Abstract
Cloud computing provides access to ”infinite” storage and computing resources, offering promising perspectives for many applications (medicine, nuclear physics, meteorology, etc.). However, this new paradigm requires rethinking of database management principles in order to allow deployment on scalable and easy to access infrastructures, applying a pay-as-you-go model. This position paper introduces building blocks to provide cost-aware semantic caching. To this end, we first introduce cost models for data management in the cloud, then we present a semantic caching framework providing finely tuned caches for different data analysis systems. This semantic caching framework is then discussed in the context of our previous work on rewriting rules and cache management for OLAP queries. Finally, it discusses the problem of query evaluation in the cloud in presence of semantic caches as a multi-criteria optimization problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Amazon. Dynamodb. Web page, http://aws.amazon.com/dynamodb/
Amazon. Elasticache. Web page, http://aws.amazon.com/elasticache/
Amazon. Rds. Web page, http://aws.amazon.com/rds/
Amazon. Simpledb. Web page, http://aws.amazon.com/simpledb/
Apache. Hadoop. Web page, http://hadoop.apache.org/
Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Communications of the ACM 53(4), 50–58 (2010)
Beyer, K.S., Ercegovac, V., Gemulla, R., Balmin, A., Eltabakh, M.Y., Kanne, C.-C., Özcan, F., Shekita, E.J.: Jaql: A scripting language for large scale semistructured data analysis. PVLDB 4(12), 1272–1283 (2011)
Chaiken, R., Jenkins, B., Larson, P.-Å., Ramsey, B., Shakib, D., Weaver, S., Zhou, J.: Scope: easy and efficient parallel processing of massive data sets. PVLDB 1(2), 1265–1276 (2008)
Chen, L., Rundensteiner, E.A., Wang, S.: Xcache: a semantic caching system for xml queries. In: SIGMOD, Madison, Wisconsin, USA, p. 618 (2002)
Chidlovskii, B., Borghoff, U.M.: Semantic caching of web queries. VLDBJ 9(1), 2–17 (2000)
Dar, S., Franklin, M.J., Jonsson, B.T., Srivastava, D., Tan, M.: Semantic data caching and replacement. In: VLDB, Bombay, India, pp. 330–341 (1996)
Dash, D., Kantere, V., Ailamaki, A.: An economic model for self-tuned cloud caching. In: ICDE, Shanghai, China, pp. 1687–1693 (2009)
Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: OSDI, San Francisco, California, USA, pp. 137–150 (2004)
d’Orazio, L., Roncancio, C., Labbé, C.: Adaptable cache service and application to grid caching. Concurrency and Computation: Practice and Experience 22(9), 1118–1137 (2010)
d’Orazio, L., Traore, M.K.: Semantic cache for pervasive grids. In: IDEAS, Cetraro, Italy, pp. 227–233 (2009)
Halevy, A.Y.: Answering queries using views: A survey. VLDBJ 10(4), 270–294 (2001)
Kantere, V., Dash, D., Gratsias, G., Ailamaki, A.: Predicting cost amortization for query services. In: SIGMOD, Athens, Greece, pp. 325–336 (2011)
Keller, A.M., Basu, J.: A predicate-based caching scheme for client-server database architectures. VLDBJ 5(1), 35–47 (1996)
Laurent, D., Spyratos, N.: Rewriting aggregate queries using functional dependencies. In: MEDES, San Francisco, CA, USA, pp. 40–47 (2011)
Lillis, K., Pitoura, E.: Cooperative xpath caching. In: SIGMOD, Vancouver, BC, Canada, pp. 327–338 (2008)
Memcached. Memcached. Web page, http://memcached.org/
Microsoft. Sql azure. Web page, http://www.windowsazure.com/en-us/home/features/data-management/
Nguyen, T.-V.-A., Bimonte, S., d’Orazio, L., Darmont, J.: Cost models for view materialization in the cloud. In: DanaC@EDBT, Berlin, Germany, pp. 47–54 (2012)
Olston, C., Reed, B., Srivastava, U., Kumar, R., Tomkins, A.: Pig latin: a not-so-foreign language for data processing. In: SIGMOD, Vancouver, BC, Canada, pp. 1099–1110 (2008)
Silva, Y.N., Larson, P.-A., Zhou, J.: Exploiting common subexpressions for cloud query processing. In: ICDE, Washington, DC, USA, pp. 1337–1348 (2012)
Spyratos, N.: The partition model: A deductive database model. ACM TODS 12, 1–37 (1987)
Thusoo, A., Sarma, J.S., Jain, N., Shao, Z., Chakka, P., Zhang, N., Anthony, S., Liu, H., Murthy, R.: Hive - a petabyte scale data warehouse using hadoop. In: ICDE, Long Beach, California, USA, pp. 996–1005 (2010)
Upadhyaya, P., Balazinska, M., Suciu, D.: How to price shared optimizations in the cloud. PVLDB 5(6), 562–573 (2012)
Vancea, A., Machado, G.S., d’Orazio, L., Stiller, B.: Cooperative database caching within cloud environments. In: Sadre, R., Novotný, J., Čeleda, P., Waldburger, M., Stiller, B. (eds.) AIMS 2012. LNCS, vol. 7279, pp. 14–25. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
d’Orazio, L., Laurent, D., Spyratos, N. (2013). Toward Cost-Aware Semantic Caching in the Cloud. In: Tanaka, Y., Spyratos, N., Yoshida, T., Meghini, C. (eds) Information Search, Integration and Personalization. ISIP 2012. Communications in Computer and Information Science, vol 146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40140-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-40140-4_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40139-8
Online ISBN: 978-3-642-40140-4
eBook Packages: Computer ScienceComputer Science (R0)