. Apress, Berkely (2010)
Scheidgen, M.: EMFFrag – Meta-Model-based Model Fragmentation and Persistence Framework (2012), http://code.google.com/p/emf-fragments
Scheidgen, M.: How Big Are Models – An Estimation. Tech. rep. (2012)
Scheidgen, M., Zubow, A., Sombrutzki, R.: ClickWatch – An Experimentation Framework for Communication Network Test-beds. In: IEEE Wireless Communications and Networking Conference, France (2012)
Schütt, T., Schintke, F., Reinefeld, A.: Scalaris: Reliable Transactional P2P Key/Value Store. In: Proceedings of the 7th ACM SIGPLAN Workshop on ERLANG, ERLANG 2008, pp. 41–48. ACM, New York (2008)
Stadler, A.: Making interoperability persistent: A 3D geo database based on CityGML. In: Lee, J., Zlatanova, S. (eds.) Proceedings of the 3rd International Workshop on 3D Geo-Information, pp. 175–192. Springer, Seoul (2008)
Steinberg, D., Budinsky, F., Paternostro, M., Merks, E.: EMF: Eclipse Modeling Framework 2.0, 2nd edn. Addison-Wesley Professional (2009)
Thomas, D.: Programming With Models – Modeling with Code. Journal of Object Technology 5(8) (2006)
Zubow, A., Sombrutzki, R.: A Low-cost MIMO Mesh Testbed based on 802.11n. In: IEEE Wireless Communications and Networking Conference, France (2012)
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Scheidgen, M., Zubow, A., Fischer, J., Kolbe, T.H. (2012). Automated and Transparent Model Fragmentation for Persisting Large Models. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds) Model Driven Engineering Languages and Systems. MODELS 2012. Lecture Notes in Computer Science, vol 7590. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33666-9_8
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DOI: https://doi.org/10.1007/978-3-642-33666-9_8
Publisher Name: Springer, Berlin, Heidelberg
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